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Proceedings ArticleDOI: 10.1109/ICCPCT.2014.7054808

Tuning and implementation of fuzzy logic controller using simulated annealing in a nonlinear real-time system

20 Mar 2014-pp 916-921
Abstract: Tuning a controller for any process purely depends on the process dynamics. Improper selection of controller parameters could spoil the entire design. Selecting a tuning technique to achieve a desired response could be dealt as an optimization problem. This paper deals with the tuning of a fuzzy logic controller using Simulated Annealing to minimize the Mean Square Error between the desired and actual output of a nonlinear system. The proposed algorithm is tested on a real time ball beam system and the results are compared with the simulated responses. By using this method best results are obtained by using less number of fuzzy membership functions. more

Topics: Adaptive simulated annealing (61%), Fuzzy logic (60%), Control theory (57%) more

Open accessJournal Article
01 Jan 2011-Springer US
Abstract: LaVail (Eds), Retinal Degenerative Diseases (Advances in Experimental Medicine and Biology 723) ISBN 978-1-4614-0630-3 7 * € (D) 213,95 | € (A) 219,94 | sFr 266,50 7 € 199,95 | £180.00 Special_SpacerSpecial_Spacer Mylonakis (Eds), Recent Advances on Model Hosts (Advances in Experimental Medicine and Biology 710) ISBN 978-1-4419-5637-8 7 * € (D) 149,75 | € (A) 153,94 | sFr 201,00 7 € 139,95 | £126.00 Special_SpacerSpecial_Spacer more

Topics: Soft computing (68%)

51 Citations

Proceedings ArticleDOI: 10.1109/EDUCON46332.2021.9454013
Gergely Takács1, Erik Mikulas1, Anna Vargova1, Tibor Konkoly1  +6 moreInstitutions (1)
21 Apr 2021-
Abstract: This article presents a reference design for the well-known ball-on-beam laboratory experiment, where a spherical ball without direct actuation is only balanced by the inclination of a supporting structure, such as beam, rail or tube. The design introduced here is completely open-source and utilizes only a handful of off-the-shelf components and 3D printing; resulting in an exceptionally low hardware cost. Moreover, the resulting apparatus fits on a standard expansion module format, known as a Shield, which is compatible with a range of microcontroller prototyping boards from the Arduino ecosystem. This affordable, small, reproducible and open design is thus intended to aid control systems or mechatronics education via hands-on student experiments or even conducting research on a budget. In addition to the hardware design with downloadable project files, we also present an application programming interface and the results of a demonstration example here. more

Topics: Ball and beam (56%), Open design (54%), Arduino (53%) more

1 Citations


Open accessJournal ArticleDOI: 10.1109/91.755393
Yuhui Shi1, Russell C. Eberhart2, Yaobin Chen2Institutions (2)
Abstract: Evolutionary fuzzy systems are discussed in which the membership function shapes and types and the fuzzy rule set including the number of rules inside it are evolved using a genetic (evolutionary) algorithm. In addition, the genetic parameters (operators) of the evolutionary algorithm are adapted via a fuzzy system. Benefits of the methodology are illustrated in the process of classifying the iris data set. Possible extensions of the methods are summarized. more

Topics: Fuzzy set operations (69%), Fuzzy classification (69%), Fuzzy number (68%) more

423 Citations

Journal ArticleDOI: 10.1109/3477.752795
01 Apr 1999-
Abstract: Due to their powerful optimization property, genetic algorithms (GAs) are currently being investigated for the development of adaptive or self-tuning fuzzy logic control systems. This paper presents a neuro-fuzzy logic controller (NFLC) where all of its parameters can be tuned simultaneously by GA. The structure of the controller is based on the radial basis function neural network (RBF) with Gaussian membership functions. The NFLC tuned by GA can somewhat eliminate laborious design steps such as manual tuning of the membership functions and selection of the fuzzy rules. The GA implementation incorporates dynamic crossover and mutation probabilistic rates for faster convergence. A flexible position coding strategy of the NFLC parameters is also implemented to obtain near optimal solutions. The performance of the proposed controller is compared with a conventional fuzzy controller and a PID controller tuned by GA. Simulation results show that the proposed controller offers encouraging advantages and has better performance. more

Topics: Fuzzy logic (58%), PID controller (58%), Fuzzy control system (57%) more

251 Citations

Open accessBook
01 Jan 1995-
Abstract: 1. Fuzzy Logic in Minutes. 2. Fuzzy Logic Primer. 3. Development Tools for Fuzzy Systems. 4. NeuroFuzzy Technologies. 5. Case Studies of Industrial Applications. 6. Fuzzy Design Cookbook. 7. Using the Software. 8. Comparing Fuzzy vs. Conventional Control. References. Index. more

Topics: Fuzzy logic (73%), Neuro-fuzzy (68%), Fuzzy control system (65%) more

245 Citations

Journal ArticleDOI: 10.1109/TIE.2012.2192891
Abstract: In this paper, the balance control of a ball and beam system is considered. Based on the T-S fuzzy modeling, the dynamic model of the ball and beam system is formulated as a strict feedback form with modeling errors. Then, an adaptive dynamic surface control (DSC) is utilized to achieve the goal of ball positioning subject to parameter uncertainties. The robust stability of the closed-loop system is preserved by using the Lyapunov theorem. In addition to simulation results, the proposed T-S fuzzy model-based adaptive dynamic surface controller is applied to a real ball and beam system for practical evaluations. Simulation and experimental results illustrate that the proposed control scheme has much better performance than that of conventional DSC. Furthermore, parameter uncertainties and external disturbance are considered to highlight the robustness of the proposed control scheme. more

Topics: Ball and beam (73%), Adaptive control (62%), Robust control (58%) more

87 Citations

Journal ArticleDOI: 10.1016/J.KNOSYS.2011.07.006
Abstract: This paper suggests the optimal tuning of low-cost fuzzy controllers dedicated to a class of servo systems by means of three new evolutionary optimization algorithms: Gravitational Search Algorithm (GSA), Particle Swarm Optimization (PSO) algorithm and Simulated Annealing (SA) algorithm. The processes in these servo systems are characterized by second-order models with an integral component and variable parameters; therefore the objective functions in the optimization problems include the output sensitivity functions of the sensitivity models defined with respect to the parametric variations of the processes. The servo systems are controlled by Takagi-Sugeno proportional-integral-fuzzy controllers (T-S PI-FCs) that consist of two inputs, triangular input membership functions, nine rules in the rule base, the SUM and PROD operators in the inference engine, and the weighted average method in the defuzzification module. The T-S PI-FCs are implemented as low-cost fuzzy controllers because of their simple structure and of the only three tuning parameters because of mapping the parameters of the linear proportional-integral (PI) controllers onto the parameters of the fuzzy ones in terms of the modal equivalence principle and of the Extended Symmetrical Optimum method. The optimization problems are solved by GSA, PSO and SA resulting in fuzzy controllers with a reduced parametric sensitivity. The comparison of the three evolutionary algorithms is carried out in the framework of a case study focused on the optimal tuning of T-S PI-FCs meant for the position control system of a servo system laboratory equipment. Reduced process gain sensitivity is ensured. more

Topics: Defuzzification (60%), Fuzzy logic (56%), Evolutionary algorithm (56%) more

75 Citations

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