Design of Hybrid MPC-PID Controller Based on Fractional Order Model of AMR

In today’s world, robots, especially autonomous mobile robots (AMR), have critical roles in domestic, medical, and industrial applications. As technology develops and the diverse demands emerge, the tasks to be completed by AMRs become more complex and challenging. AMRs need to be improved to struggle with these difficulties. So, implementing more precise and reliable control strategies for robots is becoming increasingly important. To this end, a novel hybrid control methodology, composed of a Proportional-Integral-Derivative (PID) controller and a model predictive controller (MPC), is proposed based on the fractional-order model of the AMR. The MPC optimizes the reference signal for the PID controller, enhancing overall performance. First, the fractional order model of AMR is extracted by considering the input and output data from AMR at different velocity values, eliminating the need for detailed physical modeling and technical information for AMR. After verifying the obtained model, a model reduction technique is applied to simplify the obtained transfer function to reduce the computational burden on the processor of AMR. Then, based on the simplified transfer function a hybrid MPC-PID controller is designed and implemented on Turtlebot3 Burger (TB3) AMR to improve the robot’s performance. It is demonstrated that the hybrid controller, which is designed without requiring detailed equations of the system components, exhibits a good performance in minimizing errors and enhancing reliability for both angular and linear velocity values.