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World Congress on Intelligent control and Automation (WCICA)

作者： Zhang Fan Shang Hua Mu Chundi Lu Yuchang Department of Computer Science and Technology Tsinghua University Beijing China Qingdao Branch Naval Aeronautic Engineering College Qingdao Shandong China Department of Automatic Control Tsinghua University Beijing China

In order to improve the pointing accuracy of a small satellite, the attitude control system is controlled with pitch-axis momentum and three-axis magnetic torquerods. The satellite dynamics equation and kinematic equation are built with the method of quaternion. For each of the three body axes, well-known PD control torque equations are adopted. Three position, three rate, and a dumping control gains are optimally found by building up the optimal attitude control model. In the model, two single objectives: the minimum of the transient time and the minimum of the sum of both the square sum of the attitude angle error and the square sum of the angle rate error are integrated into the multi objectives with multiobjective optimization method. The constraints require that the attitude angle, the angle rate, the three-axis dipole moment and the pitch wheel momentum should not exceed the required value. Finally, an application to the attitude control of a small satellite is presented as an example. Results show that the optimal control algorithm is feasible, effective, and reliable, and attitude control performance is also significantly improved after optimization, compared to the traditional PD control.

关键词： Satellites Wheels Magnetic moments Equations PD control Optimal control Torque control control systems Kinematics Quaternions

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A neural approach to an attentive navigation for 3D intelligent virtual agents

A neural approach to an attentive navigation for 3D intellig...

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IEEE International Conference on Systems, Man and Cybernetics

作者： M. Lozano J. Molina Artec Group Institute of Robotics. Computer Science Department University of Valencia Valencia Spain Neurotechnology Control and Robotics Group Engineering and Automatic Systems Department Politechnic University of Cartagena Spain

This paper presents an attempt to integrate attention and navigation skills in 3D embodied agents (virtual humanoids). The neural model presented has been divided in two main phases. Firstly the environment-categorization phase, where an online pattern recognition and categorization of the agent current sensory input data is carried out by an adaptive resonance driven self organizing neural network, which will finally simulate the agent's short term memory (STM). Secondly, the model must also learn how and when to map its current STM state into the navigation and attention motor layers of the 3D agent. We also review the world modelling and the agent vision system, and finally we present the first results extracted from two of the subsystems which conforms the complete neural model, such as, the environment categorization subsystem and the base navigation neural model.

关键词： Navigation Intelligent agent Intelligent robots Robotics and automation Humans Graphics Virtual environment Machine vision computer science Augmented virtuality

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Hybrid position/force control of constrained robot manipulator based on a feedforward neural network

Hybrid position/force control of constrained robot manipulat...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Lianfang Tian Jun Wang Zongyuan Mao Department of Mechanical Engineering University of California Riverside CA USA Department of Automation and Computer-aided Engineering Chinese University of Hong Kong New Territories Hong Kong China Department of Automatic Control Engineering South China University of Technology Guangzhou China

In this paper, the control of constrained robotic manipulators is addressed and the solution of a reduced order model is obtained through a nonlinear transformation. A set of differential-algebraic equations are first derived. Then controllers are designed for position and force control. The position control involves the position and velocity feedback of end-effector, while the force control is developed based on an artificial neural network. The weights of the neural network are updated online using the force error as the objective function. An example of a 2-DOF manipulator system is studied in detail. Comparisons between a conventional PID controller and the designed controller are made and a practical application is carried out. The results demonstrate the effective performance of the system.

关键词： Force control Manipulators Neural networks Feedforward neural networks Artificial neural networks Robot control Reduced order systems Differential equations Nonlinear equations Position control

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Constrained motion control of flexible manipulators based on a dynamic neural network

Constrained motion control of flexible manipulators based on...

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IEEE International Conference on Industrial Technology (ICIT)

ISBN: (纸本)0780376579

In this paper, a neural network approach is proposed for the motion control of a constrained flexible manipulator system, whereby both the contact force and the position of the end-effector contacting with a surface are controlled. The dynamic equations, vibration of the flexible link and constrained force are derived. The developed control scheme can adaptively estimate the dynamics of the manipulator by utilizing a dynamic recurrent neural network (DRNN) to approximate the underlying dynamics. Local stability of the system is discussed. The results confirm that the designed controller performs remarkably well.

关键词： Manipulator dynamics Motion control Neural networks automatic control Uncertainty control systems Motion planning Force control Equations Stability

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A pattern recognition approach to intelligent behaviour: switching the strategies

A pattern recognition approach to intelligent behaviour: swi...

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International IEEE Conference on Intelligent Systems, IS

作者： L. Frangu E. Ceanga S. Caraman Y. Boutalis Department of Automatic Control E2809CDunarea de Jos#x201D University Galati Romania Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece

The paper deals with the intelligent pattern recognition control systems. The concept of strategic situation is introduced, in the context of hierarchical structured control systems. It allows the investigation of the properties of the pattern recognition based control systems. The interaction between the system that recognizes strategies and the environment is described, along with the examples of control systems that allow such an approach. A case study, carried out on a simple process, is presented, to illustrate the method in a plausible context.

关键词： Pattern recognition control systems automatic control Intelligent control Process control Switches Humans Mobile robots Genetic algorithms Adaptive systems

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TWO - LEVEL DISSOLVED OXYGEN control FOR ACTIVATED SLUDGE PROCESSES

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IFAC Proceedings Volumes 2002年第1期35卷 467-472页

作者： M.A. Brdys W. Chotkowski K. Duzinkiewicz K. Konarczak R. Piotrowski Department of Automatic Control Technical University of Gdansk ul. G Narutowicza 11/12 80 952 Gdansk Poland School of Electronic Electrical and Computer Engineering The University of Birmingham Birmingham B15 2TT UK

Two-level controllers for dissolved oxygen reference trajectory tracking for activated sludge processes is proposed and investigated. Both the nutrient and the phosphorous removal from a wastewater by its biological treatment using an activated sludge technology are considered. Typically, an aeration system itself is a complicated hybrid nonlinear dynamical system with faster dynamics compared to internal dynamics of the dissolved oxygen at a biological reactor. It is common approach to neglect this dynamics and also important operational limitations of this system such as a limited frequency of allowed switching of the blowers. The paper proposes a two level controller to track prescribed dissolved oxygen trajectory. The upper level control unit produces desired aeration flow set points. For this unit the aeration system is an actuator. The nonlinear model predictive control algorithm is applied to design this controller unit. Also, the predictive control is used to design the lower level control unit based on a linearised hybrid dynamics of the aeration process. The overall controller is validated by simulation using real data sets and ASM2d model of the biological reactor.

关键词： bio-technical processes nonlinear systems set-point control predictive control hierarchical control

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POSITIVE REALNESS AND THE ANALYSIS OF A CLASS OF 2D LINEAR SYSTEMS

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IFAC Proceedings Volumes 2002年第1期35卷 219-224页

作者： K. Galkowski W. Paszke B. Sulikowski E. Rogers S. Xu J. Lam Z. Lin D.H. Owens Institute of Control and Computation Engineering University of Zielona Gora Poland Department of Electronics and Computer Science University of Southampton Southampton SO17 1BJ UK Departament of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada T6G 2V4 Department of Mechanical Engineering University of Hong Kong School of EEE Nanyang Technological University Nanyang Ave. 639798 Singapore Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK

Repetitive processes are a distinct class of 2D linear systems with applications in areas ranging from long-wall coal cutting and metal rolling operations through to iterative learning control schemes. The main feature which makes them distinct from other classes of 2D linear systems is that information propagation in one of the two independent directions only occurs over a finite duration. This, in turn, means that a distinct systems theory must be developed for them, which can then be translated into efficient routinely applicable controller design algorithms for applications domains. In this paper, we give the first significant results on a positive realness based approach to the analysis of these processes.

关键词： 2D linear systems repetitive processes positive realness

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MODEL REFERENCE PARAMETRIC ADAPTIVE ITERATIVE LEARNING control

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IFAC Proceedings Volumes 2002年第1期35卷 469-474页

作者： H. Yu M. Deng T.C. Yang D.H. Owens School of Engineering and Computer Science Exeter University Exeter EX4 4QF School of Engineering and Information Technology Sussex University Brighton BN1 9QT Department of Automatic Control and Systems Sheffield University Sheffield S1 3JD

Most of iterative learning control (ILC) methods requires that the relative degree of the plant is less than 2 for a linear system or the plant is passive for a non-linear system. A new model reference parametric adaptive iterative learning control using the command generator tracker (CGT) theory is proposed in this paper. The method can be applied to control a plant with a higher relative degree and it only requires to iteratively adjust n m + 2 parameters for an SISO plant. Therefore, the ILC control system is very simple. The proposed method is in the spirit of simple adaptive control which has received intensive researches during past two decades. Simulation results show the effectiveness and usefulness of the proposed method.

关键词： Iterative learning control Adaptive control Strictly positive real Model reference control

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L/sub 2/ anti-windup via receding horizon optimal control

L/sub 2/ anti-windup via receding horizon optimal control

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American control Conference (ACC)

作者： A. Bemporad A.R. Teel L. Zaccarian Dipartimento di Ingegneria dellE28099 Informazione University of Sienna Siena Italy Automatic Control Laboratory ETH Zurich Switzerland Department of Electrical and Computer Engineering University of California Santa Barbara CA USA Dipartimento di Informatica Sistemi e Produzione Uniiversity of Rome Rome Italy

The nonlinear L/sub 2/ anti-windup framework introduced by Teel and Kapoor (1997) reduces the anti-windup synthesis problem to a state feedback synthesis problem for linear systems with input saturation and input matched L/sub 2/ disturbances. In this paper, such a state feedback is synthesized using receding horizon optimal control techniques, and its equivalent piecewise affine closed-form is computed using the techniques of Bemporad et al. (2002). The properties of the resulting anti-windup compensation scheme are analyzed in the paper, and its performance is investigated through a simulation example.

关键词： Optimal control Roentgenium control systems Predictive models Predictive control Industrial control Sampling methods Constraint optimization Performance analysis Costs

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IMPROVED FEEDBACK CONSOLIDATION ALGORITHM FOR MULTICAST ABR CONNECTIONS IN ATM NETWORKS 14

IMPROVED FEEDBACK CONSOLIDATION ALGORITHM FOR MULTICAST ABR ...

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14th International Conference on computer Applications in Industry and engineering, CAINE 2001

作者： El-Sayed, Tamer M. El-Derini, Mohamed N. Selim, Mohamed S. Ahmed, Magdi A. Department of Computer Science and Automatic Control Faculty of Engineering University of Alexandria Egypt

ISBN: (纸本)9781618395344

A number of algorithms has been proposed for extending ABR congestion avoidance algorithms in ATM networks to perform feedback consolidation at the branch points of multicast connections. Schemes that attempt to maximize accuracy of feedback information tend to be slow in providing feedback to the source when the conditions in the network change. Accuracy can be traded for speed by having a switch generate feedback information before it has all the necessary information from downstream paths. This can cause consolidation noise, leading to a heavy rate at the source. In this paper, we propose improved algorithm for feedback consolidation, which combines benefits from the previous algorithms with reduced overhead. The performance of the proposed algorithm and a set of previously developed algorithms are compared under a variety of conditions. Results show that the proposed algorithm exhibits a fast transient response with accurate feedback and doesn't suffer from consolidation noise. © 2001 by the International Society for computers and Their Applications. All rights reserved.

关键词： Asynchronous transfer mode

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