A switching control strategy for nonlinear systems under uncertainty

Nonlinear systems under uncertainty are difficult to regulate with guaranteed stability and optimality. This study presents a switching control strategy, which consists of robust control Lyapunov function-based predictive controller and approximate. dynamic programming-based controller. The former guarantees the robust stability within a level set, referred to as region of attraction (ROA). The latter improves optimality and reduces computational complexity in solving Bellman equation when the system is outside the ROA. The suggested approach is illustrated on a continuous stirred tank reactor example.