Fuzzy controller optimization using a genetic algorithm for non-collocated semi-active MR based control of a three-DOF framed struture

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Rui Carneiro de Barros (Author) FEUP; Manuel T. Braz-César (Author) Other; Pedro L. P. Folhento (Author) FEUP

Conference proceedings International

Title: 2018 13TH APCA INTERNATIONAL CONFERENCE ON CONTROL AND SOFT COMPUTING (CONTROLO)

Pages: 364-367

13th APCA International Conference on Control and Soft Computing (CONTROLO)

Univ Azores, Ponta Delgada, PORTUGAL, JUN 04-06, 2018

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Other information

Authenticus ID: P-00P-YB9

DOI: 10.1109/controlo.2018.8514553

Abstract (EN): This paper aims to explore the usefulness of a simple genetic algorithm (GA) optimized Fuzzy Logic Controller (FLC) to reduce the response of a three-DOF framed structure equipped with a MagnetoRheological (MR) damper. These actuators can be controlled in bi-state control mode and/or in a semi-active configuration by continuously adjusting the amount of damping according to the actual response. Generally, model based controllers are designed to determine the actuator output. In recent years, soft computing techniques have been implemented to deal with the highly non-linear nature of structural systems. Among others, fuzzy based controllers seem to be adequate approach for these cases due to the inherent ability to deal with uncertain systems. However, a FLC design requires a wide experience in operating the system. This can be very difficult to implement in complex systems and several optimization techniques have been suggested to enhance the design process of fuzzy controllers. In this paper, a genetic algorithm (GA) optimized semi-active fuzzy based controller is proposed to reduce the seismic response of a three degree-of-freedom (DOF) structure using a MR damper at the first DOF. The uncontrolled and controlled structural responses are compared to evaluate the effectiveness of the semi-active fuzzy based controller.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4