不確定非線性離散系統(tǒng)的自適應(yīng)模糊優(yōu)化控制與應(yīng)用
發(fā)布時(shí)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(diǎn)和難點(diǎn)問(wèn)題，為此，本文針對(duì)非線性離散系統(tǒng)，提出的自適應(yīng)模糊控制方法不僅對(duì)于處理系統(tǒng)的不確定性更加有效，而且改進(jìn)了系統(tǒng)的控制性能。通過(guò)利用優(yōu)化控制方法和引入的性能指標(biāo)函數(shù)，使得控制成本達(dá)到最小，進(jìn)而實(shí)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(duì)一類(lèi)包含了未知函數(shù)和非對(duì)稱(chēng)死區(qū)的非線性離散系統(tǒng)，提出了一種自適應(yīng)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)。基于強(qiáng)化學(xué)習(xí)和backstepping算法，設(shè)計(jì)控制器使得性能指標(biāo)函數(shù)達(dá)到最小，從而實(shí)現(xiàn)優(yōu)化控制的目的。設(shè)計(jì)自適應(yīng)輔助信號(hào)來(lái)處理死區(qū)帶來(lái)的影響，再利用梯度下降規(guī)則求得自適應(yīng)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(hào)的有界性。仿真實(shí)例驗(yàn)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(dòng)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(wèn)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(shí)，證明了跟蹤誤差、自適應(yīng)律和控制輸入的有界性。仿真結(jié)果證明了設(shè)計(jì)方法的有效性。 （3）研究了離散的六階感應(yīng)電動(dòng)機(jī)模型的自適應(yīng)跟蹤控制問(wèn)題。在設(shè)計(jì)過(guò)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(shè)計(jì)參數(shù)的自適應(yīng)方案，減少了計(jì)算量。在李雅普諾夫意義下，，保證了被控系統(tǒng)的所有信號(hào)半全局一致最終有界，且跟蹤誤差收斂到零的一個(gè)小領(lǐng)域內(nèi)。仿真結(jié)果進(jìn)一步說(shuō)明了提出方法的實(shí)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(xué)位授予單位】：遼寧工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：O232
本文編號(hào)：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.
【學(xué)位授予單位】：遼寧工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：O232
【參考文獻(xiàn)】
相關(guān)期刊論文 前3條
1 許文琳,吳蓉暉;模糊控制系統(tǒng)的李亞普諾夫第二法穩(wěn)定性分析[J];湖南大學(xué)學(xué)報(bào)(自然科學(xué)版);2004年03期
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
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