Simulation study demonstrates bounded tracking error in nonlinear MIMO systems, suggesting effective model-free adaptive control under milder stability conditions.
In this paper, the controller-based dynamic linearized model-free adaptive control method is proposed for a class of multi-input multi-output nonlinear discrete-time systems. This method is developed by using the full form dynamic linearization method to establish the data models and controllers with the Newton - Raphson optimization method for controller parameter estimation and with the modified projection algorithm for model parameter estimation. The stability analysis provides a theoretical guarantee that the proposed method has ultimate boundedness of tracking error with milder conditions compared to the existing works, which is accessed with the contraction mapping principle and Lyapunov theorem. The simulation of a vapor compression refrigeration system benchmark verifies the effectiveness of the proposed method.
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Yu et al. (2026) studied this question.
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