As a key type of mobile robot, the two-wheel mobile robot has been developed rapidly for varied domestic, health, and industrial applications due to human-like movement and balancing characteristics based on the inverted pendulum theory. This paper presents a developed Two-Wheel Self-Balanced Robot (TWSBR) model under road disturbance effects and simulated using MATLAB Simscape Multibody. The considered physical-mechanical structure of the proposed TWSBS is connected with a Simulink controller scheme by employing physical signal converters to describe the system dynamics efficiently. Through the Simscape environment, the TWSBR motion is visualized and effectively analyzed without the need for complicated analysis of the associated mathematical model. Besides, 3D visualization of real-time behavior for the implemented TWSBR plant model is displayed by Simulink Mechanics Explorer. Robot balancing and stability are achieved by utilizing Proportional Integral Derivative (PID) and Linear Quadratic Regulator (LQR) controllers' approaches considering specific control targets. A comparative study and evaluation of both controllers are conducted to verify the robustness and road disturbance rejection. The realized performance and robustness of developed controllers are observed by varying object-carrying loaded up on mechanical structure layers during robot motion. In particular, the objective weight is loaded on the robot layers (top, middle, and bottom) during disturbance situations. The achieved findings may have the potential to extend the deployment of using TWSBRs in the varied important application.
In this paper, a simulation was utilized to create and test the suggested controller and to investigate the ability of a quadruped robot based on the SimScape-Multibody toolbox, with PID controllers and deep deterministic policy gradient DDPG Reinforcement learning (RL) techniques. A quadruped robot has been simulated using three different scenarios based on two methods to control its movement, namely PID and DDPG. Instead of using two links per leg, the quadruped robot was constructed with three links per leg, to maximize movement versatility. The quadruped robot-built architecture uses twelve servomotors, three per leg, and 12-PID controllers in total for each servomotor. By utilizing the SimScape-Multibody toolbox, the quadruped robot can build without needing to use the mathematical model. By varying the walking robot's carrying load, the robustness of the developed controller is investigated. Firstly, the walking robot is designed with an open loop system and the result shows that the robot falls at starting of the simulation. Secondly, auto-tuning are used to find the optimal parameter like (KP, KI and KD) of PID controllers and resulting shows the robot can walk in a straight line. Finally, DDPG reinforcement learning is proposed to generate and improve the walking motion of the quadruped robot, and the results show that the behaviour of the walking robot has been improved compared with the previous cases, Also, the results produced when RL is employed instead of PID controllers are better.