| The thesis first gives an overall view of control theory development and elaborates the H Infinite Control Theory significance and it advantage to the control engineering, in which the status and signality of the control problem of large time-delay plant plays an important role. After the introducing of the H Infinite Control Theory history and it correlated concept and theorem, both with the analyzing of the previous work of time-delay system control strategy, we give an approximation of the pure delay unit in the system, and propose the problem of Model Matching in H Infinite Control Theory. Then transform the Model Matching problem to a NeharrI Problem, and present controller architecture with the solution for the Neharri problem, the simulation verified that the controller is effective and stable to be used in a large time-delay system. Afierwards~ on the synthesis of Standard H infinite control problem and the exact Modeling Matching problem, another new control strategy of Model Matching problem was proposed and illustrated with the example of typical industnal process, which is a one order time-delay plant, the result show it has better performance than some other design for the robust controller and the response can be very close to the given model.Secondly, the thesis also takes deep insig)lt into the Neuron Network technology, which is prevailed in the control-engineering field. A conclusion reduced from H infinite theory is presented and on the basis of it, the plant is predicted with the using of RBF neuron network, and an auto-adaptive PH) nerve-cell controller is used to accommodate time-varying plant. The result of experiments shows that this strategy has high quality in both the dynamic performance and stability precision, strong robustness as well. This new control strategy composed of robust control and neuron network presented us with a new idea in control of the large time-delay system, it has both the theoretical and the practical value. |
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