In this paper, a new ultra-local model control approach is proposed. The concept is based on the linear adaptive observer to estimate the ultra-local model parameters instead of algebraic derivation technique. The importance of adaptive observer is deduced in the join estimation of state and unknown parameters of parametric systems. The closedloop control is implemented via an adaptive PID controller to reject disturbances due to exogenous parameter uncertainties. In this paper, a performance comparison between the adaptive observer based method and the algebraic derivation technique is developed to show the efficiency of the proposed control strategy. The approaches are applied to a two-tank system for the water level control. Several successful simulation results are shown to demonstrate the effectiveness of the proposed controller.
This paper deals with the design of an ultralocal model control. The proposed approach is based on the estimation of the ultra-local model parameters using least squares resolution technique instead of numerical derivation technique. The closed-loop control is implemented through an adaptive PI in order to reject the influences of the disturbance and noise output signais. Its main advantages are: its simplicity and its robustness with respect to the parameter uncertainties of system. In this paper, it is processed to test the efficiency of the parameter estimation method compared with the performance of numerical derivation technique. The method is applied to the water level control of a two-tank-system. Numerical simulations show that the generated desired trajectory is followed in an efficient way even with severe operating conditions.
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