Enhanced Control of an Inverted Cart-Pendulum System Using Cascade Pd Controller Optimized With Genetic Algorithm

Abstract

The inverted pendulum system is a widely studied benchmark problem in control engineering due to its inherent nonlinearity and instability. In this work, a nonlinear multibody model of the inverted pendulum is developed and analyzed to capture the complex dynamics of the system. A cascade Proportional-Derivative (PD) control scheme is implemented, with the dual objectives of controlling the pendulum angle and the cart position through nested control loops. The optimal tuning of PD gains, a critical factor for robust performance, is performed using Genetic Algorithm optimization technique. The proposed approach is implemented and simulated in MATLAB Simulink with Simscape to evaluate its effectiveness. Simulation results demonstrate the successful control of both pendulum angle and the cart position. The study highlights the success of cascade PD control and superior performance of the GA tuning approach over conventional methods, emphasizing its efficacy in handling nonlinear and dynamic control challenges. © 2025 IEEE.