不确定非线性离散系统的自适应模糊优化控制与应用
发布时间：2019-02-24 15:57
【摘要】：最优控制是目前非线性控制理论的研究热点和难点问题，为此，本文针对非线性离散系统，提出的自适应模糊控制方法不仅对于处理系统的不确定性更加有效，而且改进了系统的控制性能。通过利用优化控制方法和引入的性能指标函数，使得控制成本达到最小，进而实现最优控制。本论文主要做了以下三方面的工作： （1）针对一类包含了未知函数和非对称死区的非线性离散系统，提出了一种自适应模糊优化控制算法。模糊逻辑系统用于逼近系统中的未知函数。基于强化学习和backstepping算法，设计控制器使得性能指标函数达到最小，从而实现优化控制的目的。设计自适应辅助信号来处理死区带来的影响，再利用梯度下降规则求得自适应律。最后，根据李雅普诺夫稳定性定理，证明了该闭环系统的所有信号的有界性。仿真实例验证了所提出控制算法的可行性。 （2）基于带有滤波跟踪误差的直接启发式动态规划方法，解决了Henon映射混沌系统的最优跟踪控制问题。其中模糊逻辑系统用于逼近效用函数，较之前的工作，减少了控制器的成本。最后，依据李雅普诺夫函数分析方法，确保了系统的稳定性，同时，证明了跟踪误差、自适应律和控制输入的有界性。仿真结果证明了设计方法的有效性。 （3）研究了离散的六阶感应电动机模型的自适应跟踪控制问题。在设计过程中，充分利用了模糊逻辑系统的逼近性能，且较之前的控制，提出了仅需较少设计参数的自适应方案，减少了计算量。在李雅普诺夫意义下，，保证了被控系统的所有信号半全局一致最终有界，且跟踪误差收敛到零的一个小领域内。仿真结果进一步说明了提出方法的实用性。
[Abstract]:Optimal control is a hot and difficult problem in nonlinear control theory. For this reason, the adaptive fuzzy control method proposed in this paper is not only more effective to deal with the uncertainty of the system, but also to solve the problem of nonlinear discrete systems. Moreover, the control performance of the system is improved. By using the optimal control method and the introduced performance index function, the control cost is minimized and the optimal control is realized. The main contributions of this thesis are as follows: (1) an adaptive fuzzy optimal control algorithm is proposed for a class of nonlinear discrete systems with unknown functions and asymmetric dead zones. Fuzzy logic systems are used to approximate unknown functions in the system. Based on reinforcement learning and backstepping algorithm, the controller is designed to minimize the performance index function, so as to achieve the purpose of optimal control. The adaptive auxiliary signal is designed to deal with the influence of dead zone, and the adaptive law is obtained by using gradient descent rule. Finally, according to Lyapunov stability theorem, the boundedness of all signals of the closed-loop system is proved. A simulation example is given to verify the feasibility of the proposed control algorithm. (2) based on the direct heuristic dynamic programming method with filter tracking error, the optimal tracking control problem of Henon mapping chaotic system is solved. The fuzzy logic system is used to approximate utility function, which reduces the cost of controller. Finally, according to the Lyapunov function analysis method, the stability of the system is ensured. At the same time, the boundedness of tracking error, adaptive law and control input is proved. Simulation results show the effectiveness of the design method. (3) the adaptive tracking control problem of discrete sixth order induction motor model is studied. In the design process, the approximation performance of the fuzzy logic system is fully utilized, and compared with the previous control, an adaptive scheme with less design parameters is proposed, which reduces the calculation cost. In the sense of Lyapunov, all the signals of the controlled system are guaranteed to be semi-globally uniformly bounded, and the tracking error converges to a small field of zero. The simulation results further demonstrate the practicability of the proposed method.
【学位授予单位】：辽宁工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：O232
本文编号：2429699
[Abstract]:Optimal control is a hot and difficult problem in nonlinear control theory. For this reason, the adaptive fuzzy control method proposed in this paper is not only more effective to deal with the uncertainty of the system, but also to solve the problem of nonlinear discrete systems. Moreover, the control performance of the system is improved. By using the optimal control method and the introduced performance index function, the control cost is minimized and the optimal control is realized. The main contributions of this thesis are as follows: (1) an adaptive fuzzy optimal control algorithm is proposed for a class of nonlinear discrete systems with unknown functions and asymmetric dead zones. Fuzzy logic systems are used to approximate unknown functions in the system. Based on reinforcement learning and backstepping algorithm, the controller is designed to minimize the performance index function, so as to achieve the purpose of optimal control. The adaptive auxiliary signal is designed to deal with the influence of dead zone, and the adaptive law is obtained by using gradient descent rule. Finally, according to Lyapunov stability theorem, the boundedness of all signals of the closed-loop system is proved. A simulation example is given to verify the feasibility of the proposed control algorithm. (2) based on the direct heuristic dynamic programming method with filter tracking error, the optimal tracking control problem of Henon mapping chaotic system is solved. The fuzzy logic system is used to approximate utility function, which reduces the cost of controller. Finally, according to the Lyapunov function analysis method, the stability of the system is ensured. At the same time, the boundedness of tracking error, adaptive law and control input is proved. Simulation results show the effectiveness of the design method. (3) the adaptive tracking control problem of discrete sixth order induction motor model is studied. In the design process, the approximation performance of the fuzzy logic system is fully utilized, and compared with the previous control, an adaptive scheme with less design parameters is proposed, which reduces the calculation cost. In the sense of Lyapunov, all the signals of the controlled system are guaranteed to be semi-globally uniformly bounded, and the tracking error converges to a small field of zero. The simulation results further demonstrate the practicability of the proposed method.
【学位授予单位】：辽宁工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：O232
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相关期刊论文 前3条
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2 LIU YanJun;LIU Lei;TONG ShaoCheng;;Adaptive neural network tracking design for a class of uncertain nonlinear discrete-time systems with dead-zone[J];Science China(Information Sciences);2014年03期
3 LI DongJuan;;Adaptive neural network control for a class of continuous stirred tank reactor systems[J];Science China(Information Sciences);2014年10期
本文编号：2429699
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