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 adap...
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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.
This paper addresses the problem of implementing predictive controllers for supervisory level controlsystems. In this configuration the manipulated variables calculated by the Predictive controller are used as comman...
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This paper addresses the problem of implementing predictive controllers for supervisory level controlsystems. In this configuration the manipulated variables calculated by the Predictive controller are used as command signals for the Distributed controlsystems, which provide references to the operator-tuned local PID controllers that act on the physical system. This structure introduces the problem of loosing of performance if the inner-loop controllers are re-tuned. The paper discusses the solution to this problem based on the use of a two-degrees-of-freedom structure in the inner loop, that separates open and closed-loop properties. Both design guidelines and robustness issues are discussed.
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 featur...
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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.
Process models can be seen as structured knowledge base elements with syntax and semantics dictated by the underlying physical and chemical laws. The effect of model simplification assumptions is then determined by fo...
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The paper presents a number of image processing and pattern recognition applications using coordinate logic filters which execute coordinate logic operations among the pixels of the image. These filters are very effic...
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ISBN:
(纸本)9539676940
The paper presents a number of image processing and pattern recognition applications using coordinate logic filters which execute coordinate logic operations among the pixels of the image. These filters are very efficient in various 1D, 2D or higher-dimensional digital signal processing applications, such as noise removal, magnification, opening, closing, skeletonization, coding, edge detection, feature extraction, and fractal modeling. The key issue in the coordinate logic analysis of images is the method of fast successive filtering and managing of the residues. The desired processing is achieved by executing only direct logic operations among the pixels of the given image. Coordinate logic filters can be easily and quickly implemented using logic circuits or cellular automata; this is their primary advantage.
A causal iterative learning control algorithm based on optimal feedback and feedforward control is derived to provide perfect tracking of selected output values at specified times. Exponential convergence of the algor...
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The paper describes a game-theoretic framework and a computational algorithm for feasibility evaluation of automotive powertrains with storage elements in terms of fuel economy and emissions performance. The game-theo...
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The paper describes a game-theoretic framework and a computational algorithm for feasibility evaluation of automotive powertrains with storage elements in terms of fuel economy and emissions performance. The game-theoretic framework allows to handle various time-dependent uncertainties, including uncertainties in the drive cycle. In particular, an important issue in the prior approaches to this problem, the drive cycle dependence of the optimal policies, is alleviated. Within the basic framework, it is also possible to generate implementable operating policies that specify powsrtrain actuator settings as functions of engine operating conditions and states of the storage elements. We illustrate the procedure using an example poweitrain with a Direct Injection Stratified Charge engine and an aftertreatment system consisting of a Three Way Catalyst and a Lean NOx Trap.
Repetitive processes are a distinct class of 2D systems of both practical and theoretical interest. Their essential characteristic is repeated sweeps, termed passes, through a set of dynamics defined over a finite dur...
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We consider the iterative learning control problem from a 2D systems/adaptive control viewpoint. In particular, it is shown how some fundamental results from nonlinear adaptive control can be successfully applied in t...
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ISBN:
(纸本)0780366859
We consider the iterative learning control problem from a 2D systems/adaptive control viewpoint. In particular, it is shown how some fundamental results from nonlinear adaptive control can be successfully applied in the iterative learning control domain under very weak assumptions. Some areas for further research are also briefly discussed.
Differential linear repetitive processes are a distinct sub-class of 2D continuous-discrete linear systems which pose problems that cannot (except in a few very restrictive special cases) be solved by the direct appli...
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ISBN:
(纸本)0780370619
Differential linear repetitive processes are a distinct sub-class of 2D continuous-discrete linear systems which pose problems that cannot (except in a few very restrictive special cases) be solved by the direct application of standard (1D) systems theory and hence by the direct use of a large number of currently-available tools for computer-aided analysis/design. One such area is the construction of discrete approximations to their dynamics. In this paper, we investigate some problems which arise during the discretization of differential linear repetitive processes and develop solutions to them.
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