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检索条件"任意字段=3rd IFAC Conference on Intelligent Control and Automation Science, ICONS 2013"

共 157 条记录，以下是41-50 订阅

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Adaptive reactionless motion control for free-floating space manipulators with uncertain kinematics and dynamics

Adaptive reactionless motion control for free-floating space...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Xu, Shuanfeng Wang, Hanlei Zhang, Duzhou Yang, Baohua Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing 100190 China China Academy of Space Technology Beijing 100094 China

ISBN: (纸本)9783902823458

This paper investigates the adaptive version of reaction null-space (RNS) based control for free-floating space manipulators with uncertain kinematics and dynamics. The great challenge in deriving the adaptive RNS-based control scheme is that it is difficult to obtain a linear expression which is the basis of the adaptive control. The main contribution of this paper is that we skillfully obtain such a linear expression, based on which, an adaptive version of the RNS-based controller is developed at velocity level, taking into account both the kinematic and dynamic uncertainties. It is shown that the proposed control achieves both the base attitude regulation and continuous path tracking of the end-effector. The simulation results are presented to show the effectiveness of the proposed controller. Copyright © 2013 ifac.

关键词： controllers

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control of single-phase CHB grid-connected photovoltaic system under non-uniform irradiation conditions

Control of single-phase CHB grid-connected photovoltaic syst...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Ma, Chao Wu, Jing Li, Ning Li, Shaoyuan Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783902823458

This paper proposes a novel MPPT method, which will provide a correct tracking direction under the condition of non-abrupt atmospheric changes, especially non-irradiation conditions. We also present a model predictive control method based on a cost function, which help to derive the predictions for each possible switching state. The control scheme obtained is capable of controlling the dc-link current to a desired MPPT reference current, while injecting sinusoidal current to the grid with reduced total harmonic distortion. Finally, the simulation results illustrate the effectiveness of our proposed method. Copyright © 2013 ifac.

关键词： Model predictive control

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Adaptive dynamic programming for solving non-zero-sum differential games

Adaptive dynamic programming for solving non-zero-sum differ...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Li, Hongliang Liu, Derong Wang, Ding State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783902823458

In this paper, a novel adaptive dynamic programming algorithm based on policy iteration is developed to solve online multi-player non-zero-sum differential game for continuoustime nonlinear systems. This algorithm is mathematically equivalent to the quasi-Newton's iteration in a Banach space. The implementation using neural networks is given, where a critic neural network is used to learn its value function, and an action neural network sharing the same parameters with the corresponding critic neural network is used to learn its optimal control policy for each player. All the critic and action neural networks are updated online in real-time and continuously. A simulation example is presented to demonstrate the effectiveness of the developed scheme. Copyright © 2013 ifac.

关键词： Neural networks

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A linearization approach in quantum decoherence systems for compressive sensing

A linearization approach in quantum decoherence systems for ...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Wang, Yaoxiong Gao, Fang Tang, Xubing Shuang, Feng Institute of Intelligent Machines Chinese Academy of Sciences Hefei 230031 China School of Mathematics and Physics Anhui University of Technology Ma'anshan 243032 China Department of Automation University of Science and Technology of China Hefei 230026 China

ISBN: (纸本)9783902823458

Quantum decoherence leads to non-unitary evolution of quantum systems and introduces noncontrollable aspects. For composite systems, the number of decoherence parameters always scales exponentially with the system size. In this work, we adopt a so-called compressive sensing technique to logarithmically reduce original data required to recover system dynamic process and reconstruct decoherence parameters. With appropriate approximations, a key linear constraint is obtained to build connection between unknown decoherence parameters and input/output data. This linearization approach for compressive sensing will provide an efficient way for theoretical and experimental studies on decoherence quantum system. Copyright © 2013 ifac.

关键词： Compressed sensing

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Tangent barrier Lyapunov functions for the control of output-constrained nonlinear systems

Tangent barrier Lyapunov functions for the control of output...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Tang, Zhong-Liang Tee, Keng Peng He, Wei School of Computer and Science Engineering University of Electronic Science and Technology of China Chengdu 611731 China Institute for Infocomm Research ASTAR Singapore 138632 Singapore School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9783902823458

In this paper, we present a systematic control design for strict-feedback nonlinear systems with output constraints using tangent Barrier Lyapunov Functions (BLFs-Tan). Both symmetric and asymmetric BLF-Tan based backstepping control design methods are developed. It is proved that with the proposed approach and Lyapunov synthesis, the output constraints are not violated, all signals in the closed-loop systems are bounded, and asymptotical tracking is achieved. Through the simulation, we also perform a comparison study between BLF-Tan and the logarithmic BLF (BLF-Log) to illustrate the difference in control performance, and show that the performance of asymmetric BLF-Tan based controller depends on the position of initial tracking error with respect to the transformed constraint boundary. Copyright © 2013 ifac.

关键词： Lyapunov functions

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An incremental Chan-Vese model for fast medical image segmentation

An incremental Chan-Vese model for fast medical image segmen...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Hao, Jiasheng Chen, Hua School of Automation Engineering University of Electronic Science and Technology of China ChengDu 611731 China

ISBN: (纸本)9783902823458

Chan-Vese model is a powerful and exible method for many fields of computer vision such as image segmentation. However, segmentation with this method involves a lot of iterations on the whole image region, which leads to a low calculating efficiency, especially for medical image segmentation. In this paper, a new incremental Chan-Vese model for fast image segmentation is presented. We define two concepts: signed member function and signed area, and then establish a progressive iterative formula for Chan-Vese model to calculate the average value of a whole image region during every iteration. Based on this incremental model, some fast evolution algorithms such as the narrowband method can be adopted to improve the efficiency of segmentation. This model is applied to segmentation of 3D medical images, and experiments confirm its high performance, which makes classical Chan-Vese model more practical. Copyright © 2013 ifac.

关键词： Image segmentation

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Deterministic learning control of a robotic system via neural networks

Deterministic learning control of a robotic system via neura...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Li, Zhixun He, Wei Tao, Zui Liu, Chang School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China

ISBN: (纸本)9783902823458

In this paper, deterministic learning control using neural networks (NNs) is presented for a robotic system with unknown system dynamics. The dynamics of the robotic system are represented by an n-link strict robotic manipulator. The adaptive NNs is employed as the first control strategy to approximate the unknown model of the system and adapt interactions between the robot and a patient. Deterministic learning control using learned knowledge from direct NNs with Radial Basis Functions (RBFs) is employed as the second control strategy to improve the system intelligence for energy conservation and reduce control tasks. Uniform ultimate boundedness (UUB) of the closed loop system is achieved under the condition of the Lyapunov's stability with full state feedback control. Extensive simulations are carried out to expound the efficacy of the proposed control strategies and the advancement of learning control. Copyright © 2013 ifac.

关键词： Closed loop systems

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A new self-learning optimal control scheme for discrete-time nonlinear systems using policy iterative adaptive dynamic programming

A new self-learning optimal control scheme for discrete-time...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Wei, Qinglai Liu, Derong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783902823458

In this paper, a new self-learning method using policy iterative adaptive dynamic programming (ADP) is developed to obtain the optimal control scheme of discrete-time nonlinear systems. The iterative ADP algorithm permits an arbitrary admissible control law to initialize the iterative algorithm. It is the first time that the properties of the policy iterative ADP are established for the discrete-time situation. It proves that the iterative performance index function is nonincreasingly convergent to the optimal solution of the Hamilton-Jacobi-Bellman (HJB) equation. It also proves that any of the iterative control policy can stabilize the nonlinear systems. Neural networks are used to approximate the performance index function and compute the optimal control policy, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, a simulation example is given to illustrate the performance of the present method. Copyright © 2013 ifac.

关键词： Reinforcement learning

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Model free adaptive iterative learning control for farm vehicle path tracking

Model free adaptive iterative learning control for farm vehi...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Bu, Xuhui Hou, Zhongsheng Chi, Ronghu School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo China Advanced Control Systems Lab. School of Electronics and Information Engineering Beijing Jiaotong University Beijing China School of Automation and Electrical Engineering Qingdao University of Science and Technology Qingdao 266042 China

ISBN: (纸本)9783902823458

Duo to the periodicity of farm cropping, harvesting, seeding and spraying, a discrete time model free adaptive iterative learning control (MFAILC) algorithm for path tracking of farm vehicle is proposed. Based on the dynamical form linearization model for farm vehicle kinematic model l, the MFAILC algorithm can be designed just depending on the I/O data of the farm vehicle. The proposed method also can compensate the effect of initial shifting to preserve a perfect tracking. Simulations results illustrate the validity of the proposed methods. Copyright © 2013 ifac.

关键词： Iterative methods

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Iterative learning control for a class of inhomogeneous heat equations

Iterative learning control for a class of inhomogeneous heat...

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3rd ifac conference on intelligent control and automation science, icons 2013

作者： Huang, Deqing Li, Xuefang Department of Aeronautics Imperial College London South Kensington Campus United Kingdom Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

ISBN: (纸本)9783902823458

This paper addresses the boundary control problem of heat equations under the framework of iterative learning control (ILC). Without any simplification or discretization of the 3D dynamics in the time, space as well as iteration domains, the learning convergence of ILC is guaranteed through rigorous analysis by transforming the inhomogeneous heat equation into its integral form and exploiting the properties of the embedded Jacobi Theta functions. The proposed scheme not only makes anticipatory compensation possible to overcome the heat conduction delay in boundary output tracking, but also eliminates the gain margin limitation encountered in feedback control. In the end, an illustrative example is presented to demonstrate the performance of the proposed ILC scheme. Copyright © 2013 ifac.

关键词： Heat conduction

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