Artificial Intelligence Resources in Control and Automation Engineering

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This e-book focuses on the application of artificial intelligence resources in fields related to Control and Automation Engineering. Techniques such as neural networks, fuzzy logic and expert systems ...
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Fuzzy Controllers Design for the Inertia Wheel Inverted Pendulum

Pp. 73-91 (19)

Fatah Chetouane


The purpose of this chapter is to introduce the control problem of a complex system called the Inertia Wheel Inverted Pendulum (IWIP) using fuzzy logic technique. In this study, the IWIP is controlled using three different fuzzy controller designs: a self-tuning fuzzy Proportional-Integral-Derivative controller, a Mamdani-type fuzzy logic controller, and a Sugeno-type fuzzy logic controller. The performance of the designed controllers in regard to achieving stable control of the IWIP is compared and discussed. The main objective of this chapter is to address fuzzy logic controller design efficiently in a simple manner without prior knowledge of fuzzy sets theory. The only mathematics used is to describe the IWIP nonlinear physical model. Fuzzy Logic Controllers (FLC) design is explained based on the intuitive and experimental functioning of the IWIP system. The IWIP is simulated under different fuzzy control methods using Simulink™ fuzzy logic toolbox, Mathworks Inc. The IWIP parameters are provided, and our hope is that this study will serve as a benchmark for graduate students and engineers interested in applying fuzzy logic techniques in their project.


Inertia wheel pendulum, fuzzy controllers.


IEEE senior member, Electrical and Industrial Engineering Department, Université de Moncton, New Brunswick, E1A3E9 Canada