bluuebunny/crossref_metadata_2025_split huggingface dataset:
A cautious approach to robust adaptive regulation
Authors: Giri F. , M'Saad M. , Dlon J. M. , Dugard L. 
Published: July 2007

AbstractThe problem of estimated model controllability in robust pole placement adaptive regulation is investigated. The adaptive control law is modified in the sense that some measure of the parameter estimates error is incorporated into the design, leading to ‘cautious’ control actions. Two pole placement adaptive control algorithms are presented and shown to be BIBO stable in spite of bounded disturbances, time‐varying parameters and unmodelled dynamics.
Adaptive control of time‐varying plants: Simple examples
Authors: Tsakalis K. S. , Ioannou P. A. 
Published: July 2007

AbstractThe design and properties of an adaptive model reference scheme and an adaptive pole placement control scheme for linear time‐varying plants are demonstrated via two simple examples. The two new schemes combine new control laws that are appropriate for time‐varying plants with estimators that can utilize any available a prior; information on the structure of the parameter variations and are applicable to plants which are not necessarily slowly time‐varying. As illustrated by simulations, the new adaptive controllers exhibit good performance even in cases of fast plant parameter variations.
High gain observers applied to problems in the stabilization of uncertain linear systems, disturbance attenuation and N∞ optimization
Authors: Petersen Ian R. , Hollot Christopher V. 
Published: July 2007

AbstractIn recent years, a number of approaches have been developed for solving the following problem in linear systems theory: design a state feedback control so that the norm of a specified transfer function is less than a given bound over all frequencies. This paper deals with the case in which not all systems states can be measured. It shows that if a certain minimum phase condition is satisfied, then the transfer function bound achievable using state feedback can be asymptotically recovered using a high gain observer. These results have application to the problems of disturbance attenuation, H∞ optimization and the stabilization of uncertain linear systems.
Adaptive control via parameter set estimation
Authors: Kosut Robert L. 
Published: July 2007

AbstractAn adaptive control system is examined where the traditional parameter estimator is replaced by a parameter set estimator which provides a measure of uncertainty of the estimated parameters. it is shown how to construct a parameter set estimator with the property that the true system is always in the model set, and furthermore, how to design the estimation experiment so that the set of uncertainty is as small as possible given some a priori information.
A new approach to model reference adaptive control
Authors: Duarte Manuel A. , Narendra Kumpati S. 
Published: July 2007

AbstractA new approach to model reference adaptive control, based on a combination of direct and indirect control methods, is introduced in this paper. The controller structure is identical to that used in the direct method, but the algorithm used to update the controller parameters depends both on the output error as in direct control and on the plant parameter estimates as in indirect control. The global stability of the overall system is assured by the existence of a Lyapunov function. In the ideal case discussed here, the combined approach results in improved transient response with smaller amplitude of the control input as compared to the constituent methods.
A showcase of adaptive controller designs
Authors: Masten Michael K. , Cohen Herbert E. 
Published: July 2007

AbstractThe adaptive control literature contains hundreds of technical papers on many different approaches to the subject. However, engineers who are not specialists in adaptive theory often have difficulty selecting which approach to use in any given problem. This series of papers addresses this situation by defining a set of standard problems which are then solved by several distinct approaches to adaptive control. This introductory paper defines the problems and guidelines which have been used in this process.
Example applications of the linear adaptive design technique
Authors: Johnson C. D. 
Published: July 2007

AbstractAdaptive controllers can be designed by a variety of different methodologies that have been developed over the past 35 years. However, all these methodologies have one thing in common; they lead to adaptive controllers that are intriniscatly non‐linear in structure. Recently a new, unorthodox approach to the adaptive control problem has been developed. This new methodology leads to a new class of adaptive controllers that, in many cases, areentirely linearand haveall‐constant parameters(constant gains).In the present paper this new approach to adaptive control is used to design‘linear adaptive controllers’for two example applications, and the closed‐loop adaptive performance obtained in each case is illustrated by digital simulation tests. These results demonstrate that the new linear adaptive controllers are able to produce a surprisingly high‐degree of adaptation over significant ranges of plant parameter variations and disturbances.
Application of robust adaptive control using combined direct and indirect methods
Authors: Narendra Kumpati S. , Duarte Manuel A. 
Published: July 2007

AbstractA new approach, combining direct and indirect control methods, recently proposed by the authors is used to adaptively control plants with unknown parameters. The plant parameters are known to lie in a specified compact set in parameter space and the output of the plant has to follow a desired output in the presence of a piecewise‐constant input disturbance. Simulation results indicate that the combined method performs better than either the direct or the indirect method.
Performance analysis of parameter estimation algorithms based on high‐order moments
Authors: Porat Boaz , Friedlander Benjamin 
Published: July 2007

AbstractRecently, there has been a considerable interest in parametric estimation of non‐Gaussian processes, based on high‐order moments. Several researchers have proposed algorithms for estimating the parameters of AR, MA and ARMA processes, based on the third‐order and fourth‐order cumulants. These algorithms are capable of handling non‐minimum phase processes, and some of them provide a good trade‐off between computational complexity and statistical efficiency.This paper presents some results about the performance of algorithms based on high‐order moments. A general lower bound is derived for the variance of estimates based on high‐order sample moments. This bound, which is shown to be asymptotically tight, is neither the Cramer‐Rao bound nor a trivial extension thereof. The performance of weighted least squares estimates of the type recently proposed in the literature is investigated. An expression for the variance of such estimates is derived and the existence of an optimal weight matrix is proven. The general formulae are specialized to MA and ARMA processes and used to analyse the performance of some algorithms in detail. The analytic results are verified by Monte Carlo simulations for some specific test cases.A by‐product of this paper is the derivation of asymptotic formulae for the variances and covariances of the sample third‐order moments of a certain class of processes.
Adaptive beamforming
Authors: Steinhardt Allan O. , Van Veen Barry D. 
Published: July 2007

AbstractAn adaptive beamformer is a system devised to isolate a desired signal from interfering signals which are spatially disparate but which occupy the same spectral band. Traditionally these systems have been employed primarily in sonar and radar. However, because of the rise in traffic throughout the electromagnetic spectrum, coupled with the availability of high‐speed real‐time computational resources, adaptive beamforming is now increasingly of interest in wireless communications as well. In this overview we present the principles underlying these devices with an emphasis on estimation and system theoretic issues.
Adaptive control of a coupled tank apparatus
Authors: Fernandes José M. , De Souza Carlos E. , Goodwin Graham C. 
Published: July 2007

AbstractThis paper describes an experimental investigation of adaptive control applied to a coupled tank apparatus. The study is intended to explore several practical considerations which arise in the application of adaptive control to realistic processes. In the experiments, the apparatus was configured so as to have several difficulties found in practical systems, including unmodelled time delay, unmodelled high‐frequency lag and unmodelled non‐linearities. These features are studied both theoretically and experimentally. The adaptive controller is shown to perform satisfactorily in the presence of these practical difficulties. Also a comparison with other strategies for control system design is given.
Boundedness conjecture for an output error adaptive algorithm
Authors: Schoenwald D. A. , Kokotovic P. V. 
Published: July 2007

AbstractThis paper compares conditions for instability with conditions for global asymptotic stability of a discretetime output error adaptive estimation algorithm. This comparison leads to a boundedness conjecture which states that all signals within this adaptive system as well as the output error and parameter estimates remain globally bounded for all time despite any unstable behaviour. The investigation into the stability properties of this algorithm begins with a global stability criterion applied to a transfer function which is not strictly positive real. This criterion states that for large enough adaptation gain and/or input signal magnitude the system will be asymptotically stable. Then a local result is applied which states that for small enough adaptation gain and/or input signal magnitude the same system is unstable. The result is a bifurcation due to the decrease of the adaptation gain and/or input signal magnitude as the system goes from asymptotic stability to instability which remains bounded. The results suggested by the computer simulations are verified by an exact analysis of a linearized periodic version of the adaptive system.
An advanced showcase of adaptive controller designs
Authors: Masten Michael K. , Cohen Herbert E. 
Published: July 2007

AbstractThe adaptive control literature contains numerous theories for deriving adaptive controllers. However, practising engineers who are not specialists in adaptive theory often have difficulty selecting which approach to use in a given application. The papers in this special issue address this situation by defining a set of standard problems which are then solved by several distinct adaptive control approaches. This introductory paper provides the motivation for the issue (why it is important, who is the target audience, what is the goal of the process), defines the standard problems to be considered and explains the rationale for their formulation, and describes the guidelines which were established for the participants. In addition, this paper defines the ‘ideal’ closed‐loop responses for each standard problem, from which the results of the subsequent papers can be judged.
Robust adaptive control using a combined approach
Authors: Narendra Kumpati S. , Boškovič Jovan D. 
Published: July 2007

AbstractDirect control, indirect control and variable structure methods are combined with high‐gain feedback in this paper for the robust adaptive control of first‐, second‐ and third‐order plants with increasing levels of uncertainty. The latter include external disturbance, unmodelled dynamics, time delay and sensor noise. A judicious combination of the methods is found to result in satisfactory response in most cases.
On the implementation of predictive adaptive control by adaptive predictors
Authors: Chisci L. , Zappa G. , Mosca E. 
Published: July 2007

AbstractA convenient parametrization of LQ predictive control laws in terms of predictions only is stressed. This has two desirable consequences in predictive adaptive control. First, it makes the control computation independent of the identified plant representation (be it transversal, lattice or any other). Secondly, it allows modular VLSI implementation by means of standard RLS adaptive predictor modules. In this connection it is shown that control strategies based on the separate identification of multistep‐ahead predictors are more favourable than strategies based on computing multistep‐ahead predictor parameters by analytically extrapolating the identified one‐step‐ahead predictor.
Frequency‐dependent bursting in adaptive echo cancellation and its prevention using double‐talk detectors
Authors: Ding Z. , Johnson C. R. , Sethares W. A. 
Published: July 2007

AbstractEcho cancellation in telephone communications can often be accomplished by using adaptive network echo cancellers. However, under certain circumstances, these generally effective echo cancellers can cause an undesirable bursting phenomenon. In this paper the essential driving force behind bursting is attributed to the correlation between the signal the near‐end is to transmit and the signal the near‐end receives from the far‐end. This correlation and the subsequent potential for temporary destabilization arise as a result of the feedback loop structure of the four‐wire telephone circuit. A new test signal which approximately measures this correlation is proposed for use in the double‐talk detector scheme that is commonly used to halt adaptation before a mishap such as bursting occurs.
Improved method for designing linear distributed feedback systems
Authors: Kelemen M. , Kannai Y. , Horowitz I. 
Published: July 2007

AbstractA new BIBO‐type stability criterion is proven for linear systems described by partial differential operators with constant coefficients. The class of inputs contains functions which are step‐like in time and which decay appropriately in the space variables. On the basis of this result, a frequency domain synthesis procedure was developed leading to an ‘economic’ feedback loop (i.e. significant noise reduction achieved). The procedure is illustrated by means of an example.
A bayes‐closed approximation of recursive non‐linear estimation
Authors: Kulhavý Rudolf 
Published: July 2007

AbstractTo implement the Bayes estimation in a recursive manner means to cope with the need for storing a too large data statistic. We prove here that under certain assumptions, it is possible to construct a reduced description of posterior densities (a reduced statistic) which is closed with respect to the Bayes rule. Thus the optimal Bayes inference can be realized in terms of transitions between equivalence classes of densities matching the respective values of the description. Next we attempt to design a specific approximation of the recursive Bayes estimation by projecting the true posterior density orthogonally, along the appropriate equivalence class, onto a prespecified approximation family. We find that to ensure orthogonal projection globally, the approximation family must be of a mixture type and the description vector determined by the values of the Kullback‐Leibler distance between the ‘base’ densities of the mixture approximation family and the true density. A simple simulation example compares the Bayes‐closed approximation with some competitive methods.
Indirect adaptive state feedback control of linearly parametrized non‐linear systems
Authors: Campion G. , Bastin G. 
Published: July 2007

AbstractTwo indirect adaptive linearizing controllers are proposed, in continuous time, for the class of non‐linear systems which are linearly parametrized and which can be linearized by state feedback through a parametrized diffeomorphism. In each case the stability of the closed loop is analysed in detail. It is also shown how these control laws can be extended to related situations, i.e. input‐output feedback linearization and non‐linear parametrizations.
Robust stability of multi‐loop continuous time self‐tuning controllers
Authors: Gawthrop P. J. 
Published: July 2007

AbstractThe results of an earlier paper concerning global robustness of single‐loop self‐tuning controllers are extended to include multiple self‐tuning controllers operating in a multiple‐interacting‐loop environment. The robust stability is shown to depend on the singular value loci of a certain transfer function matrix. The need for control weighting to ensure global robust stability is emphasized.
On the persistency of excitation for systems having purely deterministic disturbances using the RLS algorithm
Authors: Cristi Roberto , Feuer Arie 
Published: July 2007

AbstractA system with purely deterministic disturbances can be represented by a non‐minimal model. In this paper we establish conditions on the input to the system so that when the RLS algorithm is applied to identify its parameters, convergence is guaranteed. It should be pointed out that no boundedness conditions on this input are required.
On the stability of decentralized discrete adaptive control systems
Authors: Wiemer P. , Unbehauen H. 
Published: July 2007

AbstractIn this paper some results of direct decentralized adaptive control based on input/output methods are presented. The plant is assumed to have several local adaptive controllers, each of which can observe only local system outputs and control only local inputs. Conditions for the stability of the decentralized control scheme are derived using an extended I/O sector stability theorem of Safonov.20 The associated error model of the adaptive scheme can be represented in the form of an equivalent feedback configuration comprising a non‐linear time‐varying feedforward block describing the adaptation law and a linear time‐invariant feedback block which depends on the interactions of the different control loops. Stability is obtained if the blocks verify certain sector conditions. It will be demonstrated that conventional adaptation algorithms have to be modified. The proposed RLS parameter adaptation law differs from standard algorithms by the introduction of signal normalization, interlaced parameter adaptation and a variable forgetting factor.The allowable class of interactions is restricted by the sector condition for the linear feedback block. It will be shown that less conservative conditions can be found when a parallel filter, the so‐called correction network, is introduced. Such filters make direct adaptive control possible even for non‐minimum phase systems. In addition, the correction network makes the adaptive controller robust to uncertainties in the structure of the plant.
An H∞ approach to learning control systems
Authors: Padieu Francois , Su Renjeng 
Published: July 2007

AbstractIn this paper we study a control methodology now often referred to as learning control in the recent control literature. Our primary aim is to establish a mathematical framework which will allow systematic and continuing development of learning control theory. The framework is based on the functional spaces which have been heavily used in H∞ control theory. It is then applied to the study of the convergence problems associated with learning control. Three theorems on general convergence conditions are presented.
A unified perspective on robot control: The energy lyapunov function approach
Authors: Wen John T. 
Published: July 2007

AbstractA unified framework for the stability analysis of robot tracking control is presented. By using an energy‐motivated Lyapunov function candidate, the closed‐loop stability is shown for a large family of control laws sharing a common structure of proportional and derivative feedback and a model‐based feedforward. The feedforward can be zero, partial or complete linearized dynamics, partial or complete non‐linear dynamics, or linearized or non‐linear dynamics with parameter adaptation. As a result, the dichotomous approaches to the robot control problem based on the open‐loop linearization and non‐linear Lyapunov analysis are both included in this treatment. Furthermore, quantitative estimates of the trade‐offs between different schemes in terms of the tracking performance, steady state error, domain of convergence, realtime computation load and required a priori model information are derived.
Learning control theory for robotic motion
Authors: Arimoto Suguru 
Published: July 2007

AbstractA new concept of learning control for the improvement of robot motions is proposed, which can be referred to a mathematical modelling of learning and generation of motor programmes in the central nervous system. It differs from conventional classical and modern control techniques. It stands for the repeatability of operating a given robotic system and the possibility of improving the command input on the basis of actual measurement data acquired at the previous operation. Hence adequate conditions on the repeatability and invariance of the system dynamics are assumed, but no precise description of the dynamics is required for construction of the learning algorithms. Two types of iterative learning algorithm are proposed: one uses a PD‐type (proportional and differential) update of input commands and the other a PI‐type (proportional and integral) update where velocity signals are regarded as outputs. It is shown that in both types a better performance is realized at every attempt of operation, provided a desired motion is givena prioriand the actual motion (velocity signals) can be measured at every operation. Further, the robustness of such learning control algorithms with respect to the existence of perturbed errors of initialization of the robot, disturbances and measurement noise during operation is analysed in detail. It is shown that in PD‐type learning laws such errors are neither amplified nor aggregated in later consecutive trials of operation. In the case of PI‐type learning laws it is shown that such a robustness property is assured if a forgetting factor is adequately introduced into the repetitive learning law.
Controllers which guarantee robustness with respect to unmodelled flexibilities for a class of uncertain mechanical systems
Authors: Corless Martin 
Published: July 2007

AbstractWe consider a class of uncertain mechanical systems containing flexible elements and subject to memoryless output‐feedback controllers. The damping and stiffness properties of some of the flexible elements are parametrized linearly in μ−1 and μ−2 respectively, where μ > 0 and these components become more rigid as μ approaches zero. We propose a class of ‘stabilizing’ controllers for a system model in which the above components are rigid. Subject to a ‘linear growth condition’, the controllers also stabilize the model in which the components are flexible provided μ > 0 is sufficiently small.