Optimizing Control of Over-Actuated Linear Systems With

Over-actuated linear systems with nonlinear output maps are studied, taking into account input and state constraints. Using a control Lyapunov function approach, we develop an optimizing dynamic controller that includes a reference feed-forward that cancels the transients due to the optimizer dynamics. This allows optimizing control to be implemented with low real-time computational complexity since the optimization algorithm converges only asymptotically. Conditions for local convergence and global asymptotic stability are established. A highly nonlinear colorant mixing simulation example is used to illustrate the approach