Fuzzy and neural approaches in engineering pdf download

Many classical and modern methods have been successfully applied for control of these systems Colon et al. In a study by Chang et al. The authors optimised parameters of fuzzy controllers using proposed approach.

The Lyapunov theorem was further used to analyse the close loop stability of the system. The study showed that it was much easier to control a 4-dimensional ball and beam system than a 4-dimensional inverted pendulum system. DOI: Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. A cascaded inner-outer loop scheme was constructed and parameters of inner loop FNN were tuned using gradient descent method. In another study by Bhushan et al.

The adaptive control comprises of an ideal control and a sliding mode control. The sliding mode control was used for ensuring the stability of Lyapunov function.

Oh et al. The proposed scheme consists of outer and inner controller in a cascaded architecture. The authors developed a static and dynamic sliding mode controller using both simplified and complete model. The results showed better performance of controllers designed using complete model of the system.

The study considers four inputs with two membership functions. The results showed that ACO with three parameter coding provides an optimal set of parameters for fuzzy control. In a research by Chang et al. The performance of the proposed control was further improved using ACO which optimised the controller parameters. In a study by Lin et al. The objective of the study was to drive the sliding cart and keep the see saw angle close to zero in equilibrium.

The experimental results indicate that the proposed methodology significantly enhances the performance of the system. The transfer function and object model of the proposed system has also been obtained. The results showed the effectiveness of the proposed algorithm compared to traditional PID control. Lv et al.

The balance control of ball and beam system was successfully obtained using both the controllers. In a recent research by Gao et al. The proposed system can be successfully used by students for understanding PID control in Matlab environment. The simulation and experimental results demonstrated the dynamic behaviour of ball and beam system. In this study authors designed and compared fuzzy logic and neural network controllers for stabilisation of ball and beam system.

It finds wide applications in the field of control, power systems, energy sector etc Sadeghi, ; Arya et al. The fuzzy set theory can handle uncertainties more easily compared to other traditional tools and theories Cavallaro, Images Donate icon An illustration of a heart shape Donate Ellipses icon An illustration of text ellipses.

Fuzzy and neural approaches in engineering Item Preview. EMBED for wordpress. Want more? Advanced embedding details, examples, and help! Exploring the value of relating genetic algorithms and expert systems to fuzzy and neural technologies, this forward-thinking text highlights an entire range of dynamic possibilities within soft computing With examples of specifically designed to illuminate key concepts and overcome the obstacles of notation and overly mathematical presentations often encountered in other sources, plus tables, figures, and an up-to-date bibliography, this unique work is both an important reference and a practical guide to neural networks and fuzzy systems "A Wiley-Interscience publication.

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