Gradient-Based MPC Controller for One DOF Copter Control

• Published in: International Journal of Applied Methods in Electronics and Computers
• Main Author: Uyar, Okan
• Format: Journal Article
• Language: English
• Published: 31.12.2024
• ISSN: 3023-4409; 3023-4409
• DOI: 10.58190/ijamec.2024.110

This study tries to contrast the performance of Gradient Based Model Predictive Control (MPC) with the classical PID controllers in the control of a 1 DOF copter system. While PID controllers are easy to set up and be applied in a vast number of occasions, they may become insufficient when nonlinear systems or operating constraints are considered. To that end, results show that MPC, whose optimization formulation predicts the system dynamics, has better performance measures. Simulation results show that the gradient-based MPC performs well in dynamic and steady-state performance compared to PID controllers tuned with two different coefficients. In particular, the MPC is characterized by high accuracy and minimum long-term error, no overshoot and fast settling time. In noisy conditions, MPC is able to produce a stable control signal due to its predictive capability, whereas PID controllers are more sensitive to such conditions and produce a chattering signal. It is concluded that the Gradient Based MPC is a good choice for applications that require more precise control and robustness against noise, while PID controllers are preferable due to their simplicity and low computational cost. This study tries to contrast the performance of Gradient Based Model Predictive Control (MPC) with the classical PID controllers in the control of a 1 DOF copter system. While PID controllers are easy to set up and be applied in a vast number of occasions, they may become insufficient when nonlinear systems or operating constraints are considered. To that end, results show that MPC, whose optimization formulation predicts the system dynamics, has better performance measures. Simulation results show that the gradient-based MPC performs well in dynamic and steady-state performance compared to PID controllers tuned with two different coefficients. In particular, the MPC is characterized by high accuracy and minimum long-term error, no overshoot and fast settling time. In noisy conditions, MPC is able to produce a stable control signal due to its predictive capability, whereas PID controllers are more sensitive to such conditions and produce a chattering signal. It is concluded that the Gradient Based MPC is a good choice for applications that require more precise control and robustness against noise, while PID controllers are preferable due to their simplicity and low computational cost.