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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...

引用

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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Observer-Based L_(2)-L_(infinity) Control for a Class of Stochastic systems with Time-Varying Delay

Observer-Based L_(2)-L_(infinity) Control for a Class of Sto...

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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 devoted to the problem of L_(2)-L_(infinity) control for a class of stochastic time-delay systems via observer-based feedback control. The considered observer contains no time-delay. The purpose is to design an observer-based feedback stabilizing controller such that the augmented closed-loop system is stochastically asymptotically stable with a prescribed L_(2)-L_(infinity) performance satisfied. Based on the stochastic stability theory, a delay-dependent sufficient condition is derived in terms of linear matrix inequalities (LMIs). The observer and controller design method is proposed, while the corresponding explicit expression for the observer and controller gain matrices is also given. Finally, numerical examples and simulation results are included to illustrate the effectiveness of the proposed results.

关键词： stochastic systems system clock time varying stability theory Stochastic delay systems controller gain Closed loop systems

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Robust L_(2) - L_(infinity) Consensus Control of the Second-order Multi-agent systems with Time-delay

Robust L_(2) - L_(infinity) Consensus Control of the Second-...

引用

IEEE Conference on Decision and Control

作者： Yan Cui Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University 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)9781612848006

Robust L_(2) - L_(infinity) consensus control is studied for the second-order multi-agent systems with external disturbances and parameter uncertainties. By defining an appropriate controlled output, the consensus problem of the systems is transformed into a normal L_(2) - L_(infinity) control problem, and distributed state feedback protocols with time-delay are proposed. Sufficient conditions are established for the convergence to consensus of the network under fixed or switching topology. Numerical simulations are provided to demonstrate the effectiveness of our theoretical results.

关键词： Topology Europe

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PHD filter for multi-target tracking by variational Bayesian approximation

PHD filter for multi-target tracking by variational Bayesian...

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IEEE Annual Conference on Decision and Control

作者： Wenling Li Yingmin Jia Junping Du Jun Zhang 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 Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781467357159

In this paper, we address the problem of multitarget tracking with unknown measurement noise variance parameters by the probability hypothesis density (PHD) filter. Based on the concept of conjugate prior distributions for noise statistics, the inverse-Gamma distributions are employed to describe the dynamics of the noise variance parameters and a novel implementation to the PHD recursion is developed by representing the predicted and the posterior intensities as mixtures of Gaussian-inverse-Gamma terms. As the target state and the noise variance parameters are coupled in the likelihood functions, the variational Bayesian approximation approach is applied so that the posterior is derived in the same form as the prior and the resulting algorithm is recursive. A numerical example is provided to illustrate the effectiveness of the proposed filter.

关键词： Nickel

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Gaussian mixture PHD filter for multiple maneuvering extended targets tracking

Gaussian mixture PHD filter for multiple maneuvering extende...

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IEEE Conference on Decision and Control

作者： Wenling 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)9781612848006

This paper addresses the problem of tracking multiple maneuvering extended targets in the framework of random finite set theory. An elliptical model is adopted for exploiting sensor measurements of target extent, and the target dynamics is described by a jump Markov linear system which combines the shape parameters into the kinematic state vector. As each extended target gives rise to unlabeled multiple measurements per time step, all the received measurements are partitioned into a number of subsets so that the measurements in each subset are expected to stem from the same source. In addition, the best-fitting Gaussian approximation approach is employed to circumvent the difficulty of multiple model mixing in the Gaussian mixture probability hypothesis density (GM-PHD) filter. A numerical example is provided to compare the performance of the proposed filter with that of the GM-PHD filter without measurement partition.

关键词： Maneuvering Filters shape parameter extended target Gauss Subset numerical example

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A New Resampling Algorithm for Generic Particle Filters

A New Resampling Algorithm for Generic Particle Filters

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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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Design of a Robot Cloud Center

Design of a Robot Cloud Center

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International Symposium on Autonomous Decentralized systems (ISADAS)

作者： Zhihui Du Weiqiang Yang Yinong Chen Xin Sun Xiaoying Wang Chen Xu Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China School of Software and Microelectronics Peking University Beijing China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA International School Beijing University of Posts and Telecommunications Beijing China

Service-oriented architecture and cloud computing have become the prevalent computing paradigm. In this paradigm, computing resources can be accessed like other utility services available in today's society. In the meantime, robotics applications are joining the trend. More and more robot applications are shifting from manufacture to non-manufacture and service industries. However, for the on-demand supply of the large-scale heterogeneous robots, It is still a problem have not yet been studied, including the fundamental management and efficiency issues in using of these resources. In this paper, we design a framework of "Robot Cloud Center" (RCC) following the general cloud computing paradigm to address the current limitations in capacity and versatility of robotic applications. In this framework, a robot can be provided as a service just like a public utility service so that everyone can access the powerful robotic services easily, efficiently, and cheaply. Based on a given scenario, a robot scheduling algorithm in RCC is proposed to take advantage of the heterogeneous robot resources to meet the end user's requirement with the minimum cost.

关键词： Service robots computer architecture Service oriented architecture Hardware Cloud computing Computational modeling

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Finite-time consensus control for multiple manipulators with unmodeled dynamics

Finite-time consensus control for multiple manipulators with...

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American Control Conference

作者： Bin Zhang Yingmin Jia Junping Du Jun Zhang 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 Electronic and Information Engineering Beihang University (BUAA) Beijing 100191 China

ISBN: (纸本)9781479901777

This paper is devoted to the finite-time control problem for multiple manipulators, where unmodeled dynamics is taken into consideration. An effective coordinated control strategy is introduced, under which distributed protocols with continuous feedbacks are proposed. By applying the homogeneous theory for stability analysis, it is proven that the multi-robot system can be globally finite-time stabilized through our protocols. Numerical simulations on four manipulators with two degrees of freedom are presented to validate the effectiveness of the control strategy.

关键词： unmodeled dynamics control strategy Manipulators two degrees of freedom multi-robot systems Stability analysis distributed protocol

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Non-Fragile Control for Trajectory Tracking of Nonholonomic Mobile Robots

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

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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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Column Formation Control of Multi-robot systems with Input Constraints

Column Formation Control of Multi-robot Systems with Input C...

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IEEE Conference on Decision and Control

作者： Xiaohan Chen 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)9781612848006

This paper is concerned with the column formation control of multi-robot systems that are subject to input constraints. A new leader-follower setup is proposed, under which the Lyapunov method can provide a simple controller in terms of two feedback parameters. It is shown that using an elliptic approximation to input constraints, the two feedback parameters can be obtained directly with a geometric analysis method. Moreover, a sufficient condition is presented for the leader robot to guarantee that the desired column formation can be achieved, with which a particular controller is designed by selecting two appropriate functions for the feedback parameters. Simulation results are included to verify the effectiveness of the proposed theoretical results.

关键词： Column formation control multi-robot systems leader-follower input constraints elliptic approximation

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