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本文提出了一种基于模糊规则的PID控制器的设计方法。这种方法首先通过建立模糊规则和进行模糊推理来确定PID控制器的Kp,Ki,Kd等参数,而后由PID控制规律控制广义对象。实验结果表明,本文所设计的模糊PID控制系统比常规PID控制系统具有更优良的控制品质。 相似文献
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模糊控制器在延迟控制系统中的应用 总被引:1,自引:0,他引:1
论述了模糊控制器在延迟系统控制中的应用,针对Smith预估器的设计需要精确的被控对象的传递函数的问题,提出了模糊控制器用于延迟系统控制的方案,并根据作者的经验设计了一个模糊控制规则,通过仿真实验,取得了较好的控制效果。表明模糊控制器用于延迟系统的控制具有较强的实用价值。 相似文献
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针对广义控制对象的一维鲁棒PID控制器 总被引:2,自引:0,他引:2
在现代鲁棒控制理论基础上,针对广义控制对象提出一种一维鲁棒PID控制器设计方法,其优点是控制器参数可以解析得到,控制器只有一个可调的参数,被调参数与系统的鲁棒性有直接的联系,特别地控制器可以很好地用于大纯滞后控制对象。仿真结果表明本文方法与其他方法相比具有本质的改进。 相似文献
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基于模糊规则的多模型控制方法在AUV航向控制中的应用 总被引:4,自引:0,他引:4
本文研究了基于模糊切换规则的多模型控制方法,通过模糊切换实现了多控制器集的平滑切换,各局部控制器可以采用常规或智能控制规律设计。并在环境干扰条件下,以航向控制为例,对AUV进行航向跟踪,对比基于单一模型下设计的控制器:仿真结果验证了该控制方法具有很好的控制性能和鲁棒性。 相似文献
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单参数PID模糊控制器的设计 总被引:10,自引:0,他引:10
本文提出单参数智能PID 模糊控制器的一种设计方法。对不同的被控对象,这种方法只需调节PID 某一个参数,皆能获得最佳的控制效果。本模糊控制器已成功地用于成都飞机工业公司自行研制的超塑成形机床微机温控系统,并通过公司级鉴定。 相似文献
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《Applied Soft Computing》2007,7(2):481-491
In conventional fuzzy logic controllers, the computational complexity increases with the dimensions of the system variables; the number of rules increases exponentially as the number of system variables increases. Hierarchical fuzzy logic controllers (HFLC) have been introduced to reduce the number of rules to a linear function of system variables. However, the use of hierarchical fuzzy logic controllers raises new issues in the automatic design of controllers, namely the coordination of outputs of sub-controllers at lower levels of the hierarchy. In this paper, a method is described for the automatic design of an HFLC using an evolutionary algorithm called differential evolution (DE).The aim in this paper is to develop a sufficiently versatile method that can be applied to the design of any HFLC architecture. The feasibility of the method is demonstrated by developing a two-stage HFLC for controlling a cart–pole with four state variables. The merits of the method are automatic generation of the HFLC and simplicity as the number of parameters used for encoding the problem are greatly reduced as compared to conventional methods. 相似文献
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Although a considerable amount of effort has been put in to show that fuzzy logic controllers have exceptional capabilities of dealing with uncertainty, there are still noteworthy concerns, e.g., the design of fuzzy logic controllers is an arduous task due to the lack of closed-form input–output relationships which is a limitation to interpretability of these controllers. The role of design parameters in fuzzy logic controllers, such as position, shape, and height of membership functions, is not straightforward. Motivated by the fact that the availability of an interpretable relationship from input to output will simplify the design procedure of fuzzy logic controllers, the main aims in this work are derive fuzzy mappings for both type-1 and interval type-2 fuzzy logic controllers, analyse them, and eventually benefit from such a nonlinear mapping to design fuzzy logic controllers. Thereafter, simulation and real-time experimental results support the presented theoretical findings. 相似文献
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A. Hunter K.-S. Chiu 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2000,4(3):186-192
This paper discusses the design of neural network and fuzzy logic controllers using genetic algorithms, for real-time control
of flows in sewerage networks. The soft controllers operate in a critical control range, with a simple set-point strategy
governing “easy” cases. The genetic algorithm designs controllers and set-points by repeated application of a simulator. A
comparison between neural network, fuzzy logic and benchmark controller performance is presented. Global and local control
strategies are compared. Methods to reduce execution time of the genetic algorithm, including the use of a Tabu algorithm
for training data selection, are also discussed. The results indicate that local control is superior to global control, and
that the genetic algorithm design of soft controllers is feasible even for complex flow systems of a realistic scale. Neural
network and fuzzy logic controllers have comparable performance, although neural networks can be successfully optimised more
consistently. 相似文献
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采用新的DNA进化算法自动设计Takagi-Sugeno模糊控制器 总被引:7,自引:0,他引:7
提出一种新颖的基于DNA的进化算法(DNA-EA)来自动设计一类Trakagi-Sugeno
(TS)模糊控制器.TS模糊控制器采用带有线性规则后项的TS模糊规则,连续输
入模糊集,Zadeh模糊逻辑和常用的重心反模糊器.TS模糊控制器被证明是带有可变增
益的非线性PI控制器.DNA-EA被用于自动获取TS模糊规则,并同时优化模糊规则前
项和后项中的设计参数.DNA-EA采用由生物DNA结构启发得到的DNA编码方法来编
码模糊控制器的设计参数.在DNA-EA中,引入了受微生物进化现象启发的基因转移和细
菌变异操作.另外,也引入了基于DNA遗传操作的框构变异操作.DNA编码方法非常适
合于复杂知识的表达,基于基因水平的遗传操作也很容易引入到DNA-EA中.染色体的长
度是可变的,且可插入或删除部分碱基序列.作为示例,给出了采用DNA-EA来自动设计
TS模糊控制器用于控制一类非线性系统的方法.DNA-EA能自动地构造模糊控制器.计
算机仿真结果表明,DNA-EA是有效的,且优化得到的模糊控制器是满意的. 相似文献
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Steven H. -Y. Lai 《Computers & Industrial Engineering》1993,25(1-4):13-16
A Genetic Algorithms (GAs) based method is presented in this paper for concurrent design of rule sets and membership functions for a fuzzy logic controllers to be used in spacecraft proximity operations. The heuristic nature of fuzzy logic makes GAs a natural candidate for logic design in which both rule sets and membership functions are optimized simultaneously. The employment of GAs natural genetic operations provides a means to search in a complex system space that is difficult to described mathematically. A one-dimensional controller for spacecraft proximity operations is implemented for examination in detail. The expension of the algorithm for a 6 DOP controller is discussed. 相似文献
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Woodward S.E. Garg D.P. 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》1999,29(4):565-569
This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error, and control output. The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science payload line-of-sight pointing control is used to demonstrate results. 相似文献
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This paper develops a representation of multi-model based controllers using artificial intelligence techniques. These techniques will be graph theory, neural networks, genetic algorithms, and fuzzy logic. Thus, graph theory is used to describe in a formal and concise way the switching mechanism between the various plant parameterizations of the switched system. Moreover, the interpretation of multi-model controllers in an artificial intelligence frame will allow the application of each specific technique to the design of improved multi-model based controllers. The obtained artificial intelligence-based multi-model controllers are compared with classic single model-based ones. It is shown through simulation examples that a transient response improvement can be achieved by using multi-estimation based techniques. Furthermore, a method for synthesizing multi-model-based neural network controllers from already designed single model-based ones is presented, extending the applicability of this kind of technique to a more general type of controller. Also, some applications of genetic algorithms and fuzzy logic to multi-model controller design are proposed. In particular, the mutation operation from genetic algorithms inspires a robustness test, which consists of a random modification of the estimates which is used to select the one leading to the better identification performance towards parameterizing online the adaptive controller. Such a test is useful for plants operating in a noisy environment. The proposed robustness test improves the selection of the plant model used to parameterize the adaptive controller in comparison to classic multi-model schemes where the controller parameterization choice is basically taken based on the identification accuracy of each model. Moreover, the fuzzy logic approach suggests new ideas to the design of multi-estimation structures, which can be applied to a broad variety of adaptive controllers such as robotic manipulator controller design. 相似文献
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Wei Li 《Fuzzy Systems, IEEE Transactions on》1997,5(1):128-137
It is known that control signals from a fuzzy logic controller are determined by a response behavior of a controlled object rather than its analytical models. That implies that the fuzzy controller could yield a similar control result for a set of plants with a similar dynamic behavior. This idea lends to modeling of a plant with unknown structure by defining several types of dynamic behaviors. On the basis of dynamic behavior classification, a new method is presented for the design of a neuro-fuzzy control system in two steps: 1) we model a plant with unknown structure by choosing a set of simplified systems with equivalent behavior as “templates” to optimize their fuzzy controllers off-line; and 2) we use an algorithm for system identification to perceive dynamic behavior and a neural network to adapt fuzzy logic controllers by matching the “templates” online. The main advantage of this method is that convergence problem can be avoided during adaptation process. Finally, the proposed method is used to design neuro-fuzzy controllers for a two-link manipulator 相似文献
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Yong-Qing Fan Yin-He Wang Yun Zhang Qin-Ruo Wang 《International Journal of Control, Automation and Systems》2013,11(3):624-629
This paper proposes a novel adaptive fuzzy control design for a class of nonlinear uncertain systems. The definition of compressor and limiter with adjustable parameters is introduced at beginning, and then updated laws of parameters of the compressor and estimate values of fuzzy approximation accuracies are utilized to synthesize stable adaptive controllers. The most advantage of designing adaptive fuzzy controller is neglectful of the logic structure of fuzzy logic systems, which make designer focus on parameters of the compressor, limiter and fuzzy approximation accuracies. This adaptive fuzzy control method can not only reduce the number of on-line updated parameters but also guarantee states of the closed-loop system to be uniformly ultimately bounded (UUB). Simulation results demonstrate the effectiveness of the control scheme in this paper. 相似文献
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The role of “hierarchy” in the design of fuzzy logiccontrollers 总被引:1,自引:0,他引:1
Sayyanodsari B. Homaifar A. 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》1997,27(1):108-118
This paper investigates the role of hierarchy in the systematic approach to the design of fuzzy logic controllers (FLC's). The key concept here is that the implementation of fuzzy engines at higher levels of the control hierarchy (where more reasoning is involved) yields more versatile fuzzy controllers with generally fewer control rules. At the same time, the structured nature of a hierarchical approach considerably simplifies the design procedure. 相似文献