Research on system of ultra-flat carrying robot based on improved PSO algorithm

Area of Science:

• Robotics
• Control Systems Engineering
• Artificial Intelligence

Background:

• Ultra-flat carrying robots (UCRs) are crucial for functional safety road tests of intelligent driving vehicles, requiring high control performance.
• Existing motion control systems for UCRs necessitate analysis and upgrades to meet stringent performance demands.
• Standard optimization algorithms face challenges like local optima and slow convergence in complex system parameter identification.

Purpose of the Study:

• To develop a mathematical model for the UCR motion control system using test data and system identification.
• To propose a novel, refined particle swarm optimization (PSO) algorithm, termed IWCNS-PSO, to overcome limitations of standard PSO.
• To apply the IWCNS-PSO algorithm for accurate transfer function identification and Proportional-Integral (PI) controller parameter optimization in UCRs.

Main Methods:

• System identification techniques were employed to build the mathematical model of the UCR motion control system.
• A refined PSO algorithm (IWCNS-PSO) was developed, incorporating inertia weight cosine adjustment and a natural selection principle.
• MATLAB/Simulink was used to construct an interactive simulation model for tuning PI controller parameters via the critical proportioning method and IWCNS-PSO.

Main Results:

• The IWCNS-PSO algorithm demonstrated superior performance in test functions and system identification compared to standard PSO and LDIW-PSO, converging in 95 iterations with a fitness value of 0.117.
• PI controller parameters optimized by IWCNS-PSO significantly improved system performance, reducing adjustment time to 7.99 s and overshoot to 13.41%.
• The optimized control system met essential speed, stability, and accuracy requirements for intelligent driving vehicle road tests.

Conclusions:

• The IWCNS-PSO algorithm is an effective method for system identification of complex control systems like UCRs.
• IWCNS-PSO provides an efficient approach for optimizing control system parameters, leading to enhanced performance.
• The developed methodology offers a robust solution for improving the control capabilities of ultra-flat carrying robots in safety-critical applications.