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 共查询到17条相似文献,搜索用时 187 毫秒
1.
何宏  钱锋 《科技通报》2007,23(3):408-412
从隶属函数、控制规则、量化因子和比例因子等几个方面,详细介绍了遗传算法在模糊控制器中的应用原理和发展概况,并根据目前遗传模糊逻辑控制器设计中存在的问题,提出了该领域今后的研究重点和发展趋势,为从事遗传算法及模糊逻辑研究的技术人员提供了参考。  相似文献   

2.
针对VRV空调温度控制系统的滞后、时变、非线性等特点,提出将模糊控制和遗传算法相结合,设计出基于改进遗传优化算法的模糊温度控制器,进行了两者对空调系统房间温度控制的仿真及对比分析,结果表明采用改进遗传算法的模糊控制器后,系统能够迅速稳定在设定值周围,在大大缩短了调节时间和减小稳态误差的同时,保持了对扰动的抵抗能力,使得系统的稳定性没有太大改变,即算法可以保证房间温度最终趋于设定值25℃。  相似文献   

3.
详细介绍了模糊控制技术的研究与发展。主要论述了模糊控制理论的分类及其组成,对模糊控制器的设计及应用进行了综述。重点阐述了近年来模糊控制与其他先进控制算法的融合与改进,其中包括与预测控制结合的模糊预测控制,与神经网络的融合,以及基于遗传算法的模糊控制等。  相似文献   

4.
针对PID控制器在不同的应用系统,需要动态调整PID控制参数的问题,提出了基于遗传算法的PID自适应参数优化方案。该方案通过将PID控制器产生的误差作为目标函数,利用遗传算法实现对PID控制器参数的自动调整。为了提高参数的优化效率,文章通过对交叉算子和变异算子的自适应处理,提高了PID控制器的性能。实验测试表明,文章设计的PID参数优化策略比普通的基于遗传算法优化策略效率平均高14.7%。  相似文献   

5.
为了实现基于非训练数据的神经模糊控制器的在线学习,提出了一种基于强化学习的神经模糊控制系统和相应的学习算法。该控制系统由神经模糊预测器和神经模糊控制器两部分组成,其中,神经模糊控制器采用基于确定度的模糊规则模型作为知识表示形式的扩展型神经模糊网络。在学习算法的设计中,尝试了利用强化信号得到输入状态的“期望输出”,进而将强化学习转化为基于训练数据学习的解决思路。仿真实验验证了所提出的控制系统结构和学习算法的合理性和可行性。  相似文献   

6.
贺廉云 《科技通报》2011,27(5):682-685
为了解决多变量系统模糊控制器规则组合爆炸问题,提出了一种基于融合函数的多输入模糊控制器设计方法,以降低模糊控制器的输入变量维数,简化多输入模糊控制器的设计过程,有效地处理多变量问题.二级倒立摆系统控制实例证明了该方法的可行性和鲁棒性.  相似文献   

7.
文章采用模糊自整定PID参数法设计了装载机工作装置的位置控制器,运用基于MATLAB中的模糊工具箱,在Matlab/Simulink环境下对装裁机工作装置的液压控制系统的数学模型进行仿真研究.  相似文献   

8.
本文简要阐述了遗传算法和模糊控制的基本原理,并结合二者针对一个具体的随机非线性系统进行优化研究.文章设计了基于遗传算法的自适应模糊调节器,并在充分分析了量化因子对系统稳态性能和动态性能的影响的基础上,提出了一种智能调节量化因子的模糊控制算法,使系统具有更好的动态和稳态性能.文章利用此控制器对双线性模型进行了仿真,结果证明了其有效性.  相似文献   

9.
针对传统控制规则的不足,本文设计了基于自调整因子的模糊控制规则,并将基于自调整因子模糊PID控制器应用于直流电机调速系统进行仿真。仿真结果表明直流电机调速系统基于自调整因子模糊PID控制器比传统模糊PID控制器具有更快的响应速度和更好的抗扰动能力。  相似文献   

10.
安宁  邱玮炜 《内江科技》2010,31(8):88-88
根据矿井并下掘进工作面的工作环境要求,对传统的PID控制方法进行改进,提出了一种利用遗传算法对PID控制器参数进行整定的矿井局部通风机控制方法,基于遗传算法的PID控制器根据掘进工作面的工作环境对局部通风机的转速进行实时调整一控制系统能够达到较高的控制精度和较好的稳定性。  相似文献   

11.
基于模糊控制的卫星大角度姿态机动控制方法研究   总被引:1,自引:0,他引:1  
本文设计了一个典型Mamdani类PD型模糊控制器来研究卫星大角度姿态机动控制问题。卫星姿态机动控制要求控制系统响应快、具有较强鲁棒性。模糊控制器的设计十分灵活,在控制性能方面有自己突出的特点。通过仿真,考察了模糊控制器的隶属函数在各种参数下的不同控制性能,与一个传统I/O解耦PID控制器的控制效果进行比较,并验证了模糊控制器的鲁棒性。仿真结果证实模糊控制用于姿态机动控制有良好的效果。  相似文献   

12.
This paper proposes a passive fuzzy controller design methodology for nonlinear system with multiplicative noises. Applying the Itô's formula and the sense of mean square, the sufficient conditions are developed to analyze the stability and to design the controller for stochastic nonlinear systems which are represented by the Takagi-Sugeno (T-S) fuzzy models. The sufficient conditions derived in this paper belong to the Linear Matrix Inequality (LMI) forms which can be solved by the convex optimal programming algorithm. Besides, the passivity theory is applied to discuss the effect of external disturbance on system. Finally, some numerical simulation examples are provided to demonstrate the applications of the proposed fuzzy controller design technique.  相似文献   

13.
This paper is concerned with the problem of adaptive event-triggered (AET) based optimal fuzzy controller design for nonlinear networked control systems (NCSs) characterized by Takagi–Sugeno (T–S) fuzzy models. An improved AET communication scheme with a memory adaptive rule is proposed to enhance the utilization of the state response vertex data. Different from the existing ET based results, the improved AET scheme can save more communication resources and acquire better system performance. The sufficient criteria of performance analysis and controller design are presented for the closed-loop control system subject to mismatched membership functions (MFs) and AET scheme. And then, a new MFs online learning algorithm on the basis of the gradient descent approach is employed to optimize the MFs of fuzzy controller and obtain optimal fuzzy controller for further improving system performance. Finally, two simulation examples are presented to verify the advantage and effectiveness of the provided controller design technique.  相似文献   

14.
In this paper, an adaptive Takagi–Sugeno (T–S) fuzzy controller based on reinforcement learning for controlling the nonlinear dynamical systems is proposed. The parameters of the T–S fuzzy system are learned using the reinforcement learning based on the actor-critic method. This on-line learning algorithm improves the controller performance over the time, which it learns from its own faults through the reinforcement signal from the external environment and tries to reinforce the T–S fuzzy system parameters to converge. The updating parameters are developed using the Lyapunov stability criterion. The proposed controller is faster in learning than the T–S fuzzy that parameters learned using the gradient descent method under the same conditions. Moreover, it is able to handle the load changes and the system uncertainties. The test is carried out based on two mathematical models. In addition, the proposed controller is applied practically for controlling a direct current (DC) shunt machine. The results indicate that the response of the proposed controller has a good performance compared with other controllers.  相似文献   

15.
董景荣 《预测》1999,18(6):67-69,52
本文提出了一种基于Takagi-Sugeno 模糊规则基的非线性组合预测新方法,以克服线性组合预测方法在解决非平稳时间序列组合建模问题时所遇到的困难和存在的不足,并采用相应的遗传算法确定模糊系统的参数及模糊子集的划分。  相似文献   

16.
一般的洗衣机模糊控制器都是基于经验的模糊控制,其相应的模糊语言规则并没有揭示输入输出的逻辑关系。一种基于逻辑的洗衣机控制器设计方法被提出。这个例子说明基于逻辑的模糊控制与基于经验的模糊控制相比,基于逻辑的模糊控制更合理更简便。通过控制输出的比较,说明在达到相同精度的条件下,基于逻辑的模糊控制需要计算量更少。  相似文献   

17.
The interconnected large-scale power systems are liable to performance degradation under the presence of sudden small load demands, parameter ambiguity and structural changes. Due to this, to supply reliable electric power with good quality, robust and intelligent control strategies are extremely requisite in automatic generation control (AGC) of power systems. Hence, this paper presents an output scaling factor (SF) based fuzzy classical controller to enrich AGC conduct of two-area electrical power systems. An implementation of imperialist competitive algorithm (ICA) is made to optimize the output SF of fuzzy proportional integral (FPI) controller employing integral of squared error criterion. Initially the study is conducted on a well accepted two-area non-reheat thermal system with and without considering the appropriate generation rate constraint (GRC). The advantage of the proposed controller is illustrated by comparing the results with fuzzy controller and bacterial foraging optimization algorithm (BFOA)/genetic algorithm (GA)/particle swarm optimization (PSO)/hybrid BFOA-PSO algorithm/firefly algorithm (FA)/hybrid FA-pattern search (hFA-PS) optimized PI/PID controller prevalent in the literature. The proposed approach is further extended to a newly emerged two-area reheat thermal-PV system. The superiority of the method is depicted by contrasting the results of GA/FA tuned PI controller. The proposed control approach is also implemented on a multi-unit multi-source hydrothermal power system and its advantage is established by Correlating its results with GA/hFA-PS tuned PI, hFA-PS/grey wolf optimization (GWO) tuned PID and BFOA tuned FPI controllers. Finally, a sensitivity analysis is performed to demonstrate the robustness of the proposed method to broad changes in the system parameters and size and/or location of step load perturbation.  相似文献   

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