Dynamic programming based control for perturbed discrete time nonlinear systems

The work represents a dynamic programming and piecewise linearization based control strategy for a perturbed discrete-time nonlinear system. Firstly, the perturbed discrete-time nonlinear system is linearized at each sampling time. The origin system is approximated by infinite number of the linearized models. Then, the disturbances are estimated under the assumption of slow variations in input and state during a sampling period. Finally, a controller based on the dynamic programming method is designed. The proposed control strategy is applied to control a boiler-turbine system and compared to the other method with the usage of numerical simulation. The simulation results show that the proposed method gives better performance in term of overshoot and smoothness of control signals and it can be applied to other plants in industry.