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Non-Fragile control for Trajectory Tracking of Nonholonomic Mobile Robots

Non-Fragile Control for Trajectory Tracking of Nonholonomic ...

引用

American control Conference

作者： Na Ni Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424474264

This paper is devoted to the non-fragile controller design for the trajectory tracking of nonholonomic mobile robots. Using non-linear state feedback and proper coordinate transformation, the model of nonholonomic mobile robots is exactly linearized. Based on which, the non-fragile controller is designed by employing the linear matrix inequality (LMI) approach. Simulation examples are included to illustrate the effectiveness of the proposed controller.

关键词： Trajectory Mobile robots control systems Tracking Robot kinematics Orbital robotics State feedback Error correction Sliding mode control Laboratories

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A New Resampling Algorithm for Generic Particle Filters

A New Resampling Algorithm for Generic Particle Filters

引用

American control Conference

作者： X. Fu Y. Jia J. Du F. Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424474264

This paper is devoted to the resampling problem of particle filters. We firstly demonstrate the performance of classical Resampling algorithm (also called as systematic resampling algorithm) using a novel metaphor, through which the existing defects of Resampling algorithm is vividly reflected simultaneously. In order to avoid these defects, the exquisite resampling (ER) algorithm is induced which involves some exquisite actions such as comparing the weights by stages and generating the new particles based on quasi-Monte Carlo method. Simulations indicate that the proposed ER algorithm can reduce the sample impoverishment effectively and improve the accuracy of estimation evidently, which confirm that ER algorithm is a competitive alternative to Resampling algorithm.

关键词： resampling algorithm Particle filters

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L_(2)-L_(infinity) Filter Design for Neutral Stochastic Time-Delay systems

L_(2)-L_(infinity) Filter Design for Neutral Stochastic Time...

引用

2010 49th IEEE Conference on decision and control

作者： Lin Li Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424477456

This paper is concerned with the problem of L_(2)-L_(infinity) filtering for a class of neutral stochastic systems with both discrete and distributed time-varying delays. The purpose is focusd on the design of a full order filter such that the resulting filtering error system is stochastically asymptotically stable in the mean square with a prescribed L_(2)-L_(infinity) disturbance attenuation level satisfied. By employing Lyapunov functional and stochastic stability theory, a delay-dependent sufficient condition for the existence of such a filter is obtained in terms of linear matrix inequalities (LMIs). The desired filter can be obtained by solving two LMIs.

关键词： Stochastic delay systems Filters mean square filter design stochastic systems error system stability theory Delay systems Filtration

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Analysis of Two Robust Learning control Schemes in the Presence of Random Iteration-Varying Noise

Analysis of Two Robust Learning Control Schemes in the Prese...

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American control Conference

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424474264

This paper deals with the design problem of robust iterative learning control (ILC), in the presence of noise that is varying randomly from iteration to iteration. Two ILC schemes are considered: one adopts the previous iteration tracking error (PITE) and the other adopts the current iteration tracking error (CITE), in the updating law. For both schemes, the convergence results are obtained by using a frequency-domain approach, and a comparison between them is presented from the viewpoints of the convergence condition, robustness against plant uncertainty, and delay compensation. It shows that sufficient conditions can be derived to bound the tracking error and make its expectation monotonically convergent in the sense of L_(2)-norm, which work effectively with robustness for all admissible plant uncertainties. Furthermore, the sufficient conditions for both schemes can also be formulated in terms of two complementary functions, which do not depend on the delay time as well as the plant uncertainty and, thus, make them convenient to be checked and solved using the frequency-domain tools. Numerical simulations are included to illustrate the effectiveness of the two proposed ILC schemes.

关键词： Iterative learning control monotonic convergence previous iteration tracking error current iteration tracking error random iteration-varying noise delay compensation delay compensation monotone convergence iterative methods Iterative learning control follow error Scheme design problems Delay time Sufficient conditions learning control

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Model Matching control for MIMO systems with Multiple Time Delays and Its Applications in Adaptive Scheme

Model Matching Control for MIMO Systems with Multiple Time D...

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American control Conference

作者： Haixia Su Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424474264

This paper considers the model matching problem of multiple-input multiple-output (MIMO) systems with multiple time delays. The reference model is chosen to be the diagonal delay transfer function matrix. A controller is designed for nominal systems. Furthermore, an adaptive control scheme is proposed for uncertain systems with parameter variation. The resulting scheme can guarantee the global stability of the closed-loop systems and the convergence of the tracking errors. A simulation example is included to illustrate the proposed scheme.

关键词： control system synthesis MIMO Delay effects Programmable control Adaptive control Transfer functions control systems Uncertain systems Stability Convergence

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Kalman filtering with multiple nonlinear-linear mixing state constraints

Kalman filtering with multiple nonlinear-linear mixing state...

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IEEE Conference on decision and control

作者： X. Fu Y. Jia J. Du F. Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing China Beihang University Beijing CN Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper is devoted to the problem of state estimation for a class of dynamic system with multiple nonlinear-linear (NL) mixing state constraints. A computational algorithm was developed by C. Yang and E. Blasch to incorporate a positive definite quadratic form equality constraint into the Kalman filtering for the ground vehicle tracking. However, when the target tracked in multidimensional space, a single positive definite quadratic form constraint is not enough due to the involvement of other surface such as hyperboloid, paraboloid, or even plane. A analytic method of incorporating multiple nonlinear-linear mixing state constraints into the Kalman filter is presented here, and a sufficient condition is obtained that guarantee the existence of solution. The constraints may be time varying. At each time step the unconstrained Kalman filter solution is projected onto the state constraints surface. This significantly improves the prediction accuracy of the filter. The use of this algorithm is demonstrated on a nonlinear-linear mixing spacecraft positioning problem.

关键词： Kalman filters Symmetric matrices State estimation Optimization Covariance matrix Noise

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A Fast Automatic Construction Algorithm for Kernel Fisher Discriminant Classifiers

A Fast Automatic Construction Algorithm for Kernel Fisher Di...

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2010 49th IEEE Conference on decision and control

作者： Jing Deng Kang Li George W. Irwin Robert F Harrison School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Belfast BT9 5AH UK Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK

ISBN: (纸本)9781424477456

Nonlinear Fisher Discriminant Analysis for binomial problems can be converted into a Linear-In-The-Parameters classifier model by introducing a least-squares cost function. However, the complexity of the classifier scales with the number of training samples, which makes it difficult to use on large data sets. A popular solution is to adopt a sub-model selection approach, such as Orthogonal Least Squares (OLS) or the Fast Recursive Algorithm (FRA), to produce a compact classifier with accurate parameters. The problem is that these methods need additional subjective choice of selection termination criterion, and inappropriate choice of this criterion may lead to an over-fitting classifier. Further, training data with large noise may even deteriorate the performance. This paper proposes a fast automatic forward algorithm for constructing a parsimonious descriptor of the nonlinear discriminant function, thus both the subjective choice of the termination criterion and the over-fitting problem due to noisy data can be avoided. This is achieved by an effective integration of the Bayesian regularisation technique, the Leave-One-Out (LOO) cross-validation criterion and the FRA algorithm. Experimental results are included to confirm the efficacy and superiority of the proposed algorithm on both artificial and real world data sets.

关键词： Constructive Algorithm termination criteria Classifiers Martes pennanti noisy data Fasting discriminant analysis

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Monte-Carlo tree search for a reentrant scheduling problem

Monte-Carlo tree search for a reentrant scheduling problem

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40th International Conference on computers and Industrial engineering, CIE40 2010

作者： Matsumoto, Shimpei Hirosue, Noriaki Itonaga, Kyohei Ueno, Nobuyuki Ishii, Hiroaki Faculty of Applied Information Science Hiroshima Institute of Technology 2-1-1 Miyake Saeki-ku Hiroshima 731-5193 Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Kawazu 680-4 Iizuka 820-8502 Japan Division of Electrical Electronic and Information Engineering Advanced Courses of Oita National College of Technology 1666 Oaza-Maki Oita 870-0152 Japan Department of Management and Information Systems Prefectural University of Hiroshima 1-1-71 Ujina-higashi Minami-ku Hiroshima 734-8558 Japan Department of Mathematical Sciences School of Science and Technology Kwansei Gakuin University 2-1 Gakuen Sanda 669-1337 Japan

ISBN: (纸本)9781424472956

This paper reports application results of Monte-Carlo Tree Search (MCTS) for a practical problem. In this paper, a reentrant scheduling problem is considered as a practical problem which has been addressed by our previous works. MCTS introduced by Coulom is a best-first search where the pseudorandom simulations guide the solution of problem. Recent improvements on MCTS have produced strong computer Go program, which has a large search space, and the success is a hot topic for selecting the best move. So far, most of reports about MCTS have been on two-player game, and MCTS has been applied rarely in one-player perfect-information games. MCTS does not need an admissible heuristic, so the application of MCTS for one-player games might be an interesting alternative. Additionally, one-player games like puzzles are determinately operated only by one player's decision, so sequences of changes in state are describable as a network diagram of interdependence of operations. Therefore if MCTS for one-player games is considered as a meta-heuristic algorithm, we can use this algorithm for not only many practical problems, but also combinatorial optimization problems. Especially as MCTS does not fully depend on evaluation function, so the solutions based on MCTS remain effective if objective function of problem is modified. This paper firstly investigated on the application of Single Player MCTS (SP-MCTS) introduced by Schadd et al. Next this paper showed the effectiveness of new simulation strategies on SP-MCTS by numerical experiments. Based on the results, this paper discussed the application potentiality of SP-MCTS for a practical reentrant scheduling problem.

关键词： Scheduling

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On the Fractional-Order Distributed Parameter Low-Pass Filter

On the Fractional-Order Distributed Parameter Low-Pass Filte...

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2010 49th IEEE Conference on decision and control

作者： Yan Li Hu Sheng YangQuan Chen School of Control Science and Engineering Shandong University Jinan 250061 China Department of Electronic Engineering Dalian University of Technology Dalian 116024 China Center for Self-Organizing and Intelligent Systems (CSOIS) Department of Electrical and Computer Engineering Utah State University 4120 Old Main Hill Logan UT 84322 USA

ISBN: (纸本)9781424477456

In this paper, we derive the analytical impulse response of a fractional-order distributed parameter low-pass filter of the form integral from x=a to x=b of 1/Ts~(alpha)+1 dT, where 0 <= a <= b and alpha E (0,1). The asymptotic properties of the impulse responses are obtained. Moreover, based on the derived analytical impulse response, we present a technique to perform the discretization of the above fractional-order filter. Finally, a number of illustrated figures are presented to validate the concepts.

关键词： Fractional-order filter Distributed parameter Complex path integral Discretization method

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Monte-Carlo Tree Search for a reentrant scheduling problem

Monte-Carlo Tree Search for a reentrant scheduling problem

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International Conference on computers & Industrial engineering (CIE)

作者： Shimpei Matsumoto Noriaki Hirosue Kyohei Itonaga Nobuyuki Ueno Hiroaki Ishii Faculty of Applied Information Science Hiroshima Institute of Technology Hiroshima Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Division of Electrical Electronic and Information Engineering Oita National College of Technology Oita Japan Department ofmanagement and Information Systems Prefuctural University of Hiroshima Hiroshima Japan Department of Mathematical Sciences School of Science and Technology Kwansei Gakuin University Japan

关键词： Proposals

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