Abstract
The inverted pendulum is a standard classical problem in the branch of control and systems. If a cart is bushed by force then its position and angle of the pendulum will be changed. Several controllers may employed, keeping the pendulum arm upright by controlling at the cart location. In this search paper, the fuzzy-like PID (FPID) controller has been used to control the inverted pendulum, and the parameters of the controller are tuned with several evolutionary optimization algorithms like a genetic algorithm (GA), ant colony optimization (ACO), and social spider optimization (SSO.) The result of tuned FPID with evolutionary optimization is compared with conventional PID, and it shows that FPID with SSO has been given the best result.
Highlights
The inverted pendulum is an excellent system to verify the capability of controllers in the control engineering field, and a perfect test benchmark for various complicated control searching problems
This paper presents three types of evolutionary optimization algorithms, first (GA), second (ACO), third (SSO)
By applying the fuzzy controller on the mathematical model of the inverted pendulum, which is obtained in section 2 by using evolutionary optimization algorithms, the results changed according to the type of optimization algorithm
Summary
The inverted pendulum is an excellent system to verify the capability of controllers in the control engineering field, and a perfect test benchmark for various complicated control searching problems. Some researchers neglect the friction in the mathematical model of the inverted pendulum for linearizing the system [2,3,4]. The social spider optimization (SSO) is very rarely used to find the parameters with controllers of Inverted pendulum even with its superiority compared with other artificial intelligent algorithms; as was proven in the results of this paper. This paper implements a fuzzy-PID controller and its parameters tuning by several evolutionary optimization algorithms.
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