Dependable model predictive control for reliable constrained systems

Abstract

The task of managing duty-standby predictive controllers in dependable control system for high-integrity applications is challenging owing to the output and input constraints on the multivariable systems. A novel synchronization method for redundant multivariable controllers applying the incremental dissipativity and the asymptotically positive-realness incremental-constraint (APRiC) is presented in this paper. As an alternative to the control summation in classical reliable control systems, only one scalar variable, which is the calculated supply rate, is exchanged among the member controllers. A dissipation-based quadratic constraint with respect to the control and output increments is developed from the APRiC for the redundant controllers in this approach. The APRiC is transformed into a quadratic constraint on the control vector, which is then imposed on the MPC optimization as a stability constraint. When a failure is detected, the stability constraint of the standby controller will be activated from the lower bound of the supply rate being transferred from the duty controller. The system is stabilized and dependable by the operations of such decentralized duty and standby architecture.