A control systems engineering approach, employing a two-level overall system architecture and different but compatible formalisms for system representation on the upper and lower levels, has been investigated in detai...
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A control systems engineering approach, employing a two-level overall system architecture and different but compatible formalisms for system representation on the upper and lower levels, has been investigated in detail. One design alternative is based on employing fuzzy-system approximators and solving for the adaptive tracking of the given, arbitrary, desired system outputs. The other alternative is based on state equations of composite systems and the use of neural-network approximators to deal with uncertainties and control adaptation. In both alternatives similarity property of subsystems has been exploited. Both designs can be implemented within the standard computer process control technology, and are therefore believed to be promising in applied systems engineering.
Decision support system described here makes it possible to carry out multicriterial selection of hundreds of projects simultaneously, with tens of criterion functions with bivalent variables including polynomial ones...
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One of the basic issues in the navigation of autonomous mobile robots is the obstacle avoidance task that is commonly achieved using a reactive control paradigm where a local mapping from perceived states to actions i...
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One of the basic issues in the navigation of autonomous mobile robots is the obstacle avoidance task that is commonly achieved using a reactive control paradigm where a local mapping from perceived states to actions is acquired. A control strategy with learning capabilities in an unknown environment can be obtained using reinforcement learning where the learning agent is given only sparse reward information. This credit assignment problem includes both temporal and structural aspects. While the temporal credit assignment problem is solved using core elements of the reinforcement learning agent, solution of the structural credit assignment problem requires an appropriate internal state space representation of the environment. In this paper, a discrete coding of the input space using a neural network structure is presented as opposed to the commonly used continuous internal representation. This enables a faster and more efficient convergence of the reinforcement learning process.
In this paper, the design of available bit rate (ABR) congestion control in ATM (asynchronous transfer mode) networks is considered. The goals of congestion control are high link utilization, low cell loss, and low ne...
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In this paper, the design of available bit rate (ABR) congestion control in ATM (asynchronous transfer mode) networks is considered. The goals of congestion control are high link utilization, low cell loss, and low network delay. Various algorithms for congestion control can be found in the literature. Most of them are based on a network model, which is assumed to be known. In this paper a recursive least square (RLS) algorithm for on-line identification of the network model is implemented and combined with a generalized predictive controller (GPC) and with an I-controller based on the Smith predictor. Simulations were carried out to prove the effectiveness of the proposed algorithms.
In this paper, a global variable structure relay control scheme with finite time convergence is proposed for multi-link rigid robotic manipulator systems with uncertain dynamics. For general finite time variable struc...
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A laboratory model for experimental investigations of the rubber-asphalt sliding pair has been designed with the purpose of better understanding of dynamic behavior of the friction force in the contact patch between t...
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The current lack of manufacturing techniques for very high volume handling of small objects presents a technology barrier to the commercial success in various fields like micro electromechanical systems (MEMS). A fund...
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This work presents dominant pole design (DPD) methodology, one MATLAB implementation of DPD and its usage. DPD for PI and PID controllers is derived, and on this basis MATLAB toolkit for three-pole method (3PM) has be...
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This work presents dominant pole design (DPD) methodology, one MATLAB implementation of DPD and its usage. DPD for PI and PID controllers is derived, and on this basis MATLAB toolkit for three-pole method (3PM) has been developed. The least squares procedure for finding functional dependence of PID controller parameters on process parameters is described. This least squares procedure has been applied to the first order process with dead time (FODT) obtained functional dependence, expressed through tuning formulas, is presented. Performance of PID controller tuned with 3PM tuning formulas is compared to the performance of PID controller tuned with integral criteria derived tuning formulas. Observed characteristics of DPD method are given at the end of the paper.
This paper attempts to look at the fundamental problem of fault detection and isolation (FDI) in nonlinear systems. Using the idea of input reconstruction by means of dynamic inversion the authors first discuss the pr...
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In this paper, the problems of isomorphic decomposition and controllability of a class of nonlinear systems possessing symmetries, on the basis of quotient systems, is studied. The isomorphic decomposition formations ...
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In this paper, the problems of isomorphic decomposition and controllability of a class of nonlinear systems possessing symmetries, on the basis of quotient systems, is studied. The isomorphic decomposition formations of these systems are derived. Finally, it is shown that controllability of the original systems can be determined by that of the subsystems, which are obtained through isomorphic decomposition. The corresponding sufficient and necessary conditions are given. Two new theoretical results have been proved.
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