Multiobjective optimization design of a fractional order PID controller for a gun control system.

Area of Science:

• Control Engineering
• Robotics
• Applied Mathematics

Background:

• Motion control of gun barrels is critical for high-performance gun control equipment.
• Traditional control strategies often face limitations in achieving desired accuracy and robustness.

Purpose of the Study:

• To develop an optimal fractional order PID control strategy for gun barrel motion control.
• To propose a novel multiobjective optimization algorithm for tuning controller parameters.

Main Methods:

• A fractional order PID (FOPID) control strategy was implemented for the gun control system.
• A multiobjective optimization scheme based on Pareto optimal solutions and differential evolution was developed.
• Opposition-based learning and adaptive mutation were incorporated to enhance the optimization algorithm's performance.

Main Results:

• The proposed optimization method successfully identified optimal parameters for the FOPID controller.
• Numerical simulations demonstrated that the controlled system exhibits fast response times and high accuracy.
• The control system showed significant robustness against uncertainties and disturbances.

Conclusions:

• The developed parameter tuning method for fractional order PID controllers is effective for gun control systems.
• The proposed approach enhances system performance in terms of speed, precision, and robustness.
• This work contributes a novel optimization technique applicable to complex control problems.