發(fā)布時間：2019-02-24 15:57

【摘要】：最優(yōu)控制是目前非線性控制理論的研究熱點和難點問題，為此，本文針對非線性離散系統(tǒng)，提出的自適應模糊控制方法不僅對于處理系統(tǒng)的不確定性更加有效，而且改進了系統(tǒng)的控制性能。通過利用優(yōu)化控制方法和引入的性能指標函數(shù)，使得控制成本達到最小，進而實現(xiàn)最優(yōu)控制。本論文主要做了以下三方面的工作： （1）針對一類包含了未知函數(shù)和非對稱死區(qū)的非線性離散系統(tǒng)，提出了一種自適應模糊優(yōu)化控制算法。模糊邏輯系統(tǒng)用于逼近系統(tǒng)中的未知函數(shù)�；趶娀瘜W習和backstepping算法，設計控制器使得性能指標函數(shù)達到最小，從而實現(xiàn)優(yōu)化控制的目的。設計自適應輔助信號來處理死區(qū)帶來的影響，再利用梯度下降規(guī)則求得自適應律。最后，根據(jù)李雅普諾夫穩(wěn)定性定理，證明了該閉環(huán)系統(tǒng)的所有信號的有界性。仿真實例驗證了所提出控制算法的可行性。 （2）基于帶有濾波跟蹤誤差的直接啟發(fā)式動態(tài)規(guī)劃方法，解決了Henon映射混沌系統(tǒng)的最優(yōu)跟蹤控制問題。其中模糊邏輯系統(tǒng)用于逼近效用函數(shù)，較之前的工作，減少了控制器的成本。最后，依據(jù)李雅普諾夫函數(shù)分析方法，確保了系統(tǒng)的穩(wěn)定性，同時，證明了跟蹤誤差、自適應律和控制輸入的有界性。仿真結果證明了設計方法的有效性。 （3）研究了離散的六階感應電動機模型的自適應跟蹤控制問題。在設計過程中，充分利用了模糊邏輯系統(tǒng)的逼近性能，且較之前的控制，提出了僅需較少設計參數(shù)的自適應方案，減少了計算量。在李雅普諾夫意義下，，保證了被控系統(tǒng)的所有信號半全局一致最終有界，且跟蹤誤差收斂到零的一個小領域內。仿真結果進一步說明了提出方法的實用性。
[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.
【學位授予單位】：遼寧工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：O232

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相關期刊論文 前3條

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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

本文編號：2429699