bluuebunny/crossref_metadata_2025 huggingface dataset:
A Sensitivity Analysis of Total‐Load Prediction Parameters in Standard Sediment Transport Equations1
Authors: Khorram Saeed , Ergil Mustafa
Published: September 2010

Khorram, Saeed and Mustafa Ergil, 2010. A Sensitivity Analysis of Total‐Load Prediction Parameters in Standard Sediment Transport Equations. Journal of the American Water Resources Association (JAWRA) 46(6):1091–1115. DOI: 10.1111/j.1752‐1688.2010.00469.x

Abstract:  The lack of a well‐defined, strong correlation between sediment transport load and the dominant variable selected for the development of a sediment transport equation is one of the fundamental reasons for discrepancies between computed and measured results under different flow and sediment conditions. Although several scholars have suggested different parameters, they unfortunately could not yet solve the problem. Twenty‐three total‐load equations for noncohesive particles were studied by providing insight into the relative strengths, weaknesses, and limitations. Three hundred parameters were investigated individually by using sensitivity analysis to pinpoint the key physical properties that control the errors. It is found that, the most influential parameter for the total‐load sediment flux equations used in alluvial rivers for the sand particles is the gravitational power due to Shields’ parameter with an energy slope. For the gravel particles, the most influential parameter is the universal stream power due to critical Shields’ parameter with an energy slope. Several graphs are presented to emphasize the effect of these parameters that were either directly used or were embedded within those equations. Recommendations and guides are also presented for the researchers working in this field.
Cross‐species amplification of 44 microsatellite loci developed for Chaetodon trifascialis, C. lunulatus and C. vagabundus in 22 related butterflyfish species
Authors: LAWTON REBECCA J. , PRATCHETT MORGAN S. , BAY LINE K.
Published: September 2010

Forty‐four microsatellite primers developed for three species of butterflyfish were cross‐tested against 22 related confamilial species. Amplification success and cross‐species transferability of these markers were moderately high. Between 24 and 37 loci were amplified successfully in each species, with a mean success rate per species of 71.7% (± 1.8 SE). Rates of amplification success were comparable among primers designed for the three source species, ranging from a mean success rate per species of 16.9 loci (± 0.8 SE) for Chaetodon trifascialis source loci to 13.7 loci (± 1.5 SE) for C. vagabundus source loci. Polymorphism rates were high (76.1%± 3.1 SE of all successfully amplified loci), and 10 loci were polymorphic in all successfully amplified species (Tri14, B11, C5, D3, D113, D6, D117, D120, D111, D118). The number of alleles per polymorphic locus ranged from 2 to 8, and the average number of alleles across all polymorphic loci and all species was 3.6 (± 0.07 SE). Polymorphism rates were higher overall in primers designed for C. vagabundus (89.9%± 3.9 SE). Overall cross‐testing success was lowest for Heniochus chrysostomus, the most phylogenetically divergent species. The significant cross‐testing reported here provides a valuable resource that will enable population genetics studies to be undertaken on a range of butterflyfishes without the need for expensive and time‐consuming de novo microsatellite development.
Sevoflurane Postconditioning Ameliorates Oxygen–Glucose Deprivation—Reperfusion Injury in the Rat Hippocampus
Authors: Peng Sheng , Kalikiri Pramood , Mychaskiw II George , Zhang Dengxin , Zhang Yan , Liu Gong‐Jian , Wang Guang‐Lei , Shen Zhi‐yun
Published: September 2010

Introduction: Sevoflurane is well known to exert a neuroprotective effect through anesthetic preconditioning. However, its effects on postconditioning, a neuroprotective phenomenon following an insult, have not been well studied. Aims: In this study, we examined the ability of sevoflurane to induce postconditioning in rat hippocampal slices, in vitro. Results: 2%, 4%, and 6% sevoflurane reduced neurophysiologic and morphologic neuronal injury following oxygen–glucose deprivation (OGD) and reperfusion. The quantity of damaged neurons was significantly reduced on immunofluorescence staining; excitatory amino acids (Asp, Glu) increased and inhibitory amino acids (GABA) decreased significantly. The effect was concentration‐dependent. Conclusion: Postconditioning with sevoflurane reduces neuronal damage after OGD—reperfusion injury in the CA1 area of rat hippocampus, in vitro.
The prevalence of functional quorum‐sensing systems in recently emerged Vibrio cholerae toxigenic strains
Authors: Wang Yunduan , Wang Hui , Cui Zhigang , Chen Haili , Zhong Zengtao , Kan Biao , Zhu Jun
Published: September 2010

Vibrio cholerae live in aquatic environments and cause cholera disease. Like many other bacteria, V. cholerae use quorum‐sensing (QS) systems to control various cellular functions, such as pathogenesis and biofilm formation. However, some V. cholerae strains are naturally QS‐defective, including defective mutations in the QS master regulator HapR. Here we examined the QS functionality of 602 V. cholerae clinical and environmental strains isolated in China from 1960 to 2007, by measuring QS‐regulated gene expression. We found that a greater percentage of the toxigenic strains (ctxAB+) had functional QS as compared with the non‐toxigenic strains (ctxAB‐), and that this trend increased significantly over time. We hypothesize that QS provides adaptive value in V. cholerae pathogenic settings.
Results of laparoscopic sleeve gastrectomy as a single stage bariatric procedure in Japanese patients
Authors: Sasaki A , Umemura A , Nishizuka S , Nakajima J , Uesugi N , Wakabayashi G
Published: September 2010

Introduction: Laparoscopic sleeve gastrectomy (LSG) is a quick and relatively simple bariatric operation, which thus far has shown good resolution of comorbidities and weight loss. Here we report on the short‐term outcomes of LSG as a single‐stage bariatric procedure in Japanese cases of morbid obesity.

Methods: Between June 2008 and January 2010, seven Japanese morbidly obese patients underwent LSG. The data collected included patient demographics, clinical outcomes, changes in ghrelin, and gastric expressions of ghrelin.

Results: Late gastric leak occurred in one patient and was treated with an endoscopic mucosal closure after failed attempts to treat percutaneous abdominal drainage. The median postoperative body weight loss at 6 months and 1 year were 41 kg (range, 22–45 kg) and 55 kg (range, 52–58 kg), respectively. The median percentage excess weight loss at 6 months and 1 year were 56% (range, 42%–70%) and 68% (range, 49%–87%), respectively. Resolution or improvement rates of comorbidities in the five patients followed up for more than 6 months were 100% for type 2 diabetes, hypertension, sleep apnea syndrome, and dyslipidemia, and 80% for hyperuremia. Plasma ghrelin levels were very low and were not significantly different postoperatively, and the number of ghrelin‐positive cells assessed by immunochemistry of the gastric fundus was similar to that of the control group.

Discussion: For Japanese patients with morbid obesity, LSG may represent an effective weight loss method that can resolve comorbidities in a single‐stage bariatric procedure. Further studies are required to determine the long‐term efficacy of LSG in term of weight loss.
Autoimmunity as a principal pathogenic factor in the refined model of neuropsychiatric lupus
Authors: Loheswaran Genane , Stanojcic Mile , Xu Li , Sakic Boris
Published: September 2010

Objectives:  Over the past decades, the MRL mouse model had shown significant validity in elucidating the pathogenesis of neuropsychiatric lupus erythematosus (NP SLE). However, the possibility that the inherited Fas receptor deficiency (and not autoimmunity) accounts for central nervous system (CNS) damage in the original stock 485 of MRL/MpJ‐Faslpr mice could not be rejected. The aim of the present study was to examine the consequences of autoimmune disease on behavior and brain morphology, while controlling for the genetic deficiency with a new, less symptomatic 6825 stock.

Methods:  Spleen mass, serum autoantibody and cytokine levels, immunoglobulins in cerebrospinal fluid (CSF), and brain planimetry were used to assess disease severity and CNS involvement in 5‐month‐old mice from stocks 6825 and 485. Their behavioral profiles were compared in a standard battery of tasks. The 2D‐DIGE and mass spectrometry examined brain antigens targeted by autoantibodies from serum and CSF.

Results:  The 6825 mice had smaller spleens, lower antibody and cytokine levels, and less IgG in the CSF. They were more active and showed better performance in tasks reflective of anxiety and motivated behavior. Signs of brain pathology were less profound and their CSF autoantibodies showed reduced affinity for brain antigens, largely characterized as highly‐conserved cytoskeletal proteins.

Conclusions:  The constellation of differences between the two MRL/MpJ‐Faslpr stocks confirms that the lpr mutation per se does not account for the brain pathology and altered behavior in the 485 stock. Together with significant correlations between immunological and behavioral measures, this observation suggests that soluble immune factors play a key role in pathogenesis of NP SLE. (Clin. Exp. Neuroimmunol. doi: 10.1111/j.1759‐1961.2010.00014.x, September 2010)
SUPER‐HEURISTICS AND THEIR APPLICATIONS TO COMBINATORIAL PROBLEMS
Authors: Lau Tak Wing Edward , Ho Yu‐Chi
Published: September 2010

Combinatorial problems are known to be difficult because of the shear size of the solution space and the lack of polynomial time algorithms to “solve” them. Heuristics are often devised to produce acceptable solutions in an affordable time. In this paper, we propose a method called super‐heuristic that expands the capabilities of heuristics using randomization and sampling techniques. We submit that heuristics are in general strategies that map from available information of a problem instance to decisions in solution constructions/improvement. We show that it is important to utilize the information effectively in the randomization process. More importantly, the possibility of randomization around a heuristic spells out the demarcation between the roles of human and machines in complex optimization problems.
THE ROLE OF EULER PARAMETERS IN ROBOT CONTROL
Authors: Caccavale Fabrizio , Siciliano Bruno , Villani Luigi
Published: September 2010

Euler parameters constitute a well‐known nonminimal singularity‐free representation of rigid body orientation. This paper is aimed at illustrating the role of Euler parameters in robot control; namely, the kinematic control, dynamic control and impedance control problems are surveyed in a unifying perspective, where robot's end‐effector orientation displacements are described in terms of Euler parameters. The advantages over the Euler angles typically used in the operational space framework are demonstrated.
IMPROVED CONTINUATION METHOD CONTROLLER FOR PWM SYSTEMS: AN EXPERIMENTAL CASE STUDY
Authors: Iwata T. , Yamakita M. , Furuta K.
Published: September 2010

In this paper, an improved version of online continuation method controller for PWM systems is presented. The online continuation method controller solves the PWM‐type deadbeat control problem numerically. By using this algorithm, iterations for solving the set of nonlinear equations always start from a good solution candidate and therefore it can be used online. The original continuation method is modified so that it is applicable to real systems. The validity of the proposed control method is demonstrated by a laboratory‐scale flexible arm manipulator.
BLOCK DECOUPLING CONTROL OF LINEAR MULTIVARIABLE SYSTEMS
Authors: Lin Ching‐An , Wu Chang‐Ming
Published: September 2010

This paper gives parameterizations of block decoupling controllers and achievable block‐diagonal I/O maps for linear multivariable plants under unity‐feedback configuration. The parameterizations, based on coprime factorizations and a special generalized Bezout identity, do not require the computation of Smith McMillan forms and, thus, can be reliably computed. It is also shown that through the construction of an admissible block decoupling precompensator, block decoupling controller design reduces to a set of controller designs for the block channels which are smaller in dimension.
A STABLE SELF‐LEARNING OPTIMAL FUZZY CONTROL SYSTEM
Authors: Lin Sinn‐Cheng , Chen Yung‐Yaw
Published: September 2010

The issue of developing a stable self‐learning optimal fuzzy control system is discussed in this paper. Three chief objectives are accomplished: 1) To develop a self‐learning fuzzy controller based on genetic algorithms. In the proposed methodology, the concept of a fuzzy sliding mode is introduced to specify the system response, to simplify the fuzzy rules and to shorten the chromosome length. The speed of fuzzy inference and genetic evolution of the proposed strategy, consequently, is higher than that of the conventional fuzzy logic control. 2) To guarantee the stability of the learning control system. A hitting controller is designed to achieve this requirement. It works as an auxiliary controller and supports the self‐learning fuzzy controller in the following manner. When the learning controller works well enough to allow the system state to lie inside a pre‐defined boundary layer, the hitting controller is disabled. On the other hand, if the system tends to diverge, the hitting controller is turned on to pull the state back. The system is therefore stable in the sense that the state is bounded by the boundary layer. 3) To explore a fuzzy rule‐base that can minimize a standard quadratic cost function. Based on the fuzzy sliding regime, the problem of minimizing the quadratic cost function can be transformed into that of deriving an optimal sliding surface. Consequently, the proposed learning scheme is directly applied to extract the optimal fuzzy rulebase. That is, the faster the hitting time a controller has and the shorter the distance from the sliding surface the higher fitness it possesses. The superiority of the proposed approach is verified through simulations.
APPLICATION OF H∞ CONTROL AND CLOSED LOOP IDENTIFICATION TO A MAGNETIC LEVITATION SYSTEM
Authors: Tsujino Taro , Nakashima Ken'ichi , Fujii Takao
Published: September 2010

A systematic procedure for modeling and robust control of a multivariable magnetic levitation system is described. Our previous study revealed that an observer‐based LQ controller can stabilize the system, but generates spillovers in the presence of an impulse disturbance. To solve this problem, we apply an H∞ control to suppress the spillovers caused by unmodeled dynamics which we estimate using closed loop identification. First, an exactly linearized model is obtained to compensate for nonlinearities in the system, followed by estimation of the unmodeled dynamics using closed loop identification. Second, this information is used to design a two degree of freedom H∞ servo system for suppressing the spillover while tracking a step reference input. Finally, the desired robust performance of the resulting servo system is confirmed theoretically by γ‐analysis and also experimentally.
GUIDANCE LAW EVALUATION FOR MISSILE GUIDANCE SYSTEMS
Authors: Lin Chih‐Min , Hsu Chun‐Fei , Chang Shing‐Kuo , Wai Rong‐Jong
Published: September 2010

In missile guidance system, to reduce the interception “miss distance,” it is important to choose a suitable guidance law and navigation constant. This paper investigates and compares the system behavior of guidance laws under different navigation constants. Based on use of the adjoint technique, miss distance sensitivity analyses which consider the system noise, target step maneuver, initial heading error and system parameters for different guidance laws and navigation constants are presented. Based on these analyses, some suggestions for choosing a suitable guidance law and navigation constant are given for the design of missile guidance systems. Also, a suggestion for the optimal escape time for pilots of fighter planes is given.
SINGULARITY COMPUTATION FOR ITERATIVE CONTROL OF NONLINEAR AFFINE SYSTEMS
Authors: Popa Dan O. , Wen John T.
Published: September 2010

This paper considers a gradient type of iterative algorithm applied to the open loop control for nonlinear affine systems. The convergence of the algorithm relies on the control signal in each iteration be nonsingular. We present an algorithm for computing the singular control for a general class of nonlinear affine systems. Various nonlinear mechanical systems, including nonholonomic systems, are included as examples.
IMPLEMENTATION OF A DRIVING SIMULATOR BASED ON A STEWART PLATFORM AND COMPUTER GRAPHICS TECHNOLOGIES
Authors: Tseng Hung‐Lung , Fong I‐Kong
Published: September 2010

This paper describes works related to the development of a land vehicle driving simulator, which consists of a Stewart platform as its motion device and a computer graphical system as its visual component. The main task is to enable the pilot‐experience the sensation of motion while driving the vehicle under the constraint of the platform's finite working space. Involved are works such as establishment of the vehicle dynamical model, analysis of the forces acting on the pilot, and application of the washout algorithm and human motion sensation models. With the results from these works, appropriate motion trajectory commands for the platform can be generated. Besides the physical motion part, a computer graphical system is installed to generate scenes that give visual cues. While following the pilot's steering signals and matching the platform's motion, the visual system creates animation scenes of the environment, which are shown on a large screen in front of the pilot through an LCD projector. To test the completed system, different pilots operate it and give subjective assessments. Also, gyros are mounted on the platform to measure its responses to motion commands. Here some experimental results are summarized and discussed.
ROBUST NONLINEAR CONTROLLER DESIGN FOR A LONGITUDINAL FLIGHT CONTROL PROBLEM
Authors: Hu Shr‐Shiung , Chang B.C. , Yeh H.H. , Kwatny H.G.
Published: September 2010

In this paper, the H∞ approximate I/O linearization formulation and μ‐synthesis are employed to design a nonlinear controller for an aircraft longitudinal flight control problem. We propose modified nonlinear H∞ controller formulas to approximately linearize the system and use μ‐synthesis to address tracking, regulation, and robustness issues.
OPEN‐LOOP AND CLOSED‐LOOP OPTIMIZATION OF LINEAR CONTROL SYSTEMS
Authors: Gabasov R. , Kirillova F.M. , Balashevich N.V.
Published: September 2010

A canonical optimal control problem for linear systems with time‐varying coefficients is considered in the class of discrete controls. On the basis of linear programming methods, two primal and two dual methods of constructing optimal open‐loop controls are proposed. A method of synthesis of optimal feedback control is described. Results are illustrated by a fourth‐order problem; estimates of efficiency of proposed methods are given.
AN ALGORITHM FOR DIGITAL IMPLEMENTATION OF TRAJECTORY TRACKING CONTROLLERS
Authors: Aguilar J. L. Mancilla , García R. A. , Troparevsky M. I.
Published: September 2010

In this work, we study the problem of the digital implementation of continuous‐time solutions to the trajectory tracking control problem for nonlinear systems. We exhibit an example that shows that, in general, no proper behavior of the tracking error can be expected when these solutions are implemented via the Sampling and Zero Order Hold technique. Inspired in some constructions developed in the context of Positional Games, we present a sampled‐data controller that, based on a continuous‐time solution of the tracking problem, assures semiglobal practical stability of the tracking error, with final error arbitrarily small if we choose a suitable sampling period. The controller is robust with respect to small external disturbances and small errors in the measurements.
A Learning‐Theoretic Approach To Model‐Set Identification
Authors: Oishi Yasuaki , Kimura Hidenori
Published: September 2010

A new approach to model‐set identification is proposed based on an agnostic learning theory. The squared prediction error is estimated together with its uncertainty uniformly in some parameter region. Based on this estimation, a model set is constructed so as to include the best model. The proposed approach does not require assumptions on the true dynamics or the noise, neither does it need infinite number of input‐output data in order to justify its result. But it guarantees that the size of the identified model set converges to zero as the number of input‐output data increases. Improvement of the precision is considered on the proposed identification method. Generalization of the approach is discussed and a numerical example is presented.
Just‐in‐Time Modeling for Function Prediction and Its Applications
Authors: Zheng Qiubao , Kimura Hidenori
Published: September 2010

This paper introduces a variant of k Bipartite Neighbors (k‐BN), called k‐BN2, for use in function prediction. Like k‐BN, k‐BN2 selects k instances surrounding the query, i.e., the novel instance, and keeps them bipartitely. However, in order to improve the prediction precision, based on the bipartite neighborhood, k‐BN2 combines local linear models and the global nonlinear model to predict the value of the novel instance. Applied to two real measured datasets, k‐BN2 outperforms the typical k‐BN andthose methods in which k‐BN or a related approximate physical model alone is exploited.
Stability of a Trajectory‐Based Control Law for an Unknown Nonlinear Non‐Minimum Phase System
Authors: Brockwell Anthony , Evans Rob , Mareels Iven
Published: September 2010

We investigate the stability of an unknown nonlinear discrete‐time non‐minimum phase system under a trajectory‐based control law. The system can be regarded as a first‐order approximation to a continuous‐time system. Hence, one of the parameters in the discrete‐time system equation can be regarded as the “sampling interval”. We show that, subject to certain conditions, as long as the sampling interval is neither too short nor too long, the closed‐loop system is stable in a certain sense.
The Search of Equilibrium Strategies for Controlled Boundary Value Problem
Authors: Vasilieva Olga
Published: September 2010

The present paper is focused on the finite‐time differential game of m players with nonzero sum. The principal difference from regular cases consists in the fact that the states of players are subordinated to boundary value system of ordinary differential equations (rather than the initial value system). By the end of the game we understand the equilibrium situation and our purpose is to design a well‐founded suitable method for the equilibrium control search.
H∞ Control of Linear Discrete‐Time Systems With Norm‐Bounded Nonlinear Uncertainties
Authors: Peng Zhihong , Cai Zixing
Published: September 2010

In this paper, robust H∞ control of a class of discrete‐time uncertain systems in state‐space form with linear nominal parts and norm‐bounded nonlinear uncertainties in both state and output equations is discussed. Such systems have a unique characterisic; that is, the two norm‐bounded nonlinear uncertainties have the equivalent representation by means of time‐varying and norm‐bounded linear uncertainties. To overcome the conservativenss of [5], the two nonlinear uncertainty sets are considered to be different. Then, by converting such systems into related discrete‐time linear systems with time‐varying and norm‐bounded linear uncertainties, we obtain that a sufficient condition for robust H∞ control of such systems is equivalent to the solvability of the same problem of the related linear uncertain systems, which is solvable by means of a linear algebraic Riccati inequality.
On The Approximation Capability of Neural Networks ‐ Dynamic System Modeling and Control
Authors: Chak Chu Kwong , Feng Gang , Ma Jian
Published: September 2010

This paper discusses issues related to the approximation capability of neural networks in modeling and control. We show that neural networks are universal models and universal controllers for a class of nonlinear dynamic systems. That is, for a given dynamic system, there exists a neural network which can model the system to any degree of accuracy over time. Moreover, if the system to be controlled is stabilized by a continuous controller, then there exists a neural network which can approximate the controller such that the system controlled by the neural network is also stabilized with a given bound of output error.
Design of an Optimal Unknown Input Observer for Load Compensation in Motion Systems
Authors: Hsu Pau‐Lo , Houng Yow‐Choung , Yeh Syh‐Shiuh
Published: September 2010

Recently, several model‐based control designs have been proposed for motion systems and computerized numerical control (CNC) machines to improve motion accuracy. However, in real applications, their performance is seriously degraded when significant disturbances or cutting forces are applied. In this paper, we derive straightforward design procedures for a general‐structured unknown input observer (UIO) which perfectly decouples the effect of the external disturbance from the state estimation. Furthermore, we derive the optimal UIO by minimizing the estimation errors for both the state and the disturbance via the Riccati equation. Experimental results show that the performance of alladvanced motion controllers suffers when external loads are applied. By compensating for the disturbance of a servo motor using the proposed optimal‐UIO, the original contouring accuracy, which is degraded by the external loading, can be successfully recovered.
Fine Tuning Of Membership Functions For Fuzzy Neural Systems
Authors: Lee Ching‐Hung , Teng Ching‐Cheng
Published: September 2010

This paper presents a new method for fine‐tuning the Gaussian membership functions of a fuzzy neural network (FNN) to improve approximation accuracy. This method results in special shape membership functions without the convex property. We first recall that any continuous function can be represented by a linear combination of Gaussian functions with any standard deviation. Therefore, the Gaussian membership function in the second layer of the FNN can be replaced by several small Gaussian functions; the weighting vectors of this new network (called FNN5) can then be updated using the backpropagation algorithm. The proposed method can adapt proper membership functions for any nonlinear input/output mapping to achieve highly accurate approximation. Convergence analysis shows that the weighting vectors of the FNN5 eventually converge to the optimal values. Simulation results indicate that (a) this approach improves approximation accuracy, and (b) that the number of rules can be reduced for any given level of accuracy. For the purpose of illustrating the proposed method, the FNN5 is also applied to tune PI controllers such that gain and phase margins of the closed‐loop system achieve the desired specifications.
Aggressive Longitudinal Aircraft Path Tracking Using Nonlinear Control
Authors: Al‐Hiddabi Saif A. , McClamroch N. Harris
Published: September 2010

We study the problem of converting a trajectory tracking controller to a path tracking controller for a nonlinear non‐minimum phase longitudinal aircraft model. The solution of the trajectory tracking problem is based on the requirement that the aircraft follows a given time parameterized trajectory in inertial frame. In this paper we introduce an alternative nonlinear control design approach called path tracking control. The path tracking approach is based on designing a nonlinear state feedback controller that maintains a desired speed along a desired path with closed loop stability. This design approach is different from the trajectory tracking approach where aircraft speed and position are regulated along the desired path. The path tracking controller regulates the position errors transverse to the desired path but it does not regulate the position error along the desired path. First, a trajectory tracking controller, consisting of feedforward and static state feedback, is designed to guarantee uniform asymptotic trajectory tracking. The feedforward is determined by solving a stable noncausal inversion problem. Constant feedback gains are determined based on LQR with singular perturbation approach. A path tracking controller is then obtained from the trajectory tracking controller by introducing a suitable state projection.
Evolutionary‐Programming‐Based Kalman Filter for Discrete‐Time Nonlinear Uncertain Systems
Authors: Guo Shu‐Mei , Shieh Leang‐San , Lin Ching‐Fang , Coleman Norman P.
Published: September 2010

Some observations and improvements on the conventional Kalman filtering scheme to function properly are presented. The improvements can be achieved using the minimal principle evolutionary programming (EP) technique. A new linearization methodology is presented to obtain the exact linear models of a class of discrete‐time nonlinear time‐invariant systems at operating states of interest, so that the conventional Kalman filter can work for the nonlinear stochastic systems. Furthermore, a Kalman innovation filtering algorithm and such an algorithm based on the evolutionary programming optimal‐search technique are proposed in this paper for discrete‐time time‐invariant nonlinear stochastic systems with unknown‐but‐bounded plant uncertainties and noise uncertainties to find a practically implementable “best” Kalman filter. The worst‐case realization of the discrete‐time nonlinear stochastic uncertain systems represented by the interval form with respect to the implemented “best” nominal filter is also found in this paper for demonstrating the effectiveness of the proposed filtering scheme.
A Study On Iterative Learning Control With Adjustment Of Learning Interval For Monotone Convergence In The Sense Of Sup‐Norm
Authors: Park Kwang‐Hyun , Bien Zeungnam
Published: September 2010

It has been found that some huge overshoot in the sense of sup‐norm may be observed when typical iterative learning control (ILC) algorithms are applied to LTI systems, even though monotone convergence in the sense of λ‐norm is guaranteed. In this paper, a new ILC algorithm with adjustment of learning interval is proposed to resolve such an undesirable phenomenon, and it is shown that the output error can be monotonically converged to zero in the sense of sup‐norm when the proposed ILC algorithm is applied. A numerical example is given to show the effectiveness of the proposed algorithm.
Bifurcation Analysis of the Zero Dynamics and the Practical Stabilization of Nonlinear Minimum‐Phase Systems
Authors: Byrnes C.I. , Isidori A.
Published: September 2010

It is well‐known that, in a globally minimum phase nonlinear system, high‐gain output feedback can be used to steer trajectories from any arbitrarily large compact set to any arbitrary small neighborhood of the origin. The question, however, of describing the asymptotic behavior of the closed loop system so obtained inside this small neighborhood has remained open. In this paper we address this question. In particular, we describe explicitly, in terms of properties of the open‐loop system, the structure of certain compact attractors that might exists and determine their stability in the sense of Lyapunov.
Liding Control With Genetic Algorithm for Mismatched Disturbance
Authors: Chang Jeang‐Lin , Li Keh‐Tsong , Chen Yon‐Ping
Published: September 2010

This paper presents a new sliding control to deal with linear systems suffering from matched‐to‐part disturbance and mismatched disturbance. Only parts of the control inputs are designed using the sliding‐mode theory in order to eliminate the matched‐to‐part disturbance. Based on an important criterion, the proposed controller employs the applicable genetic algorithm to effectively reduce the influence of mismatched disturbance during sliding motion. A numeric example is used to demonstrate the effectiveness of the developed controller.
Discrete Sliding‐Mode Control of Mimo Linear Systems
Authors: Chang Jeang‐Lin
Published: September 2010

This paper introduces a discrete sliding‐mode control for linear time‐invariant systems in the presence of matched uncertainties. The switching surface is constructed by applying the pole‐assignment method applying to the overall system, not the system in the sliding mode. Importantly, the control algorithm is derived to handle the rate of convergence to the sliding mode and to prevent the control law from encountering any unreasonably large variations. As for the system stability, it can be found that the system is stabilized and finally restricted to a known region. A numerical example is also included to demonstrate all the features of the developed discrete sliding‐mode control.
Resilient H∞ Control Design for Discrete‐Time Uncertain Linear Systems: An Auxiliary System Transformation Approach
Authors: Yee Jiong‐Sang , Wang Jian Liang , Yang Guang‐Hong
Published: September 2010

This paper studies the resilient (non‐fragile) H∞ output‐feedback control design for discrete‐time uncertain linear systems with controller uncertainty. The design considers parametric norm‐bounded uncertainty in all state‐space matrices of the system, output and controller equations. The paper shows that the resilient H∞ output‐feedback control problem is equivalent to a scaled H∞ output‐feedback control problem of an auxiliary system without any system or controller uncertainty. Using the existing optimal H∞ design to solve the auxiliary system, the design guarantees that the resultant closed‐loop systems are quadratically stable with disturbance attenuation γ for all admissible system and controller uncertainties. A numerical example is given to illustrate the design method and its benefits.
Recursive Back‐Stepping Design of An Adaptive Fuzzy Controller for Strict Output Feedback Nonlinear Systems
Authors: Wang Wei‐Yen , Chan Mei‐Lang , Lee Tsu‐Tian , Liu Cheng‐Hsin
Published: September 2010

In this paper, a back‐stepping adaptive fuzzy controller is proposed for strict output feedback nonlinear systems. The unknown nonlinearity and external disturbances of such systems are considered. We assume that only the output of the system is available for measurement. As a result, two filters are constructed to estimate the states of strict output feedback systems. Since fuzzy systems can uniformly approximate nonlinear continuous functions to arbitrary accuracy, the adaptive fuzzy control theory combined with a tuning function scheme is developed to derive the control laws of strict output feedback systems that possess unknown functions. Moreover, the H∞ performance condition is introduced to attenuate the effect of the modeling error and external disturbances. Finally, an example is simulated in order to confirm the applicability of the proposed method.
H∞ Control and Sliding Mode Control of Magnetic Levitation System
Authors: Shen Jing‐Chung
Published: September 2010

In this paper, H∞ disturbance attenuation control and sliding mode disturbance estimation and compensation control of a magnetic levitation system are studied. A magnetic levitation apparatus is established, and its model is measured. Then the system model is feedback linearized. A H∞ controller is then designed. For comparison, a sliding mode controller and a PID controller also were designed. Some experiments were performed to compare the performance of the H∞ controller, the sliding mode controller and the PID controller.
Output Feedback Sliding Mode Controller Design Via H∞ THEORY
Authors: Chang Jeang‐Lin
Published: September 2010

For a linear system with mismatched disturbances, a sliding mode controller using only output feedback is developed in this paper. Through application of the H∞ control theory, the designed switching surface can achieve robust stabilization and guarantee a level of disturbance rejection during sliding mode. Although the system exhibits disturbances, a state estimator is used which, using only measured outputs, can asymptotically estimate the system states. The control law is designed with respect to the estimated signals. Finally, a numerical example is presented to demonstrate the proposed control scheme.
Pid Regulation Of Robot Manipulators With Elastic Joints
Authors: Alvarez‐Ramirez Jose , Cervantes Ilse
Published: September 2010

This paper studies the stability of a class of PID controller to stabilize robot manipulators with elastic joints. It is shown that a PD action on the rotor position and an integral control action on the link position suffice to provide semiglobal asymptotic stability of the desired link position.
Digital Redesign Of Continuous‐Time Suboptimal Tracker For Two‐Dimensional Systems
Authors: Li Jimshone , Tsai Jason Sheng‐Hong , Shieh Leang‐San
Published: September 2010

In this paper, the digital redesign of a continuous suboptimal tracker for the two‐dimensional (2‐D) systems is proposed. This paper presents a new optimal digital redesign technique of 2‐D systems for finding a dynamic digital control law from the given continuous‐time 2‐D systems by minimizing a quadratic cost function (performance index). We directly convert the original continuous‐time 2‐D quadratic cost function into the discretized form and solve the optimization problem in the discrete‐time domain. The developed optimal digital redesign control law enables the output of the digitally controlled closed‐loop systems to closely match the reference signal for 2‐D systems, and it can be easily implemented using microcomputers. An illustrative example is presented to demonstrate the effectiveness of the proposed procedure.
Reliable State Feedback Control Synthesis For Uncertain Linear Systems
Authors: Yang Guang‐Hong , Wang Jian Liang , Soh Yeng Chai , Lou Kok‐Yong
Published: September 2010

This paper is concerned with the problem of designing reliable state‐ feedback control for a class of uncertain linear systems with norm bounded uncertainty. A procedure for designing reliable state‐feedback control is presented for the case of actuator faults that can be modeled by a scaling factor. In the design, the performance of the normal system (without fault) is optimized, as the considered system operates under the normal condition most of the time. In addition, when actuator faults occur, the closed‐loop system retains robust stability and satisfies a known quadratic performance bound. A numerical example is provided to illustrate the effectiveness of the proposed design method.
On Velocity‐Based Local Model Networks For Nonlinear Identification
Authors: McLoone Séamus C. , Irwin George W.
Published: September 2010

This paper exposes the strengths and weaknesses of the recently proposed velocity‐based local model (LM) network. The global dynamics of the velocity‐based blended representation are directly related to the dynamics of the underlying local models, an important property in the design of local controller networks. Furthermore, the sub‐models are continuous‐time and linear providing continuity with established linear theory and methods. This is not true for the conventional LM framework, where the global dynamics are only weakly related to the affine sub‐models. In this paper, a velocity‐based multiple model network is identified for a highly nonlinear dynamical system. The results show excellent dynamical modelling performances, highlighting the value of the velocity‐based approach for the design and analysis of LM based control. Three important practical issues are also addressed. These relate to the blending of the velocity‐based local models, the use of normalised Gaussian basis functions and the requirement of an input derivative.
Regularizability Of Linear Descriptor Systems Via Output Plus Partial State Derivative Feedback
Authors: Duan Guang‐Ren , Zhang Xian
Published: September 2010

Regularizability of a linear descriptor system via output plus partial state derivative feedback is studied. Necessary and sufficient conditions are obtained, which are only dependent upon the open‐loop coefficient matrices. It is also shown that under these necessary and sufficient conditions, “almost all” output plus partial state derivative feedback controllers can regularize a regularizable linear descriptor system. The proposed conditions generalize many existing results. The presented example demonstrates the proposed results.
Computationally Efficient Algorithm For Frequency‐Weighted OptimalH∞Model Reduction
Authors: Wu Fen , Jaramillo Juan J.
Published: September 2010

In this paper, a frequency‐weighted optimalH∞model reduction problem for linear time‐invariant (LTI) systems is considered. The objective of this class of model reduction problems is to minimizeH∞norm of the frequency‐weighted truncation error between a given LTI system and its lower order approximation. A necessary and sufficient solvability condition is derived in terms of LMIs with one extra coupling rank constraint, which generally leads to a non‐convex feasibility problem. Moreover, it has been shown that the reduced‐order model is stable when both stable input and output weights are included, and its state‐space data are given explicitly by the solution of the feasibility problem. An efficient model reduction scheme based on cone complementarity algorithm (CCA) is proposed to solve the non‐convex conditions involving rank constraint.
Robust H∞ Filtering For Uncertain Stochastic Time‐Delay Systems
Authors: Xu Shengyuan , Chen Tongwen
Published: September 2010

This paper deals with the problem of robust H∞ filtering for uncertain stochastic systems. The system under consideration is subject to time‐varying norm‐bounded parameter uncertainties and unknown time delays in both the state and measurement equations. The problem we address is the design of a stable filter that ensures the robust stochastic stability and a prescribed H∞ performance level for the filtering error system irrespective of all admissible uncertainties and time delays. A suffient condition for the solvability of this problem is proposed and a linear matrix inequality approach is developed for the design of the robust H∞ filters. An illustrative example is provided to demonstrate the effctiveness of the proposed approach.
Toward The Implementation Of A Seek‐Controller For An Optical Pick‐Up Head Using A Discrete Sliding‐Mode Control Scheme
Authors: Tai Tsang‐Li , Chen Jian‐Shiang
Published: September 2010

Chattering is inevitable in most sliding‐mode controllers due to finite and imperfect switching. Most of the discrete‐time sliding‐mode schemes reported to date fail to alleviate chattering effectively; even under perturbation‐free conditions, chattering is still inevitable. This present work proposes a scheme that can guarantee both one‐sided behavior and chattering‐free performance with uncertainties of the known bounds of the plant. This scheme is applied to the design of a seek‐controller for an optical pick‐up head to illustrate its feasibility. Both simulation and experimental studies were performed to further validate its effectiveness.
Robust Stability For Uncertain Discrete Singular Systems With State Delay
Authors: Xu Shengyuan , Lam James
Published: September 2010

A computationally simple stability condition for discrete singular systems with state delay is presented in this paper. Based on this, a robust stability result for such systems with structured parametric uncertainties is given. This condition ensures that, for all admissible uncertainties, the system under consideration is regular, causal and stable. Then D‐stability results for discrete singular delay systems are obtained. All the proposed conditions are easy to test.
Period And Priority Assignment Method For Dcs Design
Authors: Kim Hyoung Yuk , Park Hong Seong
Published: September 2010

Distributed control systems (DCS) used in industry environments consist of sensors, actuators, and controllers that are connected with a fieldbus. It is difficult to design the DCS while guaranteeing the time‐critical requirements because of both communication delays due to the fieldbus and computation delays due to many tasks executed in one node. This paper proposes a priority assignment method and a period assignment method that find the shortest periods of control loops and guarantee the end‐to‐end constraints such as precedence constraints and timing constraints. Also, a DCS design method is presented by using the proposed two assignment methods. The presented design method considers the worst‐case response times of tasks and messages simultaneously and is applicable to a practical DCS, which consists of several constraints. The design method is validated by examples.
SLIDING MODES, Δ‐MODULATORS, AND GENERALIZED PROPORTIONAL INTEGRAL CONTROL OF LINEAR SYSTEMS
Authors: Sira‐Ramírez Hebertt
Published: September 2010

In this article, we attempt a reapproachment between sliding mode control of linear systems and classical control through the possibilities of evading state measurements and circumventing the use of asymptotic state observers in the sliding surface synthesis. This is shown to be possible thanks to the use of integral state reconstructors combined with iterated integral output error compensation. The proposed scheme is also robust with respect to unmatched perturbation inputs. A connection between sliding modes and classical analog Δ‐modulators, and their natural generalization, is also brought to attention as a tool for the realization of integral reconstructor based sliding mode control schemes.
AN ASYMPTOTIC SECOND‐ORDER SMOOTH SLIDING MODE CONTROL
Authors: Shtessel Yuri B. , Shkolnikov Ilya A. , Brown Mark D.J.
Published: September 2010

Presented is a method of smooth sliding mode control design to provide for an asymptotic second‐order sliding mode on the selected sliding surface. The control law is a nonlinear dynamic feedback that in absence of unknown disturbances provides for an asymptotic second‐order sliding mode. Application of the second‐order disturbance observer in a combination with the proposed continuous control law practically gives the second‐order sliding accuracy in presence of unknown disturbances and discrete‐time control update. The piecewise constant control feedback is “smooth” in the sense that its derivative numerically taken at sampling rate does not contain high frequency components. A numerical example is presented.
IMPLICIT TRIANGULAR OBSERVER FORM DEDICATED TO A SLIDING MODE OBSERVER FOR SYSTEMS WITH UNKNOWN INPUTS
Authors: Boukhobza T. , Djemai M. , Barbot J.P.
Published: September 2010

It has been presented in previous works that every uniformly observable single‐output system can be put on a triangular observation form. For this structure a special kind of sliding mode observer has been designed by authors, which ensures a finite‐time state reconstruction using a step by step observation algorithm. In this paper, we show that the multi‐output case is more delicate to study especially when the system has some unknown inputs. Thus, in order to generalizes the triangular observer form, from single to multi‐output case, we define an Implicit Triangular Observer (ITO) form. For such a form, two results are given. Firstly, we design a finite time converging observer for all values of the unknown inputs. Secondly, we give the necessary and sufficient condition, including a matching condition, for the existence of a coordinate change to put the system into this form. It is also shown that this class of systems is a subset of the uniform observable class of systems.