Stability Analysis of Multiobjective Robust Controller Employing Switching of Competitive Associative Nets

So far, we have developed a multiobjective robust controller using GPC (generalized predictive controller) and CAN2s (competitive associative neural nets) to learn and approximate Jacobian matrices of nonlinear dynamics of the plant to be controlled. Here, the CAN2 is an artificial neural net for learning efficient piecewise linear approximation of nonlinear function. In our previous studies, we have shown that the controller is capable of coping with the change of plant parameter values as well as the change of control objective by means of switching CAN2s. This paper examines the stability of the controller by means of using a linear plant to be controlled, and show the properties and the effectiveness of the present method.

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