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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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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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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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Improved Multidisciplinary Multiobjective Collaborative Optimization Technique Based on NSGA-II Algorithm 1

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IFAC Proceedings Volumes 2010年第25期43卷 139-144页

作者： H. Li Y. Jing S. Zhang V. Ojleska T. Kolemisevska G.M. Dimirovski Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University Shenyang 110004 P.R. China Northeastern University School of Information Science & Engineering Shenyang 110004 P.R. China SS Cyril and Methodius University School FEIT Institute of ASE Karpos II BB MK-1000 Skopje R. Macedonia Dogus University Computer Eng. and Control Eng. Departments TR-34722 Istanbul Turkey

The multiobjective collaborative optimization (MCO) has been widely adopted in concurrent engineering design as a good multiobjective optimization approach provided the problem of optimization results converging often to a local extremum has been taken care of. It has been demonstrated to yield useful solutions to a wide range of optimization problems under concurrent condition both technical and non-technical ones. A solution strategy for MCO that overcomes this drawback is proposed here on the grounds of genetic NSGA-II algorithm. It is an adaptive heuristic search technique that controls the distances between the individual and system's feasible region during genetic evolution. In the evolving NSGA-II based non-dominated sorting, the individual threshold of infeasibility degree is reduced gradually via genetic evolution and the individual's feasibility capacity is determined by its infeasibility degree and the threshold. It has been applied to a benchmark example of speed reducer design, and the obtained results demonstrate the proposed technique is comparably more efficient and may offer substantial advantages over the gradient-based optimization methods. Copyright © 2010 IFAC

关键词： Collaborative optimization dynamic threshold genetic algorithms multidisciplinary optimization multiobjective optimization

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Optimal weights for consensus of networked multi-agent systems

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Information Technology Journal 2009年第1期8卷 77-82页

作者： Li, Xiang-Shun Fang, Hua-Jing Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China School of Automation Wuhan University of Technology Wuhan 430070 Hubei China

In this study, a way to design the optimal weights associated with edges of undirected graph composed of multi-agent systems is presented. The optimal weights are designed to make the states of the multi-agent systems converge to consensus with a fast speed as well as the maximum communication time-delay can be tolerated. The method used in our research is based on linear matrix inequality theory. The convergence speed which is determined by the second-smallest eigenvalue of graph Laplacian matrix is assumed to be a given value, at the same time the maximum communication time-delay which is decided by the maximum eigenvalue of Laplacian matrix can be got. In order to get required second-smallest eigenvalue and optimal maximum eigenvalue, the order of Laplacian matrix is reduced by variable decomposition. Moreover, designing the optimal weights is equivalent to minimizing condition number of a positive-definite matrix. Simulation results are coincidental with theoretical analysis. © 2009 Asian Network for Scientific Information.

关键词： Multi agent systems

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Improved grey-topology algorithm for forecasting

Improved grey-topology algorithm for forecasting

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6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： Li, Zhi-Jun Dai, Qing-Quan Song, Ye-Xin Chen, Mian-Yun School of Automation WHUT Wuhan China College of Science NUE Wuhan China Department of Control Science and Engineering HUST Wuhan China

ISBN: (纸本)9780769537351

Scientific forecast is of great importance to the economic phenomenon research and economic decisionmaking. Therefore, the research about economic forecast theory and method is always a hot topic. This paper proposed an algorithm combined with the grey model, least square method and topology model, which can be a new advanced algorithm for forecasting. Using this new algorithm, the paper forecasts the tendency of average energy consumption per person of our country and then come to the conclusion that the new algorithm is more accurate. It proves that the new algorithm is a good one and can be used by authorities to make strategy decision for economy. © 2009 IEEE.

关键词： Topology

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The smooth switching of fuzzy-PI control

The smooth switching of fuzzy-PI control

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6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： He, Fang Zhao, Shouhua Tong, Weiming Yu, Bo Wang, Qiang School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China School of Control Science and Engineering University of Jinan Jinan China College of Automation Qingdao Technological University Qingdao China School of Mechanical Engineering University of Jinan Jinan China

ISBN: (纸本)9780769537351

Various methods of multimode control are adopted more and more widely to improve the performance of control systems. The problem of smooth switching of different controllers is the key in application of multimode control. This paper focuses on the unsteady problem at switching point of controllers in multimode control system. The concept of smooth switching in process of switching is proposed. And different switching methods are analyzed. The feasibility of idea of switching at natural switching point is discussed. Specially, the smooth switching of Fuzzy-PI control is analyzed and the fuzzy controller is designed. The simulation about smooth switching at natural switching point of Fuzzy-PI control system is done to prove the idea of natural switching. The analysis result of this paper can offer effective reference for other multimode control design. © 2009 IEEE.

关键词： controllers

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