Optimizing control of over-actuated linear systems with nonlinear output maps via control Lyapunov functions

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 dynamic reference feedforward. 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.