Model-free Periodic Adaptive Control for a Class of Nonlinear and Non-affine Discrete-Time Systems

摘要

In this paper,by introducing the concept of PPD,we give a new dynamical linearization method and present a new model-free periodic adaptive control approach for a class of general nonlinear and non-affine discrete-time systems.The only prior knowledge is that the given trajectory is periodic with a known period and the controller design and convergence analysis only depends on the I/O data of the dynamical system.In other words,we can easily select the control parameters without requiring any other knowledge of the control system.The model-free periodic adaptive control updates the PPD values and control signal periodically in a pointwise manner over one entire period by the PPD estimate values and the I/O data of the preceding period,instead of the preceding time instance,in the sequel achieves the geometrical tracking convergence.A simulation example illustrates the feasibility and effectiveness of the proposed method.