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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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Particle Swarm Optimization Based on Gaussian Mutation and Its Application to Wind Farm Micro-siting

Particle Swarm Optimization Based on Gaussian Mutation and I...

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2010 49th IEEE Conference on Decision and control

作者： Chunqiu Wan Jun Wang Geng Yang Xing Zhang Department of Automation Tsinghua University Beijing 100084 P. R. China Department of Control Science and Engineering Tongji University Shanghai 201804 P. R. China School of Aerospace Tsinghua University Beijing 100084 P. R. China

ISBN: (纸本)9781424477456

In this paper, a particle swarm optimization algorithm with Gaussian mutations, denoted by GPSO, is proposed to solve constrained optimization problems. Two Gaussian mutation operators are employed to search the promising regions for better solutions. One operator is for the region between the personal best position and the global best one. The other operator is for the region around the global best position. The Gaussian mutations help the population jump out of local optima and find better solutions with more probability. The feasibility-based method compares the performance of different particles. Evaluated by three typical optimization problems, GPSO is more accurate, robust and efficient for locating global optima. The GPSO method is applied to a wind-farm micrositing problem. Simulation results demonstrate that the power generation of the wind farm is further improved while the execution time is substantially reduced.

关键词： Wind farms Particle swarm optimization Gauss execution time Power production micro Wind Mutation particle swarm algorithm

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Robust stabilization of uncertain kinematic systems in nonholonomic mobile robots with one trailer

Robust stabilization of uncertain kinematic systems in nonho...

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Chinese control Conference (CCC)

作者： Chaoli Wang Fang Yang Yunhui Liu Zhenying Liang Control Science and Engineering Department University of Shanghai for Science and Technology (USST) Shanghai P. R. China Business School Ningbo University of Technology Shanghai P. R. China Dept. of Mechanical and Automation Engineering The Chinese University of Hong Kong Satin NT P. R. China Business School Shandong University of Technology Shanghai P. R. China

Based on visual servoing feedback, this paper provides a novel uncertain model of the kinematic systems in nonholonomic mobile robots with one trailer with uncalibrated visual servoing parameters. The strongly nonlinear disturbances and drift terms in its uncertain chained form of this model fails to meet the so called triangularity condition. The methods available in the literatures are not suitable to be used to investigate its stabilizing problem of the system. In order to deal with this difficulty, the special structure of the systems is exploited to design the stabilizing controller, which is divided into three phases. In the first phase, a newly state transformation is exploited to propose a stabilizing controller to make most of the states of the system tends to zero only excepts one state. In the second phase, the left state is stabilized and the other states remain little change by designing another controller. In the final phase, the control inputs can be set zero. The states remain constant. Finally, the simulation is presented to illustrate the stabilizing performance of the developed control algorithm.

关键词： Mobile robots Kinematics Cameras Robot vision systems Visualization Robustness Polynomials

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

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

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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 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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A NEW NEURAL NETWORK-BASED ADAPTIVE ILC FOR NONLINEAR DISCRETE-TIME SYSTEMS WITH DEAD ZONE SCHEME

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Journal of Systems science & Complexity 2009年第3期22卷 435-445页

作者： Ronghu CHI Zhongsheng HOU Institute of Autonomous Navigation and Intelligent Control School of Automation and Electrical EngineeringQingdao University of Science and Technology Qingdao 266042 China. Advanced Control Systems Laboratory School of Electronics and Information Engineering Beijing JiaotongUniversity Beijing 100044 China.

By introducing a deadwzone scheme, a new neural network based adaptive iterative learning control （ILC）（NN-AILC） scheme is presented for nonlinear discrete-time systems, where the NN weights are time-varying. The most distinct contribution of the proposed NN-AILC is the relaxation of the identical conditions of initial state and reference trajectory, which are common requirements in traditional ILC problems. Convergence analysis indicates that the tracking error converges to a bounded ball, whose size is determined by the dead-zone nonlinearity. Computer simulations verify the theoretical results.

关键词： Adaptive control iterative learning control neural network non-identical initial condition,non-identical trajectory.

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State observation for a class of uncertain nonlinear systems via deterministic learning

State observation for a class of uncertain nonlinear systems...

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Chinese control Conference (CCC)

作者： Guopeng Zhou Cong Wang College of electric and electronic engineering Huazhong University of Science and Technology Wuhan P.R. China College of Mathematics and statistics Xianning University Xianning P.R. China School of Automation Center for Control and Optimization South China University of Technology Guangzhou P.R. China

In this paper, based on the recently proposed theory of deterministic learning, a new neural observer is proposed for a class of uncertain nonlinear systems undergoing periodic or recurrent motions. Firstly, it is shown that the state observation error converges to a small neighborhood of zero exponentially in finite time, and a partial persistent excitation (PE) condition is satisfied. Secondly, by imposing an auxiliary filter and constructing a new Lyapunov function, it is obtained that the neural weight estimation error also converges to a small neighborhood of zero. Thus, the system uncertain dynamics along the periodic trajectory can be locally-accurately identified by the radial basis function(RBF) neural networks(NNs) and then stored in a constant RBF NNs. Finally, a constant NNs observer is also implemented, with guaranteed stability and good performance. The proposed observer scheme does not require high-gain design, and the embedded localized NNs can learn (identify) the nonlinear uncertain dynamics along the estimated periodic or recurrent system trajectory.

关键词： Observers Artificial neural networks Trajectory Nonlinear systems Approximation methods Adaptive systems Radial basis function networks

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Diagnosis of UAV Pitot Tube Defects Using Statistical Change Detection

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IFAC Proceedings Volumes 2010年第16期43卷 485-490页

作者： Søren Hansen Mogens Blanke Jens Adrian Technical University of Denmark Department of Electrical Engineering Automation and Control Group Elektrovej B. 326 DK-2800 Lyngby. Denmark Danish Forces Joint UAV Team Naval Weapons School Gnibenvej 55 DK-4583 Sjællands Odde. Denmark CeSOS Marine Technology Centre Norwegian University of Science and Technology NTNU NO-7491 Trondheim Norway

Unmanned Aerial Vehicles need a large degree of tolerance to faults. One of the most important steps towards this is the ability to detect and isolate faults in sensors and actuators in real time and make remedial actions to avoid that faults develop to failure. This paper analyses the possibilities of detecting faults in the pitot tube of a small unmanned aerial vehicle, a fault that easily causes a crash if not diagnosed and handled in time. Using as redundant information the velocity measured from an onboard GPS receiver, the air-***speed estimated from engine throttle and the pitot tube based airspeed, the paper analyses the properties of residuals. A dedicated change detector is suggested that works on pre-whitened residuals and a generalised likelihood ratio test is derived for a Cauchy probability density, which the residuals are observed to have. A detection scheme is obtained using a threshold that provides desired quantities of false alarm and detection probabilities. Fault detectors are build based on raw residual data and on a whitened edition of these. The two detectors are compared against recorded telemetry data of an actual event where a pitot tube defect occurred.

关键词： Fault detection Change detection Unmanned Aerial Vehicle Pitot tube

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New enhancement of infrared image based on human visual system

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Chinese Optics Letters 2009年第3期7卷 206-209页

作者：于天河李秋明戴景民 Department of Automation Measurement and Control Engineering Harbin Institute of Technology Computer Center Harbin University of Science and Technology School of Astronautics Harbin Institute of Technology

Infrared images are firstly analyzed using the multifractal theory so that the singularity of each pixel can be extracted from the images. The multifractal spectrum is then estimated, which can reflect overall characteristic of an infrared image. Thus the edge and texture of an infrared image can be accurately extracted based on the singularity of each pixel and the multifractal spectrum. Finally the edge pixels are classified and enhanced in accordance with the sensitivity of human visual system to the edge profile of an infrared image. The experimental results obtained by this approach are compared with those obtained by other methods. It is found that the proposed approach can be used to highlight the edge area of an infrared image to make an infrared image more suitable for observation by human eyes.

关键词： Imaging systems Infrared imaging Infrared spectroscopy Pixels

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