MRAC-Based Adaptive Feedback Linearization Control Method for Continuous-Time Nonlinear Systems with Uncertain Parameters

The feedback linearization method can accurately linearize the nonlinear system. However, feedback linearization needs the exact dynamic of nonlinear systems, it is difficult to apply to unknown nonlinear systems. To be capable to perform the feedback linearization of the continuous-time nonlinear system containing uncertain parameters, a model reference adaptive control (MRAC) scheme is introduced in this paper. First, we construct a state feedback controller by the knowledge of the system model structure and form it into an adjustable system together with the nonlinear object. The reference model is decided upon to be a standard linear system. Second, based on the output errors of reference model and adjustable system, we adaptively modify the state feedback controller’s unknown parameters using the gradient descent approach. Finally, the simulations and real-world experiments on a first-order inverted pendulum system are carried out to assess the effectiveness of given methods.