Robust Passivity Cascade Technique-Based Control Using RBFN Approximators for the Stabilization of a Cart Inverted Pendulum

This paper proposes a novel passivity cascade technique (PCT)-based control for nonlinear inverted pendulum systems. Its main objective is to stabilize the pendulum’s upward states despite uncertainties and exogenous disturbances. The proposed framework combines estimation properties of radial basis function neural networks (RBFNs) with attributes framework. unknown terms system are estimated using an RBFN approximator. performance closed-loop further enhanced by integral angular position as virtual state variable. lumped (NN—Neural Network approximation, external disturbances parametric uncertainty) compensated adding robustifying adaptive rule-based signal PCT-based control. boundedness confirmed theorem. approach was assessed under both nominal disturbed conditions.