Minimum entropy control of nonlinear ARMA systems over a communication network
In this paper, the entropy concept has been utilized to characterize the uncertainty of the tracking error for nonlinear ARMA stochastic systems over a communication network, where time delays in the communication channels are of random nature. A recursive optimization solution has been developed. In addition, an alternative algorithm is also proposed based on the probability density function of the tracking error, which is estimated by a neural network. Finally, a simulation example is given to illustrate the efficiency and feasibility of the proposed approach.

title: An Intelligent Mill Load Switching Control of the Pulverizing System for an Alumina Sintering Process
abstract: This paper proposes an intelligent switching control strategy for the pulverizing system for an alumina sintering process. The control strategy consists of a coordinating controller, a proportional-integral (PI) controller, a rule-based reasoning controller and a switching mechanism. The practical application to a pulverizing system in an alumina sintering process has shown that when the hot air temperature is low and varies frequently, this control strategy ensures that the mill load and the temperature of the mill outlet are both within their required ranges, and also controls the mill load at the level corresponding to the maximum mill output. Moreover, it has been observed that the proposed control strategy can avoid the fault operating condition and effectively reduce the unit energy consumption.

title: Advances in stochastic distribution control
abstract: Stochastic distribution control systems aims at the controller design so as to realize a shape control of the distributions of certain random variables in the process. Once the probability density functions (PDFs) of these variables are used to describe their distributions, the control task is to obtain control signals so that the output PFDs of the system are made to follow their target PDFs. In this paper, a survey of the recent developments on the research of stochastic distribution control systems will be made.

title: Robust minimum entropy tracking control with guaranteed stability for nonlinear stochastic systems under modeling errors
abstract: In this paper, robust minimum entropy tracking control problem is considered for nonlinear stochastic systems. The controlled systems are described by nonlinear non-Gaussian difference equations with the un-modeled uncertainty and modeling error, as well as time delays. Entropy is adopted to characterize the uncertainty of the tracking error. The nonlinear multi-step-ahead predictive cost function is used and the relationship between the probability density functions of the input and the tracking error via the uncertain mapping is established. With these formulations, the cost function can be bounded as a nonlinear functional of the control input and the known bounds of the errors. Explicit design algorithms are presented for the robust suboptimal controller and further for the stabilization controllers. The Renyi's entropy has also been used to simplify the cost function. Simulations are given to demonstrate the effectiveness of the proposed control algorithm.

title: Novel Parameter Identification by Using a High-Gain Observer With Application to a Gas Turbine Engine
abstract: In this study, a novel identification technique, that is high-gain observer-based identification approach, is proposed for systems with bounded process and measurement noises. For system parameters with abnormal changes, an adaptive change detection and parameter identification algorithm is next presented. The presented technique and algorithm are finally applied to the parameter identification of the gas turbine engine by using the recorded input data from the engine test-bed. The identified parameters and the response curves are desirable. The simulations have proved the effectiveness of the proposed procedure compared with the previous identification approach.

title: Descriptor observer approaches for multivariable systems with measurement noises and application in fault detection and diagnosis
abstract: In this paper, new descriptor observer design approaches are presented for multivariable systems with measurement noises. If the system matrix is stable, the proposed modified proportional and derivative observer technique allows us not only to decouple the measurement noise in any forms completely, but also obtain accurate estimations of both system states and measurement noises. If the system is detectable and the noise is bounded, it has been shown that two design parameters can provide more degrees of freedom. In this context, the derivative gain parameter is chosen to reduce the amplification of the noise, and the proportional gain is then selected to guarantee the stability of the error dynamics. For systems with both measurement output noises and input disturbances, a modified proportional, derivative and integral observer is constructed to asymptotically estimate states, input disturbances, and output noises at the same time. The applications of the proposed observers for systems with actuator and sensor faults are also discussed. Numerical examples are given to illustrate the design procedures, and the simulation results show the satisfactory tracking performance.

title: Partition of a bipartite graph into cycles
abstract: (1984) conjectured that if G is a graph on n 1 + n 2 +⋯+ n k vertices with n i ⩾3 for 1⩽ i ⩽ k a minimum degree δ ( G )⩾⌈ n 1 /2⌉+⌈ n 2 /2⌉+⋯+⌈ n k /2⌉, then G contains k vertex-disjoint cycles of lengths n 1 , n 2 ,⋯, n k respectively. He proved this conjecture for k =2. In this note we consider a similar problem in bipartite graphs and prove: If G is a bipartite graph with partites V 1 and V 2 where | V 1 |=| V 2 |= n , n = n 1 + n 2 +⋯+ n k for n 1 ⩾ n 2 ⩾⋯⩾ n k ⩾2, k ⩾2 and δ ( G )⩾ n 1 + n 2 + ⋯+ n k −1 + n k /2, then G contains k vertex-disjoint cycles of lengths 2 n 1 ,2 n 2 ,…,2 n k , respectively. We demonstrate by producing examples that the above result is best possible when k =2.

title: Post-pass binary adaptation for software-based speculative precomputation
abstract: Recently, a number of thread-based prefetching techniques have been proposed. These techniques aim at improving the latency of single-threaded applications by leveraging multithreading resources to perform memory prefetching via speculative prefetch threads. Software-based speculative precomputation (SSP) is one such technique, proposed for multithreaded Itanium models. SSP does not require expensive hardware support-instead it relies on the compiler to adapt binaries to perform prefetching on otherwise idle hardware thread contexts at run time. This paper presents a post-pass compilation tool for generating SSP-enhanced binaries. The tool is able to: (1) analyze a single-threaded application to generate prefetch threads; (2) identify and embed trigger points in the original binary; and (3) produce a new binary that has the prefetch threads attached. The execution of the new binary spawns the speculative prefetch threads, which are executed concurrently with the main thread. Our results indicate that for a set of pointer-intensive benchmarks, the prefetching performed by the speculative threads achieves an average of 87% speedup on an in-order processor and 5% speedup on an out-of-order processor.

title: A Polygon Detection Algorithm for Robot Visual Servoing
abstract: The problem of detecting polygon structures in images arises in many applications, from building extraction to cryo-electron microscopy. In this paper, A polygon detection algorithm (PDA) based on line detection is proposed. First of all, we introduce a parallel thinning algorithm to eliminate useless feature points. Then the feature points are organized as disjoint feature contours. For each independent contour, we detect line segment candidates based on RANSAC algorithm. With these candidates, a polygon (triangle, rectangle or other polygons) is composed. Compared to the state-of-the-art shape detection algorithms, PDA is much faster and it can detect any polygons such as triangles, rectangles, etc. We introduce PDA to a 6DOFs robot visual servoing platform and the experimental results show that significant improvements in time efficiency and performance robustness of the proposed algorithm have been achieved.

title: Triangles in claw-free graphs
abstract: A graph is said to be claw-free if it does not contain an induced subgraph isomorphic to K 1,3 . Let k be a positive integer. Our main result is as follows: If G is a claw-free graph of order at least 3 k and d(x) + d ( y )⩾3 k + 1 for every pair of non-adjacent vertices x and y of G , then G contains k vertex-disjoint triangles unless either k is odd and G is one exceptional graph of order 3 k + 1, or k is 1 and G is the union of vertex-disjoint cycles of length at least 4.

title: A Fast and Robust Ellipse Detection Algorithm Based on Pseudo-random Sample Consensus
abstract: Ellipse is one of the most common features that appears in images. Over years in research, real-timing and robustness have been two very challenging problems aspects of ellipse detection. Aiming to tackle them both, we propose an ellipse detection algorithm based on pseudo-random sample consensus (PRANSAC). In PRANSAC we improve a contour-based ellipse detection algorithm (CBED), which was presented in our previous work. In addition, the parallel thinning algorithm is employed to eliminate useless feature points, which increases the time efficiency of our detection algorithm. In order to further speed up, a 3-point ellipse fitting method is introduced. In terms of robustness, a "robust candidate sequence" is proposed to improve the robustness performance of our detection algorithm. Compared with the state-of-the-art ellipse detection algorithms, experimental results based on real application images show that significant improvements in time efficiency and performance robustness of the proposed algorithm have been achieved.