A benchmark study of two self-organizing artificial neural network models, ART2 and DIGNET, is conducted. The architecture differences and learning procedures between these two models are compared. The performance of ...
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In this paper, an adaptive controller with improved transient and steady-state performance using parameter mismatch compensation and high-order tuning is presented. As in previous designs, the use of a properly design...
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The paper introduces a neural network-based model of logical connectives. The network consists of two types of generic OR and AND neurons structured into a three layer topology. The specificity of the logical connecti...
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In this paper, a new method for the computation of the optimal step in gradient algorithms for a class of linear quadratic optimal control problems is presented. This method improves the convergence of the gradient al...
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In this paper, a new method for the computation of the optimal step in gradient algorithms for a class of linear quadratic optimal control problems is presented. This method improves the convergence of the gradient algorithms and is optimal, i.e., it out performs any other step searching scheme in the above class of problems.
In this paper the Supervisory control Problem (SCP) for discrete event systems (DES) is generalized to a class of probabilistic discrete event systems (PDES). Necessary and sufficient conditions for the existence of a...
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In this paper the Supervisory control Problem (SCP) for discrete event systems (DES) is generalized to a class of probabilistic discrete event systems (PDES). Necessary and sufficient conditions for the existence of a solution to the probabilistic SCP for a class of nonterminating PDES are developed. Methods of representing probabilistic supervisors for PDES are described and the computation of supervisors is briefly discussed. Finally, we discuss how the results may be extended to terminating probabilistic languages.< >
作者：
P.C. BreedveldElectrical Engineering Department
Control Systems and Computer Engineering Group Control Laboratory and Mechatronics Research Centre Twente University of Twente Enschede Netherlands
The author identifies incentives for the use of computer-aids in modelling and design of physical systems and discusses possible solutions.
The author identifies incentives for the use of computer-aids in modelling and design of physical systems and discusses possible solutions.< >
This paper derives the tight upper bound on the number of stationary points that an nth order Hopfield network can have, and provides a characterization of synaptic sign patterns that allow a network to achieve this c...
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This paper derives the tight upper bound on the number of stationary points that an nth order Hopfield network can have, and provides a characterization of synaptic sign patterns that allow a network to achieve this capacity. We show that n/sup C//sub [/n/2] is the tight upper bound on the number of stationary points of an n-order Hopfield network. A simple graph theoretic characterization of the maximum capacity networks is given.< >
This paper is concerned with the design of a discrete time Model Reference Adaptive control System (WACS) for motion control under unknown nonlinear friction. Static and Coulomb friction forces are represented by a de...
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This paper is concerned with the design of a discrete time Model Reference Adaptive control System (WACS) for motion control under unknown nonlinear friction. Static and Coulomb friction forces are represented by a deadzone element for the input, which is active at low velocities. and disturbance. which may take different values depending on the motion direction. respectively. Then, the WAes for the nonlinear friction is a cascade combination of a nonlinear block which contains the deadzone and the disturbance term and a linear dynamic block. Experimental results from a rotary servo system demonstrate the effectiveness of the proposed WAeS
作者：
Daniel E. RiveraSaurabh BhatnagarDepartment of Chemical
Bio and Materials Engineering and Control Systems Engineering Laboratory Computer-Integrated Manufacturing Systems Research Center Arizona State University Tempe AZ USA
A novel technique for identifying reduced-order models in the closed-loop is presented. The method arrives at a process model and its corresponding compensator in an iterative fashion by introducing a series of step c...
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A novel technique for identifying reduced-order models in the closed-loop is presented. The method arrives at a process model and its corresponding compensator in an iterative fashion by introducing a series of step chan at the manipulated variable. The bias introduced into the identification data set by the closed-loop system, coupled with a control-relevant prefilter, yields a model whose corresponding control system improves its performance at every step. The method is appealing to chemical engineering practitioners because it combines the tasks of system identification with controller commissioning to produce a simple-to-use yet reliable autotuning procedure.
The problem of improved performance adaptive control (IPAC) of a class of linear and nonlinear systems is considered. A method for its solution is presented, the main feature of which lies in augmenting the "stan...
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The problem of improved performance adaptive control (IPAC) of a class of linear and nonlinear systems is considered. A method for its solution is presented, the main feature of which lies in augmenting the "standard" model reference adaptive controller by a properly designed signal compensating for the effect of plant parameter uncertainty on the output error. One of the main performance improvement characteristics of the proposed IPAC is that the zero-state output error can be made arbitrarily small under standard model reference adaptive control (MRAC) assumptions in the case of linear systems while a similar result holds for a class of linearizable systems as well. The exponential convergence of the output and parameter errors in the presence of sufficiently rich reference inputs, remains a valid property of this controller which also achieves improved robustness in the presence of bounded disturbances and/or unmodeled dynamics as well as in the case of an adaptation switch-off.
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