STUDY ON OPTIMIZATION AND INTELLECTUALIZATION OF NONLINEAR ROBUST ADAPTIVE CONTROL

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(1) Design methods of adaptive control systems with uncertain relative degrees and unknown degrees were studied. Adaptive stabilizing control systems, model reference adaptive control systems and adaptive servo control systems for processes with such uncertainties are constructed in the proposed control schemes. The related references are I), 3), 5), 7), 8), 15) and 17).(2) A design method of new simple adaptive control systems was considered. It was shown that the proposed design method can be easily applied to general relative degree cases by utilizing high-gain observers with same dimensions as relative degrees, and that the robustness of the proposed adaptive control systems is also assured for small unstructured uncertainties. The related references are 6) and 12).(3) New classes of adaptive controllers which are optimal or sub-optimal to some meaningful cost functionals, were derived. Adaptive H2 or HOO optimal (sub-optimal) control systems are constructed for general class of ad … More aptive control problems. The related references are 2), 9), 10), 11) and 21). Next, those approaches were applied to the design of adaptive nonlinear HOO control systerns for time-varying processes. The new control schemes are derived as solutions of particular nonlinear HOO control problems, where unknown system parameters are regarded as exogenous disturbances to the processes, and thus the resulting control systems are bounded for arbitrarily large but bounded variations of time-varying parameters. The related references are 13), 14), 16), 1 8), 20) and 24). The adaptive optimal control strategies were also applied to the design of adaptive nonlinear Hcocontrol systems with neural networks (NN). Those control schemes are derived as solutions of particular nonlinear Hco control problems, where unknown system parameters and modeling errors in NN approximators are regarded as exogenous disturbances to the processes. The resulting control systems are bounded for arbitrarily large but bounded variations of time-varying parameters and modeling errors in NN approximators. The related reference is 22).(4) Adaptive gain-scheduled HOO controb schemes of linear parameter-varying (LPV) systems are developed. In the proposed adaptive schemes, the estimates of unknown scheduled parameters are obtained successively, and the current estimates are fed to the controllers to stabilize the plants and to attain HOO control performance adaptively. Stability analysis of the adaptive control systems is carried out by utilizing Lyapunov approaches based on linear matrix inequalities in the bounded real lemma. The related reference is 23).(5) Design methods of adaptive or nonlinear control systems for bilinear processes were obtained, parts of which were applied to the design of semi-active suspension systems in real vehicles. The related references are 4) and 19). Less