Fuzzy Control of a Gyroscopic Inverted Pendulum

摘要

In this paper we present the efficient control imparted to an inverted gyroscopic pendulum (GIP) and demonstrate how the control mechanism through a flywheel mounted at the top of the GIP governed by a fuzzy logic controller (FLC) achieves good stability and control performance of the system around vertical position. The intuitive knowledge of controlling the GIP via a wheel momentum is fuzzified in an FLC with a base of 49 rules. FLC design is conducted using simulation before testing on real GIP plant. Compared to a proportional-integral-derivative (PID) controller it is concluded that the FLC is more suitable for stabilizing the GIP system which has a weak restoring torque. I. INTRODUCTION Development of control techniques for inverted pendulum (IP) has always remained an interesting topic to control engineers for decades. This is largely due to its physical simplicity along with complete instability. Also these control techniques are applicable to control of rockets, robots, fast moving ground vehicles and anti-seismic controls for buildings. The control goal aims at keeping the IP at an upright position, despite the natural tendency of IP to fall on either side. There are various types of IPs discussed academically followed by many kinds of control methods, e.g. Proportional-Integral-Derivative (PID), Fuzzy Logic (FL), Linear-Quadratic-Gaussian (LQG), Genetic Algorithms (GA) and Artificial Neural Networks (ANN), or any combination of these techniques. Most of the pendulums developed so far have restoring force(s) applied somehow at the fulcrum. Various linearization techniques can be used to account for nonlinearities, such as linear compensators based on Jacobian linearization. Similarly, approximate linearization was used effectively to design a controller for an inverted pendulum (1). Some authors have considered an alternative control action consisting of an oscillatory vertical force applied to the pendulum pivot (2), (3). The stabilizing