Abstract
In this paper, two different soft-computing techniques namely proportional–integral–derivative (PID) and adaptive neuro-fuzzy inference system (ANFIS) have been applied for control of highly nonlinear three-stage inverted pendulum system. The system consists of three rigid pendulums mounted on a movable cart, and the objective is to stabilize all the three pendulums in the vertical upright position while the cart is controlled at particular location. A mathematical model of the proposed system has been developed using Newton’s second law of motion. All the three pendulums were connected to each other with the help of pin joints, thereby making its dynamics more complex and hence difficult to control. The study considered a PID controller for control due to its inherent robustness and ease of design. The results of PID were further used for training of ANFIS controller. The study further compares the performance of both the controllers by analyzing settling time, maximum overshoot ranges and steady-state error characteristics of the system. Simulations were performed in MATLAB which confirmed the validity of proposed technique.
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Ashwani, K., Yadnyesh, N. (2021). Control Optimization of Triple-Stage Inverted Pendulum Using PID-Based ANFIS Controllers. In: Saran, V.H., Misra, R.K. (eds) Advances in Systems Engineering. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-8025-3_49
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