A robust model predictive control algorithm for incrementally conic uncertain/nonlinear systems

作者：Acikmese Behcet^*; Carson John M III; Bayard David S

来源：International Journal of Robust and Nonlinear Control, 2011, 21(5): 563-590.

DOI：10.1002/rnc.1613

• model predictive control
• robust control
• Lyapunov theory
• nonlinear systems
• uncertain systems
• linear matrix inequalities
• receding horizon control
• incrementally conic uncertainty

This paper presents a robustly stabilizing model predictive control algorithm for systems with incrementally conic uncertain/nonlinear terms and bounded disturbances. The resulting control input consists of feedforward and feedback components. The feedforward control generates a nominal trajectory from online solution of a finite-horizon constrained optimal control problem for a nominal system model. The feedback control policy is designed off-line by utilizing a model of the uncertainty/nonlinearity and establishes invariant 'state tubes' around the nominal system trajectories. The entire controller is shown to be robustly stabilizing with a region of attraction composed of the initial states for which the finite-horizon constrained optimal control problem is feasible for the nominal system. Synthesis of the feedback control policy involves solution of linear matrix inequalities. An illustrative numerical example is provided to demonstrate the control design and the resulting closed-loop system performance.

• 出版日期2011-3-25