MODEL PREDICTIVE CONTROL OF LINEAR SYSTEMS SUBJECT TO ACTUATOR DEGRADATION

The degradation of physical components in engineering systems is generally unavoidable, in view of factors such as wear due to usage, aging of the materials and hostile environmental conditions. In particular, the degradation of actuators in a closed-loop control system can lead to poor performance and, in extreme cases, loss of controllability. In this context, it may be interesting to design controllers that can exploit the available knowledge on the degradation dynamics to maintain adequate performance and extend the useful life of the actuators. The present work is concerned with cases in which the degradation rate depends on the exerted control effort. It is shown that the loss of actuator effectiveness can be taken into account by using an augmented design model of the bilinear type. A model predictive controller (MPC) can then be implemented by using suitable optimization algorithms that can handle quadratic costs subject to bilinear constraints. A simulated example is presented to illustrate some of the salient advantages of the proposed method. The results obtained by using the proposed MPC are compared to those of a standard MPC formulation, as well as an MPC with model parameters updated at each sample time according to the degradation state of the actuator.