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EXPERIMENTAL RESULTS ON ADAPTIVE NONLINEAR control AND INPUT PRESHAPING FOR MULTILINK FLEXIBLE MANIPULATORS

AUTOMATICA 1995年第1期31卷 83-97页

作者： KHORRAMI, F JAIN, S TZES, A School of Electrical Engineering and Computer Science Control/Robotics Research Laboratory (CRRL) Polytechnic University Brooklyn NY 11201 United States Department of Mechanical Engineering Control/Robotics Research Laboratory (CRRL) Polytechnic University Brooklyn NY 11201 United States

Adaptive input precompensators in conjunction with nonlinear controllers for multi-link flexible manipulators are considered in this paper. In an earlier paper, we had shown that application of a nonlinear inner-loop control reduces the variations in frequencies due to the geometrical configuration for multi-link flexible manipulators. This results in a better performance when input preshaping or any other controller based on a linear model is designed. To improve the performance of the system to parameter variations (e.g. changes in payload), an adaptive version of the advocated controller is utilized. This is achieved by estimating the time of application of the impulses for on-line preshaping and in the case of payload uncertainty, estimation of the payload and real-time adjustment of the nonlinear inner-loop based controller. Frequency domain Time-Varying Transfer Function Estimate (TTFE) and Empirical Transfer Function Estimate (ETFE) system identification algorithms are proposed for estimation of vibrational modes and unknown payload. Experimental results on a two-link flexible manipulator with adaptive nonlinear control and preshaping are provided to show the effectiveness of the advocated controllers. Overall, the present paper completely generalizes the adaptive input preshaping technique for multi-link flexible manipulators.

关键词： FLEXIBLE MANIPULATORS VIBRATION DAMPING NONLINEAR control INPUT PRESHAPING IDENTIFICATION ADAPTIVE control

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SCHEDULING DEPENDENT TASKS ON IDENTICAL MACHINES USING A NOVEL HEURISTIC CRITERION - A ROBOTIC COMPUTATION EXAMPLE

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 1995年第3期12卷 229-237页

作者： TZAFESTAS, S TRIANTAFYLLAKIS, A RIZOS, G Intelligent Robotics and Control Unit Department of Electrical and Computer Engineering National Technical University of Athens Zografou Greece

The problem of scheduling n dependent tasks, with arbitrary processing times, on m identical machines so as to minimize the makespan criterion is considered. Since this problem is NP-hard in the strong sense, it can be solved only suboptimally using heuristic approaches. Two new heuristic algorithms (dispatching rules), namely MVT/MISF acid DMVT/MISF algorithms, for this problem are proposed. These algorithms are then used, together with the existing ones CP/MISF and DHLF/MISF, as a dispatching rule base of a new adaptively weighted combinatorial dispatching (AWCD) rule. This combinatorial dispatching rule has a superior behaviour compared to simple dispatching rules. Extended experimentation with these algorithms supports this argument. Here a representative robotic dynamics computation example is included. In addition, some empirical rules are derived and proposed for the selection of a simple dispatching rule (heuristic) if such a selection is required, for each particular input data set. These methods, as well as the existing optimal algorithms for special solvable cases of the considered problem, have been integrated in a decision support system (DSS).

关键词： SCHEDULING PROBLEMS DISPATCHING RULES HEURISTIC ALGORITHMS DEPENDENT TASKS MAKESPAN CRITERION LIST SCHEDULING ALGORITHMS

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AN IMPLEMENTATION OF FAST GLOBALLY-STABLE ADAPTIVE ROBOT control ON A MULTIPROCESSOR NETWORK

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control engineering PRACTICE 1995年第11期3卷 1553-1562页

作者： ZIAUDDIN, SM ZALZALA, AMS Department of Automatic Control and Systems Engineering Robotics Research Group University of Sheffield Mappin Street Sheffield Sl 4DU UK

This paper is concerned with efficient and fast computations of adaptive control algorithms for robot manipulators. Adaptive controllers employing the highly coupled and non-linear dynamics of manipulators are computationally complex, which presents a major obstacle in their real-time implementation for industrial applications. A solution to this problem is suggested by utilising a parallel-processing approach. The controller algorithm is implemented for a robot manipulator with six degrees of freedom, utilising a transputer network, for which programming is performed in C. The execution times achieved by the distributed algorithm are well within the limit acceptable for real-time control.

关键词： ADAPTIVE control ROBOTIC MANIPULATORS GLOBAL STABILITY PARALLEL PROCESSING MULTIPROCESSORS

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Transputer control System with a GAs Motion Planner for the PUMA560 Industrial Robotic Manipulator

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IFAC Proceedings Volumes 1995年第22期28卷 77-82页

作者： Q. Wang A.M.S. Zalzala Robotics Research Group Department of Automatic Control & Systems Engineering University of Sheffield Mappin Street Sheffield SI 3JD UK

This paper describes a new control system for the PUMA 560 industrial robotic manipulator based on transputer networks, where both the hardware and software designs are detailed. A Transputer Interface Board (ТIB) establishing a transputer link to the 6503 microprocessors of the PUMA arm joints has been designed, built and tested. In addition to hardware implementation, software testing for this new system has been successfully accomplished. A great deal of flexibility can be achieved with this new system, yet without many difficulties, where it can be used as a platform to implement advanced control algorithms and develop sensor-based intelligent robotic structures which need much more computational power. Genetic Algorithms are used to plan the PUMA robot motion trajectory based on the new PUMA control platform, and the motion planner runs concurrently with the controller. Real-time experiments show that PUMA moves much more smoothly along the optimum planned trajectory.

关键词： Robot control Motion Planning Genetic Algorithms (GAs) Distributed control Interfaces

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Decentralized adaptive output feedback control of large scale interconnected nonlinear systems

Decentralized adaptive output feedback control of large scal...

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American control Conference (ACC)

作者： S. Jain F. Khorrami Control/Robotics Research Laboratory CRRL Department of Electrical Engineering Polytechnic University Brooklyn NY USA

In this paper, we present a global, decentralized adaptive design procedure for a class of large scale nonlinear systems, which utilizes only local output feedback. The advocated scheme guarantees robustness to parametric and dynamic uncertainties in the interconnections, and also rejects any bounded disturbances entering the system. The uncertainties are assumed to be bounded by an unknown pth order polynomial in the outputs. The resulting controller maintains global uniform boundedness of all signals of the closed-loop system with good robustness and disturbance rejection properties.

关键词： Programmable control Adaptive control Output feedback Large-scale systems Uncertainty Nonlinear systems Robustness Nonlinear dynamical systems Polynomials control systems

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An ANDECS-MATLAB Multicriteria Design for a Maglev Vehicle Comparing a ’Classical’ and a ’Modern’ control Structure

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IFAC Proceedings Volumes 1995年第23期28卷 113-118页

作者： J. Bals J.E. Paddison DLR-Oberpfaffenhofen Control Design Engineering Institute for Robotics & System Dynamics D-82230 Wessling Germany Loughborough University of Technology Department of Electronic and Electrical Engineering Loughborough UK

For a low speed Maglev system of the single stage suspension type a control design study is described where a ’classical’ dynamic compensator control structure is compared with a ’modern’ LQG control structure. To properly tune the free parameters in the respective controller synthesis procedures the ANDECS-MATLAB design environment is used. The multi-objective design approach of ANDECS allows to simultaneously satisfy the suspension requirements corresponding to both random and deterministic inputs.

关键词： Computer-Aided Multi-Objective Design Magnetic Suspension Transportation

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Neural networks in robotics: state of the art

Neural networks in robotics: state of the art

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： S.G. Tzafestas Intelligent Robotics and Control Unit Department of Electrical and Computer Engineering National and Technical University of Athens Athens Greece

This paper provides a short review of the neural network approach to system control with reference to robotic systems. Starting with an exposition of the main neurocontrol architectures, the paper overviews the literature on the application of neural networks to robot kinematics, dynamics, path planning and motion control, including some work on neurofuzzy control. To appreciate better robot neurocontrol, an unsupervised robot neurocontroller is presented in some detail. The paper includes a discussion of the criticism made to the neural control paradigms, and an outline of some interesting areas for further research.

关键词： Neural networks Intelligent networks control systems Automatic control Biological neural networks Neurons Intelligent robots Adaptive control Neurocontrollers Humans

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Global decentralized adaptive control for large scale nonlinear systems without strict matching

Global decentralized adaptive control for large scale nonlin...

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American control Conference (ACC)

作者： S. Jain F. Khorrami Control/Robotics Research Laboratory Department of Electrical Engineering Polytechnic University Five Metrotech Center Brooklyn NY USA

Decentralized adaptive control design is developed for a class of large-scale interconnected nonlinear systems which do not satisfy the strict matching restriction. To this end, large-scale nonlinear systems transformable to the decentralized strict feedback form are considered. The interconnections are assumed to be bounded by unknown polynomials in states. The controller maintains a global uniform boundedness of the model reference tracking error to a compact set which can be made arbitrarily small based on appropriate choice of control gains. In the regulation case, global asymptotic performance is achieved.

关键词： Adaptive control Large-scale systems Nonlinear systems control systems Feedback Polynomials Nonlinear control systems Programmable control Robot control Laboratories

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Robust adaptive control of a class of nonlinear systems: state and output feedback

Robust adaptive control of a class of nonlinear systems: sta...

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American control Conference (ACC)

作者： S. Jain F. Khorrami Control/Robotics Research Laboratory Department of Electrical Engineering Polytechnic University Five Metrotech Center Brooklyn NY USA

A new adaptive design procedure is presented which guarantees robustness to parametric and dynamic uncertainties for a class of nonlinear systems, and also rejects any bounded, unmeasurable disturbances entering the system. The uncertainties in the system are assumed to be unknown, except that they are bounded by an unknown pth order polynomial; in the arguments. For the state feedback case, we identify systems transformable to a special strict feedback form. For the case, where only the outputs are measured, the adaptive design procedure applies to systems transformable to the output feedback form, where the output dependent nonlinear terms are unknown. Results in both cases are presented for state-output tracking and regulation problems.

关键词： Robust control Adaptive control Nonlinear systems Output feedback State feedback Uncertainty control systems Nonlinear dynamical systems Polynomials Error correction

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Implementation of real time spatial mapping in robotic systems through self-organizing neural networks

Implementation of real time spatial mapping in robotic syste...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： V. Morellas J. Minners M. Donath Robotics Laboratory Department of Mechanical Engineering and the Center for Advanced Manufacturing Design and Control University of Minnesota Minneapolis MN USA

Presents a methodology which allows an autonomous agent i.e., a mobile robot, to learn and build maps of its operating environment by relying only on its range sensors. The maps, described with respect to the robot's inertial frame, are developed in real time by correlating robot position and sensory data. This latter feature characterizes part of the uniqueness of the authors' approach. These maps are topologically isomorphic to the maps created for the same room(s) by humans. The methodology exploits the principle of self-organization, implemented as an artificial neural network module which processes incoming sensor range data. The generation of environmental maps can be visualized as an elastic string of neurons whereby every neuron represents a finite portion of the physical world. This elastic string stretches dynamically so as to take on the shape of the environment, a unique characteristic of the authors' methodology. In this respect, the neural net provides a discretized representation of the "continuous" physical environment as the latter is seen through the robot's own sensors. Experiments, focused on indoor applications, have successfully demonstrated the ability of a robot to build maps of geometrically complex environments. The results presented in this paper, compared with the authors' earlier efforts, show significant improvement in that every single sensor data point contributes equally to the location of the neurons of the spatial map at the end of the learning process. This is important because the authors wish to minimize the effect of the order in which data points are processed.

关键词： Real time systems Robot sensing systems Sensor phenomena and characterization Neurons Autonomous agents Mobile robots Humans Artificial neural networks Data visualization Shape

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