Research on Adaptive Identification Systems to Estimate Dynamic Behaviors of Moving Objects

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In this research, we derived the adaptive parameter adjustment law to estimate and control of dynamic behavior of nonlinear systems. We used a dynamic error system which satisfied a Riccati equation instead of the Lurie' equations, and showed the boundedness of the error system using σ-modification-like parameter adjustment law. Using the proposed We desinged the fuzzy adaptive identifier for unknown stable plants with unknown input nonlinearities, and designed a fuzzy identifier and a controller for the ball-plate apparatus which has two inputs and two outputs. The ball-plate system is the educational kit produced by Tequipment Inc., which consists of a plate pivoted at its center such that the slope of the plate can be manipulated in two perpendicular directions and which has the intelligent vision system for measurement of a ball position. First, a nonlinear model, called the fuzzy approximator expanded by the fuzzy basis functions, of the ball-plate system is given. The obtained fuzzy model contains the product of the system parameters and regressor signals consist of the fuzzy basis functions. Next, to estimate the unknown system parameters in the fuzzy model, the linear identifier for plant parameters is added to the fuzzy identifier for input nonlinearities. Finally, the performance of the proposed fuzzy identifier is investigated by the MATLAB simulation and the experiment.