A robust human-imitating intelligent control was proposed for nonlinear systems. Firstly, a human-imitating qualitative control law was developed through the analyses of the physical model of the plant. The qualitative control law was quantified by some method of parameter-optimization based on the nominal model of the plant. Then, on the basis of the developed human-imitating controller, a robust compensator was proposed to overcome the bad influences resulted from modeling errors, unmodeled dynamics and disturbances. The compensator was derived by Lyapunov stability theory, thus the stability of the closed-loop system was guaranteed. However, the specified Lyapunov function usually essential in a common Lyapunov-based approach was not needed during the design ofthe robust compensator, as a result, the difficulties in designing the Lyapunov function for a nonlinear system was conquered. Applying the proposed scheme to control a double inverted pendulum, the results of experiment verify the validity of this design.
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