STABILIZING PROPERTIES OF CONSTRAINED PREDICTIVE CONTROL

Standard GPC and CRHPC stability results have traditionally been deriv ed in the state-space, using the properties of the solution of the Ric cati equation associated with the control law. Unfortunately this type of study does not readily extend to constrained control laws which ar e nonlinear. By invoking the monotonicity, with respect to time, of th e receding-horizon cost function, however, an extension of the stabili ty properties of a subclass of GPC, termed GPC(infinity), and of CRHPC may be obtained, when inequality constraints are added to the control objective. The problem of feasibility (i.e. the compatibility of the constraints) is also becoming a major area of interest in predictive c ontrol. In GPC(infinity) and CRHPC, the feasibility problem is compoun ded by the use of endpoint equality constraints on the tracking error. A new concept called setpoint conditioning is introduced here, which may be used to resolve the incompatibilities between the inequality an d the end-point equality constraints, without compromising stability.