| 英文摘要 | As is well known, there are demands for nonlinear optimal controller designs in many real world applications. Therefore, adaptive dynamic programming (ADP), as a new paradigm for approximately solving the optimal control problem of nonlinear systems, has gained much attention from a lot of researchers. Adaptive dynamic programming, combining with neural networks, can effectively avoid the “curse of dimensionality”, and meanwhile obtain the approximate optimal closed-loop feedback control law. However, the architecture of ADP approach is far from perfect. Many theoretical and technical issues of optimal control for nonlinear systems based on ADP have yet to be addressed. In this dissertation, based on ADP, in the presence of external disturbance and unknown mathematical model, optimal tracking control problems are investigated for nonlinear systems. Furthermore, a neural network (NN) based ADP approach is applied to solve the optimal temperature control problem of the water-gas shift (WGS) process. The main contributions of the dissertation can be briefly described as follows: 1. Propose a novel optimal tracking controller design scheme for aclass of unknown discrete-time (DT) nonlinear systems by using greedy iterative heuristic dynamic programming (HDP) algorithm. First, in order to obtain the dynamics of nonlinear system, an identifier is constructed by a three-layer feedforward NN. Second, a feedforward controller is designed to get the steady control input of the system. Third, via system transformation, the original tracking problem is transformed into an optimal regulation problem with respect to the state tracking error. Then, the greedy iterative HDP algorithm is introduced to deal with the regulation problem with convergence analysis. Finally, simulation results are also presented to demonstrate the effectiveness of the proposed scheme. 2. In the presence of external disturbance, a nearly H∞ optimal tracking control scheme based on generalized Hamilton-Jacobi-Isaacs (GHJI) is developed for affine DT nonlinear systems. First, via system transformation, the original tracking problem is transformed into an optimal regulation problem with respect to the state tracking error. Second, with regard to the converted regulation problem, the corresponding GHJI equation is formulated, and then the L2-gain analysis of the closed-loop nonlinear system are employed. Third, a nearly optimal iterative algorithm based on the game theoretic interpretation of ... |
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