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In this study, we proposed a controller design method of a two wheeled self-balancing vehicle (TWSBV) based on a fuzzy T-S model (T-S Fuzzy) associated with a genetic algorithm (GA). To achieve the stable controller of TWSBV, we used GA to determine the proper state feedback gains and used the T-S Fuzzy formed by the heuristic experiment with two fuzzy membership functions: vehicle body angle and...
Interval type-2 fuzzy logic controllers (IT2 FLCs) have been treated as a black box in most control applications because the input-output relationship is not fully understood. Reason is that the input-output mapping is very difficult to be expressed in closed-form, therefore, most fuzzy control designers use evolutionary computation methods such as genetic algorithm and big bang-big crunch optimisation...
This paper presents a novel terminal synergetic control for DC-DC buck converters. Since buck converters have high nonlinearity and uncertainty, an indirect adaptive control is developed based on recently developed synergetic control methodology. Fuzzy systems are used in an adaptive scheme to approximate the system using a nonlinear model while synergetic control guarantees robustness and the use...
In this paper a novel localization technique is proposed using fuzzy logic and genetic algorithm to get nearly precise location of sensor nodes, in a range free localization system. This localization technique gives a stable system in which both magnitude and range of the error are very low. Various membership functions (MF) are tested among which the Sinc MF provides the best results for the system...
Fuzzy modeling is one of the most known and used techniques in different areas to emulate the behavior of systems and processes. In most cases, as in data-driven fuzzy modeling, these fuzzy models reach a high performance from the point of view of accuracy, but from other points of view, such as complexity or interpretability, the models can present a poor performance. Several approaches are found...
Among the various approaches to determine the true domain of fuzzy inference rules in the designing of fuzzy controller, the important one is to solve a system of fuzzy relation equations corresponding to the fuzzy inference sentence. In our earlier work, we gave a new method to construct the system and presented a method to solve the system when the system is consistent. But when the system is inconsistent,...
This paper utilizes a real-valued genetic algorithm (RGA) and fuzzy system to an autonomous vehicle control problem. Obstacle avoidance and parking control are performed by the use of a CCD camera, sonar sensor, and localization system on a wheeled mobile robot (WMR). The camera provides image of the surrounding. Distance between the WMR and object or obstacle can be obtained by image process and...
This paper proposes an intelligent trading system using support vector regression optimized by genetic algorithms (SVR-GA) and multilayer perceptron optimized with GA (MLP-GA). Experimental results show that both approaches outperform conventional trading systems without prediction and a recent fuzzy trading system in terms of final equity and maximum drawdown for Hong Kong Hang Seng stock index.
Many high-order systems have a large state space. Such systems need to additional computation time for complex calculation to find the output response. Traditionally, iteration methods have been applied to solve this problem. In this paper advantages of stability equation method derived by Parmer, [1], and the error minimization technique used in genetic-fuzzy algorithm have been combined to propose...
The architecture of nature-inspired computation systems is inquired into, the characteristics of fuzzy design in nature-inspired computation systems are researched, and a particular scheme on fuzzy design in nature-inspired computation systems is designed with environment being these data gathered from the present; study unit adopting fuzzy optimization algorithm based on genetic algorithm; knowledge...
One of the most important goals of time series analysis is prediction basing on the analyzed information. But it is not easy to analyze the patterns, regularities and trends of non-stationary and/or chaos time series because their major characteristics are non-linear and vague. In this paper, we propose primary and secondary tuning procedures that can enhance the accuracy for designing fuzzy prediction...
In this paper, we try to automatically induce the membership functions appropriate for the TS fuzzy model. A GA-based learning algorithm is thus proposed to achieve the purpose. The proposed approach considers the shapes of membership functions in fitness evaluation in addition to the accuracy. The shapes of membership functions are evaluated by the overlap and coverage factors, which are used to...
In this paper, the application of the classifier system to human support of hot strip mill operation and making decision rules by the classifier system are described. The rule base for the correction of operation and the judgment of performance are necessary for the system that becomes agent of the human expert. The method to extract correction rules by a classifier system is shown. To search appropriate...
This paper applies an intelligent technique based on fuzzy-genetic algorithm for automatically detecting failures in aircraft. The fuzzy-genetic algorithm constructs the automatic fault detection system for monitoring aircraft behaviors. Fuzzy-based classifier is employed to estimates the time of occurrence and types of actuator failure. Genetic algorithms are used to generate an optimal fuzzy rule...
It is difficult to learn TSK fuzzy model because the problem is multiconstraint and multitarget optimization. GA-BP hybrid learning method for the model is proposed. Some problems related to a species coding means for the model structure, evolution and fitness evaluation strategy are discussed. The error back propagation algorithm (BP) for training the antecedent and consequent parameters during the...
In this paper, an effective genetic algorithm (GA) approach is proposed for tuning the parameters of membership functions based on input-output pairs. By minimizing a quadratic measure of the error in the least-squares sense, the real-valued chromosomes of a population are evolved to get the best coefficients. Comparison to the well-known back-propagation algorithm for fuzzy logic system shows that...
The purpose of this paper is to implement a new method for designation of fuzzy logic controller for STATCOM to improve the voltage profile. Because of the importance of power quality in industrial bus bars when the loads are numerous, the classic methods of control (because of inherent time delay) can not been used. Therefore the fuzzy controller has been developed to for compensation because of...
The purpose of this paper is to study a new method to design the fuzzy controller to control STATCOM for promotion voltage profile. Because of the importance of power quality in industrial bus bars when the loads are numerous, the classic methods of control (because of inherent time delay) can not been used. Therefore the fuzzy controller has been developed to for compensation because of the fast...
Transparent decision support systems in the finance sector have an important role in the analysis and the decision process. This paper proposes a relatively transparent credit scoring model for evaluating the creditworthiness of the credit applicants through a hybrid data mining approach. The main motivation to apply this approach is to obtain a credit scoring model from a data set that not only have...
This paper proposed control of static VAR compensator (SVC) for improvement of voltage profile with fuzzy controller that tuned with genetic algorithm. Our method integrated two design stages; determinations of membership function and rules consequent parameters, because these stages may not be independent, it's important to consider them simultaneously to obtain optimal fuzzy systems. We present...
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