Universiti Teknologi Malaysia Institutional Repository

Fuzzy force learning controller of flexible wiper system

Zolfagharian, Ali and Valipour, Peiman and Ghasemi, Seyed Ebrahim (2016) Fuzzy force learning controller of flexible wiper system. Neural Computing and Applications, 27 (2). pp. 483-493. ISSN 0941-0643

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Abstract

Wiper blade of automobile is among those types of flexible system that is required to be operated in quite high velocity to be efficient in high load conditions. This causes some annoying noise and deteriorated vision for occupants. The modeling and control of vibration and low-frequency noise of an automobile wiper blade using soft computing techniques are focused in this study. The flexible vibration and noise model of wiper system are estimated using artificial intelligence system identification approach. A PD-type fuzzy logic controller and a PI-type fuzzy logic controller are combined in cascade with active force control (AFC)-based iterative learning (IL). A multi-objective genetic algorithm is also used to determine the scaling factors of the inputs and outputs of the PID-FLC as well as AFC-based IL gains. The results from the proposed controller namely fuzzy force learning (FFL) are compared with those of a conventional lead–lag-type controller and the wiper bang–bang input. Designing controllers based on classical methods could become tedious, especially for systems with high-order model. In contrast, FFL controller design requires only tuning of some scaling factors in the control loop and hence is much simpler and efficient than classical design methods.

Item Type:Article
Uncontrolled Keywords:Artificial intelligence, Computation theory, Fuzzy logic, Genetic algorithms, Identification (control systems), Intelligent control, Iterative methods, Religious buildings, Soft computing, Active force control, Artificial intelligence systems, Automotive wiper, Fuzzy logic controllers, Learning controllers, Multi-objective genetic algorithm, PI-type fuzzy logic controller, Softcomputing techniques, Controllers
Subjects:T Technology > TJ Mechanical engineering and machinery
Divisions:Mechanical Engineering
ID Code:73951
Deposited By: Fahmi Moksen
Deposited On:22 Nov 2017 12:07
Last Modified:22 Nov 2017 12:07

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