Multi-objective nonlinear predictive control of process systems: A dual-mode tracking control approach. (January 2015) - He, Defeng
Highlights: Design a multi-objective dual-mode NMPC of nonlinear processes with multiple conflicting objectives and constraints on the state and control. Both the correction and the terminal law in the proposed NMPC are computed online via the same cost functions. The closed-loop stability of the proposed NMPC is guaranteed by using a terminal region and the dual-mode control principle. The proposed NMPC does not require computing the Pareto front and subjectively selecting the weighting factors. Abstract: There typically exist different and often conflicting control objectives, e.g., reference tracking, robustness and economic performance, in many chemical processes. The current work considers the multi-objective control problems of continuous-time nonlinear systems subject to state and input constraints and multiple conflicting objectives. We propose a new multi-objective nonlinear model predictive control (NMPC) design within the dual-mode paradigm, which guarantees stability and constraint satisfaction. The notions of utopia point and compromise solution are used to reconcile the confliction of the multiple objectives. The designed controller minimizes the distance of its cost vector to a vector of independently minimized objectives, i.e., the steady-state utopia point. Recursive feasibility is established via a particular terminal region formulation while stabilizing the closed-loop system to the compromise solution via the dual-mode control principle. In order to derive the terminal region as large as possible, a terminal control law with free-parameters is constructed by using the control Lyapunov functions (CLFs) technique. Two examples of multi-objective control of a CSTR and a free-radical polymerization process are used to illustrate the effectiveness of the new multi-objective NMPC and to compare their performance.