Sensors & Transducers

Vol. 261, Issue 2, July 2023, pp. 33-40

Controlling a Two-Link Robot using Sliding Mode Control Combined with Neural Network

Ayoub Belkheir and El Mehdi Mellouli

Laboratory of Engineering, Systems, and Applications (LISA) Sidi Mohamed Ben Abdellah University Fez, Morocco


Received: 25 May 2023 /Accepted: 23 June 2023 /Published: 26 June 2023

Abstract: This research focuses on designing and controlling a MIMO (Multiple Input and Multiple Output) two-link robot using a mix of Sliding Mode Control (SMC) and artificial intelligence (specifically, Radial Basis Function Neural Network (RBFNN)). In the first section, we present the model dynamics of this system in the state space. Then, in the second section, we provide a new approach in which we attempt to identify the optimum performance and attain stability in finite time by predicting the nonlinear dynamics of the system and also reducing the disturbance and uncertainty impacts on the system using artificial intelligence. And, by examining the Lyapunov function we can prove the stability of the system. Based on the simulations of the new technique presented in the latter portion of this work, we illustrate and enhance the superiority of our methodology over existing ways, their positive outcomes, and their effectiveness in time tracking, stability, and robustness.

Keywords: Two-link robot, Normal sliding mode control, Artificial intelligence, Lyapunov function, Non-linear function.