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Knowledge-based artificial fish-swarm algorithm

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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Stability analysis and design for discrete fuzzy systems with time-delay under imperfect premise matching

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Journal of Information and Computational Science 2011年第13期8卷 2613-2622页

作者： Zhang, Zejian Huang, Xianlin Ban, Xiaojun Gao, X.Z. Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin 150001 China Department of Automation and Systems Technology School of Electrical Engineering Aalto University Otaniementie 17 00076 Aalto Finland

This paper is concerned with the issue of stability analysis and controller design for the discrete T-S fuzzy control system with time-delay under imperfect premise matching, in which the discrete T-S fuzzy time-delay model and fuzzy controller do not share the same membership functions. Some novel stability conditions including the information of membership functions of the discrete fuzzy time-delay model and controller are proposed. The new stability conditions are less conservativeness, and enhance the design flexibility by arbitrarily selecting membership functions for the fuzzy controller as well. Two numerical examples are presented to illustrate the less conservativeness and the effectiveness of the proposed results. 1548-7741/Copyright © 2011 Binary Information Press.

关键词： Fuzzy control

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A linear multi-agent systems approach to diffusively coupled piecewise affine systems: Delay robustness

A linear multi-agent systems approach to diffusively coupled...

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IEEE Conference on Decision and control

作者： Kenji Kashima Antonis Papachristodoulou Frank Allgöwer Graduate School of Information Science and Engineering Tokyo Institute of Technology Tokyo Japan Department of Engineering Science University of Oxford Oxford UK Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany

ISBN: (纸本)9781612848006;9781612848013

In this paper, we investigate ultimate boundedness of large-scale arrays consisting of piecewise affine (PWA) sub-systems linearly interconnected through channels with delays. Under an assumption on subsystem dynamics, it is shown that ultimate boundedness can be reduced to the stability of a linear delay differential system. This enables us to use linear multi-agent system theory. As a result, we obtain sufficient conditions for ultimate boundedness taking the robustness of the interconnection topology into account. The usefulness of the results is examined through its application to the FitzHugh-Nagumo model.

关键词： Delay Europe Silicon Biology

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Vibration control of a Multi-Flexible-Link Robot Arm under Gravity

Vibration Control of a Multi-Flexible-Link Robot Arm under G...

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IEEE International Conference on Robotics and Biomimetics

作者： J. Malzahn A. S. Phung F. Hoffmann T. Bertram Institute of Control Theory and Systems Engineering Technische Universitat Dortmund

ISBN: (纸本)9781457721366

This paper proposes a novel independent joint control concept on a 3 DOF flexible link robot subject to deflections caused by gravity. The scheme dampens induced link oscillations in the presence of configuration dependant plant frequency and damping variations by integrating link strain feedback and impulse based input shaping. The approach is robust and the control does not depend on a dynamic model at runtime. The damping efficiency is evaluated experimentally in terms of strain measurement as well as end-effector position across the entire workspace.

关键词： Multi-flexible-link robots Vibration control Independent joint control

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A Distributed Simplex Algorithm and the Multi-Agent Assignment Problem

A Distributed Simplex Algorithm and the Multi-Agent Assignme...

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2011 American control Conference (ACC)

作者： Mathias Burger Giuseppe Notarstefano Frank Allgower Francesco Bullo Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Department of Engineering University of Lecce Lecce Italy Dynamical Systems and Computation University of California슠Santa Barbara CA USA

In this paper we propose a novel distributed algorithm to solve degenerate linear programs on asynchronous networks. Namely, we propose a distributed version of the well known simplex algorithm. We prove its convergence to the global lexicographic minimum for possibly fully degenerate problems and provide simulations supporting the conjecture that the completion time scales linearly with the diameter of the graph. The algorithm can be interpreted as a dual version of the constraints consensus algorithm proposed in [1] to solve abstract programs when the last is applied to linear programs. Finally, we study a multi-agent task assignment problem and show that it can be solved by means of our distributed simplex algorithm.

关键词： Linear programming Optimization Distributed algorithms Algorithm design and analysis Vectors Convergence Program processors

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Data Based Kinematic Model of a Multi-Flexible-Link Robot Arm for Varying Payloads

Data Based Kinematic Model of a Multi-Flexible-Link Robot Ar...

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IEEE International Conference on Robotics and Biomimetics

作者： A. S. Phung J. Malzahn F. Hoffmann T. Bertram Institute of Control Theory and Systems Engineering Technische Universitat Dortmund

ISBN: (纸本)9781457721366

Reducing weight and inertias of conventional robot arms with an elastic structure allows safer interactive cooperation between humans and robots. While the end effector pose of a rigid robot is determined by the forward kinematic chain, the pose of elastic arms results from a superposition of the rigid kinematics and the pose dependent deflection caused by gravity. This property complicates the computation of forward and inverse kinematics in particular in case of dynamic loads. This paper presents a machine learning approach to extract various nonlinear regression models of the forward and inverse kinematics of a three degrees of freedom (DOF) flexible-link robot arm with dynamic loads from experimental data. The forward model predicts the target pose, given the joint angles and the strain signals while the inverse kinematic model predicts the joint angles required to assume a target pose. The transformation of the original features onto suitable nonlinear features substantially improves the generalisation ability of the both forward and inverse kinematic model. The closed loop inverse kinematic controller archieves a pose accuracy of 3 mm and the results show that the learned model can solve the inverse kinematics problem of flexible robot arms with sufficient accuracy even with unknown payloads.

关键词： Flexible-link robot arm Neural network Kinematic problem

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Locally Constrained Decision Making via Two-Stage Distributed Simplex

Locally Constrained Decision Making via Two-Stage Distribute...

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IEEE Conference on Decision and control

作者： Mathias Burger Giuseppe Notarstefano Frank Allgower Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 70550 Stuttgart Germany Department of Engineering University of Lecce Via per Monteroni 73100 Lecce Italy

ISBN: (纸本)9781612848006

In this paper we propose a distributed algorithm for solving linear programs with combinations of local and global constraints in a multi-agent setup. A fully distributed and asynchronous algorithm is proposed. The computation of the local decision makers involves the solution of two distinct (local) optimization problems, namely a local copy of a global linear program and a smaller problem used to generate "problem columns". We show that, when running the proposed algorithm, all decision makers agree on a common optimal solution, even if the original problem has several optimal solutions, or detect unboundedness and infeasibility if necessary.

关键词： decision makers optimal solution linear programming distributed algorithms original problem decision making Simplex Distribute local optimization

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On State-Constrained control of a CSTR *

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IFAC Proceedings Volumes 2011年第1期44卷 6079-6084页

作者： Florian Bayer Mathias Bürger Martin Guay Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 70550 Stuttgart Germany Department of Chemical Engineering Queen's University Kingston Ontario Canada K7L 3N6

Abstract In this note, we study the problem of multiple hard output constraints imposed on a continuous stirred tank reactor (CSTR) subject to external disturbances. Constraints on the concentration and on the temperature are considered. We show, analytically and with simulations, that there are critical combinations of constraints, where robust constraint satisfaction cannot be guaranteed. As a consequence violation of at least one constraint has to be allowed.

关键词： State-Constraints Process control Robust control

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Object existence probability fusion using dempster-shafer theory in a high-level sensor data fusion architecture

Object existence probability fusion using dempster-shafer th...

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IEEE Symposium on Intelligent Vehicle

作者： Michael Aeberhard Sascha Paul Nico Kaempchen Torsten Bertram Group Connected Drive BMW Group Research and Technology Munich Germany Group Information Technology BMW AG Munich Germany Institute of Control Theory and Systems Engineering Technical University Dortmund Munich Germany

Future driver assistance systems need to be more robust and reliable because these systems will react to increasingly complex situations. This requires increased performance in environment perception sensors and algorithms for detecting other relevant traffic participants and obstacles. An object's existence probability has proven to be a useful measure for determining the quality of an object. This paper presents a novel method for the fusion of the existence probability based on Dempster-Shafer evidence theory in the framework of a highlevel sensor data fusion architecture. The proposed method is able to take into consideration sensor reliability in the fusion process. The existence probability fusion algorithm is evaluated for redundant and partially overlapping sensor configurations.

关键词： Driver circuits Vehicles Electronic mail Robustness Estimation Bayesian methods Uncertainty

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The application of BP Neural Network based on improved PSO in BF temperature forecast

The application of BP Neural Network based on improved PSO i...

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International Conference on Electrical and control engineering (ICECE)

作者： Hongjun Wang Dexiong Li Zhuoqun Zhao Huijuan Qi Lina Liu Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Tianjin University of Technology Tianjin China Shijiazhuang Institute of Railway Technology Shijiazhuang China HNV College of Mechanical and Vehic Engineering Changsha China

The BP network has the disadvantages such as low learning efficiency, low speed of convergence, easily falling into the local minimum state, poor ability to adapt, ect. For PSO algorithm, it is fast for convergence, especially at the initial stage, simple for the computing, and is easy to implement. Compared with the genetic algorithms, it does have not the complex operations of hybrid codecs, mutation, so it is a good optimization algorithm. However, PSO algorithm also has some shortcomings it is more and more slow for convergence rate at the late evolution of the algorithm. In this paper, a new BP Neural Network based on improved Particle Swarm Optimization (PSO) is proposed. The convergence speed of this algorithm and the capacity of searching global extremum is increased through adjusting the adaptive capacity of learning factor. The simulation results illustrate that the improved PSO is superior to the standard BP algorithm and particle swarm optimization.

关键词： Particle swarm optimization Blast furnaces Iron Biological neural networks Temperature measurement Neurons Convergence

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