Modeling and adaptive control of bipedal robots

This thesis focuses on the design and performance analysis of an adaptive control system for a bipedal robot with 5 degrees of freedom. Maintaining the balance and stability of walking motions in bipedal robots is one of the primary challenges in robotic control. To address this, an adaptive control strategy has been developed to ensure precise control of the robot's joint angles. The uncertainties in the robot's dynamic parameters, combined with changes in environmental factors, can negatively impact system performance. Therefore, the proposed adaptive control strategy enhances the system's flexibility and adaptability to counteract these uncertainties. The adaptive control system continuously detects changes in the robot's dynamic parameters and quickly responds to these fluctuations to maintain system stability. Thanks to these real-time updates, tracking errors are minimized, and the robot's stability is preserved. In simulations conducted in the Simulink environment, the adaptive control strategy exhibited lower tracking error, greater stability, and improved adaptability compared to the sliding mode control. In particular, it enhanced stability by increasing the robot's sensitivity and accuracy under changing environmental conditions. This demonstrates that the adaptive control strategy is an effective method to improve control for complex dynamic systems like bipedal robots. The control system developed in this study is based on Lyapunov stability criteria to ensure the stability of the robot and the accuracy of trajectory tracking. The results show that adaptive control offers a critical solution for bipedal robots to operate successfully in complex and variable environments. This study provides a valuable foundation for developing adaptive xvi control methods that can improve the performance of robots in challenging conditions, enhancing the reliability of robotic applications in advanced tasks.