共查询到20条相似文献,搜索用时 31 毫秒
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一种基于人工免疫原理的最优模糊神经网络控制器 总被引:1,自引:0,他引:1
提出了一种基于人工免疫原理的最优RBF模糊神经网络控制器设计方案.首先给出了控制器结构,其次将免疫进化算法用于控制器参数的优化,设计了一种满足二次型性能指标的最优RBF模糊神经网络控制器.将该控制器用于控制实际倒立摆系统,并采用状态变量合成方法以大大减少模糊规则的数目,实验结果验证了该控制器的有效性. 相似文献
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Gwo-Ruey Yu Yu-Chia Huang Chih-Yung Cheng 《International journal of systems science》2016,47(9):2225-2236
In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi–Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used. 相似文献
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Sung-Kwun Oh Seung-Hyun Jung Witold Pedrycz 《Expert systems with applications》2009,36(9):11641-11651
In this study, we present a design of an optimized fuzzy cascade controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for a rotary inverted pendulum system. In this system, one controls the movement of a pendulum through the adjustment of a rotating arm. The objective is to control the position of the rotating arm and to make the pendulum maintain the unstable equilibrium point at vertical position. To control the system, we design a fuzzy cascade controller scheme which consists of two fuzzy controllers arrange in a cascaded topology. The parameters of the controller are optimized by means of the HFCGA algorithm. The fuzzy cascade scheme comprises two controllers located in two loops. An inner loop controller governs the position of the rotating arm while an outer controller modifies a set point of the inner controller implied by the changes of the angle of pendulum. The HFCGA being a computationally effective scheme of the Parallel Genetic Algorithm (PGA) has been developed to eliminate an effect of premature convergence encountered in Serial Genetic Algorithms (SGA). It has emerged as an effective optimization vehicle to deal with very large search spaces. A comparative analysis involving computing simulations and practical experiment demonstrates that the proposed HFCGA based fuzzy cascade controller comes with superb performance in comparison with the conventional Linear Quadratic Regulator (LQR) controller as well as HFCGA-based PD cascade controller. 相似文献
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Integration of PSO and GA for optimum design of fuzzy PID controllers in a pendubot system 总被引:1,自引:0,他引:1
In this paper, a novel auto-tuning method is proposed to design fuzzy PID controllers for asymptotical stabilization of a
pendubot system. In the proposed method, a fuzzy PID controller is expressed in terms of fuzzy rules, in which the input variables
are the error signals and their derivatives, while the output variables are the PID gains. In this manner, the PID gains are
adaptive and the fuzzy PID controller has more flexibility and capability than the conventional ones with fixed gains. To
tune the fuzzy PID controller simultaneously, an evolutionary learning algorithm integrating particle swarm optimization (PSO)
and genetic algorithm (GA) methods is proposed. The simulation results illustrate that the proposed method is indeed more
efficient in improving the asymptotical stability of the pendubot system.
This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January
31–February 2, 2008 相似文献
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Design and stability analysis of fuzzy model-based nonlinear controller for nonlinear systems using genetic algorithm 总被引:2,自引:0,他引:2
Lam H.K. Leung F.H. Tam P.K.S. 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2003,33(2):250-257
This paper presents stability analysis of fuzzy model-based nonlinear control systems, and the design of nonlinear gains and feedback gains of the nonlinear controller using a genetic algorithm (GA) with arithmetic crossover and nonuniform mutation. A stability condition is derived based on Lyapunov's stability theory with a smaller number of Lyapunov conditions. A solution of the stability conditions is also determined using GA. An application example of stabilizing a cart-pole typed inverted pendulum system is given to show the stabilizability of the nonlinear controller. 相似文献
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We design a non-linear stabilizing control law for a four degree of freedom spherical inverted pendulum. The pendulum is a slim cylindrical beam attached to a horizontal plane via a universal joint; the joint is free to move in the plane under the influence of a planar force. The upright position is an unstable equilibrium of the uncontrolled system because of gravity. The objective is to design a controller so that it stabilizes the upright position starting from any position in the upper hemisphere with arbitrary velocity. We achieve this by first transforming the original system to an appropriate upper triangular form and then designing a controller which incorporates a high gain design with the method of non-linear forwarding. The control law is evaluated through computer simulations. 相似文献
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基于遗传算法的模糊系统优化设计方法 总被引:32,自引:0,他引:32
提出了一种带有混合变长编码和模糊变异算子的新型模糊遗传算法,并钭其应用到模糊系统的优化设计中。仿真结构表明,这种方法具有即使系统缺乏任何先验知识,也能通过评价学习,遗传优化获得满足系统动态性能的优化控制规则的特点。 相似文献
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倒立摆的双闭环模糊控制 总被引:36,自引:3,他引:33
对倒立摆采用双闭环的模糊控制方案,内环控制倒立摆的角度,外环控制倒立摆的位置,两个模糊控制器的设计都很简单,执行时间很短。在实际倒立摆装置上的实验结果验证了该方案的可行性和良好的控制性能。 相似文献
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We develop a hybrid state-space fuzzy model-based controller with dual-rate sampling for digital control of chaotic systems. A Takagi-Sugeno (TS) fuzzy model is used to model the chaotic dynamic system and the extended parallel-distributed compensation technique is proposed and formulated for designing the fuzzy model-based controller under stability conditions. The optimal regional-pole assignment technique is also adopted in the design of the local feedback controllers for the multiple TS linear state-space models. The proposed design procedure is as follows: an equivalent fast-rate discrete-time state-space model of the continuous-time system is first constructed by using fuzzy inference systems. To obtain the continuous-time optimal state-feedback gains, the constructed discrete-time fuzzy system is then converted into a continuous-time system. The developed optimal continuous-time control law is finally converted into an equivalent slow-rate digital control law using the proposed intelligent digital redesign method. The main contribution of the paper is the development of a systematic and effective framework for fuzzy model-based controller design with dual-rate sampling for digital control of complex such as chaotic systems. The effectiveness and the feasibility of the proposed controller design method is demonstrated through numerical simulations on the chaotic Chua circuit 相似文献
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In this paper, an optimal adaptive robust PID controller based on fuzzy rules and sliding modes is introduced to present a general scheme to control MIMO uncertain chaotic nonlinear systems. In this control scheme, the gains of the PID controller are updated by using an adaptive mechanism, fuzzy rules, the gradient search method, and the chain rule of differentiation in order to minimize the sliding surfaces of sliding mode control. More precisely, sliding mode control is used as a supervisory controller to provide sufficient control inputs and guarantee the stability of the control approach. To ascertain the parameters of the proposed controller and avoid trial and error, the multi-objective genetic algorithm is employed to augment the performance of proposed controller. The chaotic system of a Duffing-Holmes oscillator and an industrial robotic manipulator are the case studies to evaluate the performance of the proposed control approach. The obtained results of this study regarding both systems are compared with the outcomes of two notable studies in the literature. The results and analysis prove the efficiency of the proposed controller with regard to MIMO uncertain systems having challenging external disturbances in terms of stability, minimum tracking error and optimal control inputs. 相似文献
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Nonlinear state feedback controller for nonlinear systems:Stability analysis and design based on fuzzy plant model 总被引:2,自引:0,他引:2
This paper presents the stability analysis of a fuzzy-model-based control system consisting of a nonlinear plant and a nonlinear state feedback controller and the design of the nonlinear gains of the controller. The nonlinear plant is represented by a fuzzy model having p rules. A nonlinear state feedback controller is designed to close the feedback loop. Under this design, the stability condition is reduced to p linear matrix inequalities. An application example on stabilizing a mass-spring-damper system will be given 相似文献
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针对设计高维模糊控制器过程中会遇到的“规则爆炸”问题,利用蚁群算法进行控制规则的过滤简化。为了用尽量少的规则得到尽可能好的控制效果,利用蚁群算法在饵决组合优化问题中的强大优势,在已有的完备规则中优选出若干条规则嵌人模糊控制器。采用带有时间窗口的蚁群算法去克服遗传算法优选模糊控制规则时可能产生的规则不连续的问题。该文还从遗传算法和蚁群算法工作机制的角度分析了对这两种算法加入约束条件的可操作性。以单级倒立摆控制系统为对象进行仿真研究,最后的仿真结果表明该文方法可以使模糊控制规则具有更好的简化效果和鲁棒性,并能具有好的控制效果。 相似文献
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利用混沌优化的模糊控制方法对二级倒立摆系统进行闭环控制。用混沌算法优化控制器的参数,首先将混沌变量引入到模糊控制器的参数域,并进行全局范围内直接寻优,当获得全局近似最优解后,再缩小寻优区间,根据性能指标,在次优解附近继续寻优,得到全局最优参数。控制结果说明该方法是有效可行的。 相似文献