On the computation of reference signal constraints for guaranteed tracking performance

Abstract

This paper concerns the problem of determining constraints on reference signals for tracking systems such that the tracking performance can be guaranteed within a specified tolerance for any reference signal satisfying the constraints. We first consider the problem of computing derivative constraints, which are linear constraints on the (vector-valued) reference signal and its time derivatives, and present an off-line algorithm for computing inner approximations to supremal derivative constraint sets based on the hyperplane method for generating inner and outer approximations to the reachable set of states for the controlled system. No simulation is required. We then consider planning problems in which a finite number of parameters are selected to generate the reference signal. The derivative constraints are mapped into this parameter space. The simplicial approximation method is proposed as a method for computing an approximation to the set of admissible parameters. The resulting (linear) parameter constraints characterize a class of reference signals which can be successfully executed by the tracking system, thereby permitting supervisory planning and control to be carried out in the reference signal parameter space without simulating detailed models of the underlying system dynamics. We illustrate the computational algorithm and the application of derivative and parameter constraints for the problem of generating trajectories for a two-axis computer numerical control (CNC) cutting tool.