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作者： Zhang, Dan Yu, Li Wang, Qing-Guo Department of Automation Zhejiang University of Technology Zhejiang Provincial United Key Laboratory of Embedded Systems Hangzhou 310032 China Department of Mechanical Engineering National University of Singapore 117576 Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore 119260 Singapore Singapore

ISBN: (纸本)9788995605646

This paper is dealt with the fault detection problem for a class of network-based nonlinear systems with communication constraints and random missing measurements. The nonlinear plant is described by a Takagi-Sugeno (T-S) fuzzy time-delay model, it has multiple sensors and only one of them can access to the fault detection filter at each transmission instant. The measurement signal is missing randomly and the missing rate differs from one channel link to another. The goal is to design a fault detection filter such that, the estimation error between the residual and fault is minimized. By casting the addressed fault detection problem into an auxiliary H∞ filtering problem of a stochastic switched fuzzy time-delay system, a sufficient condition for the existence of the desired fault detection filter is obtained. A numerical example is provided to illustrate the effectiveness and applicability of the proposed technique. © 2011 Asian control Association.

关键词： Nonlinear systems

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The Research on Time-varying Parameter Identification in Support Beam under Moving Mass

The Research on Time-varying Parameter Identification in Sup...

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第四届国际机械工程与力学会议

作者： Minzhuo WANG Qiang CHEN Guolai YANG Department of Systems and Control Engineering School of Management and EngineeringNanjing University Department of Mechanical Design and Automation School of Mechanical EngineeringNanjing University of Science and Technology

This paper reviews the current knowledge about time-varying parameter identification in support beam under moving mass. The basic models of support beam are described first. Then three classical methods of identification are introduced. Finally, Interpretive Method (IM) is applied to the cantilever and the inertia force which is between the beam and moving mass has been numerical calculated. According to comparison of numerical calculation with different parameters model by using Interpretive Method (IM), relative percentage error is defined. In calculation, only one parameter can be changed, i.e. changing sampling frequency, accuracy of natural frequency or the order of modal. According to the results of identification, the effect of different parameters on the result of identification is discussed and an optimal set of parameters is obtained.

关键词： Time-varying parameter, Inertia force, Identification, Cantilever, Interpretive Method

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Robust Model Matching for Geometric Fault Detection Filters

Robust Model Matching for Geometric Fault Detection Filters

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American control Conference

作者： Peter Seiler Jozsef Bokor Balint Vanek Gary J. Balas Aerospace and Engineering Mechanics Department University of Minnesota Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences

ISBN: (纸本)9781457700811

Geometric fault detection and isolation filters are known for having excellent fault isolation properties. However, they are generally assumed to be sensitive to model uncertainty and noise. This paper proposes a robust model matching method to incorporate model uncertainty into the design of geometric fault detection filters. Several existing methods for robust filter synthesis are described to solve the robust model matching problem. It is then shown that the robust model matching problem has an interesting self-optimality property for multiplicative input uncertainty models. Finally, a simple example is presented to study the effect of parametric uncertainty and unmodeled dynamics on the performance of a geometric filter.

关键词： Robustness Uncertainty Mathematical model Fault detection Computational modeling Equations Linear matrix inequalities

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Inverse dynamics compensation via 'simulation of feedback control systems'

Inverse dynamics compensation via 'simulation of feedback co...

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作者： Tagawa, Y. Tu, J.-Y. Stoten, D.P. Department of Mechanical Systems Engineering Tokyo University of Agriculture and Technology 2-24-16 Nakacho Koganei Tokyo 184-8588 Japan Department of Mechanical Engineering National Tsinghua University Hsinchu City Taiwan Advanced Control and Test Laboratory University of Bristol Bristol United Kingdom

In many applications within the fields of science, engineering, mathematics, and socio-economics, the 'inverse problem' (i.e. the problem of determining a system's input from its output) is commonplace. The current paper presents a new concept for solving the inverse problem, which the authors call inverse dynamics compensation via 'simulation of feedback control systems' (IDCS). IDCS is a numerical method that obtains an approximate inverse dynamic solution via a feedback control simulation, using only the forward dynamic model of the linear or non-linear system. Simulations are ideal environments for feedback control, in the sense that they can be completely noise-free and precisely known, so that the IDCS method can be tuned for the best possible performance. It is seen that IDCS can use the advantages of such ideal control simulation performance in the real world of physical implementations. This paper first introduces the basic idea of IDCS. Then, the effectiveness of the proposed method is demonstrated via three illustrative examples, in which the systems to be controlled have continuous and discontinuous non-linearities. IDCS performance is also investigated via physical experimentation on a non-linear servohydraulic test rig. Finally, extensions of the basic IDCS formulation are introduced which are potentially useful for the solution of additional practical problems. © Authors 2011.

关键词： Inverse problems

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A Complementary Modularized Ramp Metering Approach Based on Iterative Learning control and ALINEA

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IEEE Transactions on Intelligent Transportation systems 2011年第4期12卷 1305-1318页

作者： Zhongsheng Hou Xin Xu Jingwen Yan Jian-Xin Xu Gang Xiong Advanced Control Systems Laboratory School of Electronic and Information Engineering Beijing Jiaotong University BJTU Beijing China Institute of Automation College of Mechatronics and Automation National University of Defense Technology Changsha China Department of Electrical and Computer Engineering National University of Singapore Singapore Automation Institute Chinese Academy of Sciences (CAS) Beijing China

Ramp metering is an effective tool for traffic management on freeway networks. In this paper, we apply iterative learning control (ILC) to address ramp metering in a macroscopic-level freeway environment. By formulating the original ramp metering problem as an output regulating and disturbance rejection problem, ILC has been applied to control the traffic response. The learning mechanism is further combined with Asservissement Linéaire d'Entrée Autoroutière (ALINEA) in a complementary manner to achieve the desired control performance. The ILC-based ramp metering strategy and the modified modularized ramp metering approach based on ILC and ALINEA in the presence of input constraints are also analyzed to highlight the advantages and the robustness of the proposed methods. Extensive simulations are given to verify the effectiveness of the proposed approaches.

关键词： Traffic control Mathematical model Convergence Learning systems Feedforward neural networks

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Wind turbine pitch optimization

Wind turbine pitch optimization

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IEEE Conference on control technology and Applications (CCTA)

作者： Benjamin Biegel Morten Juelsgaard Matt Kraning Stephen Boyd Jakob Stoustrup Department of Automation and Control University of Aalborg Aalborg Denmark Information Systems Laboratory Electrical Engineering Department Stanford University Stanford CA USA

We consider a static wind model for a three-bladed, horizontal-axis, pitch-controlled wind turbine. When placed in a wind field, the turbine experiences several mechanical loads, which generate power but also create structural fatigue. We address the problem of finding blade pitch profiles for maximizing power production while simultaneously minimizing fatigue loads. In this paper, we show how this problem can be approximately solved using convex optimization. When there is full knowledge of the wind field, numerical simulations show that force and torque RMS variation can be reduced by over 96% compared to any constant pitch profile while sacrificing at most 7% of the maximum attainable output power. Using iterative learning, we show that very similar performance can be achieved by using only load measurements, with no knowledge of the wind field or wind turbine model.

关键词： Blades Wind turbines Fatigue Rotors Force Poles and towers Torque

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Multi-channel template extraction for automatic EEG spike detection

Multi-channel template extraction for automatic EEG spike de...

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IEEE/ICME International Conference on Complex Medical engineering, CME

作者： Zhanfeng Ji Takenao Sugi Satoru Goto Xingyu Wang Masatoshi Nakamura Department of Automation East China University of Science and Technology Shanghai China Department of Advanced Systems Control Engineering Saga University Saga Japan Research Institute of Systems Control Saga Japan

A multi-channel template extraction method is proposed for automatic EEG spike detection. The template is extracted automatically without any prior knowledge. The template extraction algorithm consists of three steps. Firstly, all possible spike events are detected. Secondly, the focus channels are identified for each event. Thirdly, the multi-channel template is extracted for each focus channel. The algorithm produces template adapted to not only individual patient, but also individual focus. The method was evaluated using the recordings from two epilepsy patients. The results suggested that template method should be of multi-channel for spike detection.

关键词： Correlation Nickel

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Knowledge-based artificial fish-swarm algorithm

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IFAC Proceedings Volumes 2011年第1期44卷 14705-14710页

作者： Ying Wu Xiao-Zhi Gao Kai Zenger Control Theory and Engineering Department Harbin Institute of Technology Harbin 150001 China Department of Automation and Systems Technology Aalto University School of Electrical Engineering Espoo P.O.BOX 15500 FI-00076 Aalto Finland

Abstract In this paper, a knowledge-based Artificial Fish-Swarm (AFA) optimization algorithm with crossover, CAFAC, is proposed to enhance the optimization efficiency and combat the blindness of the search of the AFA. In our CAFAC, the crossover operator is first explored. The knowledge in the Culture Algorithm (CA) is next utilized to guide the evolution of the AFA. Both the normative knowledge and situational knowledge is used to direct the step size as well as direction of the evolution in the AFA. Ten high-dimensional and multi-peak functions are employed to investigate this new algorithm. Numerical simulation results demonstrate that it can indeed outperform the original AFA.

关键词： Artificial Fish-Swarm Algorithm (AFA) Crossover operator Culture Algorithm (CA)

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Dynamic vehicle routing for robotic systems

Dynamic vehicle routing for robotic systems

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作者： Bullo, Francesco Frazzoli, Emilio Pavone, Marco Savla, Ketan Smith, Stephen L. Center for Control Dynamical Systems and Computation Department of Mechanical Engineering University of California in Santa Barbara Santa Barbara CA 93106 United States Laboratory for Information and Decision Systems Department of Aeronautics and Astronautics Massachusetts Institute of Technology Cambridge MA 02139 United States Jet Propulsion Laboratory California Institute of Technology Pasadena CA 91109 United States Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA 02139 United States Department of Electrical and Computer Engineering University of Waterloo Waterloo ON N2L 3G1 Canada

Recent years have witnessed great advancements in the science and technology of autonomy, robotics, and networking. This paper surveys recent concepts and algorithms for dynamic vehicle routing (DVR), that is, for the automatic planning of optimal multivehicle routes to perform tasks that are generated over time by an exogenous process. We consider a rich variety of scenarios relevant for robotic applications. We begin by reviewing the basic DVR problem: demands for service arrive at random locations at random times and a vehicle travels to provide on-site service while minimizing the expected wait time of the demands. Next, we treat different multivehicle scenarios based on different models for demands (e.g., demands with different priority levels and impatient demands), vehicles (e.g., motion constraints, communication, and sensing capabilities), and tasks. The performance criterion used in these scenarios is either the expected wait time of the demands or the fraction of demands serviced successfully. In each specific DVR scenario, we adopt a rigorous technical approach that relies upon methods from queueing theory, combinatorial optimization, and stochastic geometry. First, we establish fundamental limits on the achievable performance, including limits on stability and quality of service. Second, we design algorithms, and provide provable guarantees on their performance with respect to the fundamental limits. © 2011 IEEE.

关键词： Adaptive algorithms

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control of Upper-Limb Power-Assist Exoskeleton Based on Motion Intention Recognition

Control of Upper-Limb Power-Assist Exoskeleton Based on Moti...

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2011 IEEE International Conference on Robotics and automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

作者： Yongji Wang Jian Huang Weiguang Huo Jun Wu Lei Cheng Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Technol Engineering Research Center of Metallurgical Automation and Measurement Technology Ministry of Educa

Recognizing the user motion intention plays an important role in the study of power-assist robots. An intention-guided control strategy is proposed for the upper-limb power-assist exoskeleton. A force sensor system comprised of force sensing resistors (FSRs) is designed to online estimate the motion intention of user upper limb. A new concept called “intentional reaching direction (IRD)” is proposed to quantitatively describe this intention. Both the state model and the observation model of IRD are obtained by enumerating the upper limb behavior modes and analyzing the relationship between the measured force signals and the motion intention. Based on these two models, the IRD can be online inferred by applying filtering technology. Guided by the estimated IRD, an admittance control strategy is assumed to control the motions of three DC motors in the joints of the robotic arm. The effectiveness of the proposed approaches is finally confirmed by the experiments on a 3-DOF robotic exoskeleton.

关键词： Joints Exoskeletons Force Humans Robot sensing systems Jacobian matrices

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