Dual control strategy based on receding horizon
基于滚动优化的对偶控制策略

The control of a stochastic system with unknown parameter was considered.A novel dual control algorithm based on receding horizon was proposed.In dynamic programming functional equation,the Kalman fliter is used to estimate the state of such system,and the linearization method is applied to approximate the nonlinear cost-to-go function with respect to posterior probabilities,the receding horizon strategy is then proposed to decouple the coupling relation between control and learning.Thus,the explicit recursive expression of the original unsolvable functional equation and a control law with easy implementation are obtained.The performance of the control law derived in this paper is also illustrated with an example.The simulation results show that the control law with dual property can achieve preferable compromise between learning and control.