Design of Multi-Criteria PI Controller Using Particle Swarm Optimization for Multiple UAVs Close Formation

2010 ◽  
Vol 1 (2) ◽  
pp. 1-17
Author(s):  
Xiangyin Zhang ◽  
Haibin Duan ◽  
Shan Shao ◽  
Yunhui Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Absolute Error ◽  
Pi Controller ◽  
Formation Flight ◽  
Swarm Optimization ◽  
Formation Tracking ◽  
Multiple Uavs ◽  
On Line ◽  
Uninhabited Aerial Vehicles

Close formation flight is one of the most complicated problems on multiple Uninhabited Aerial Vehicles (UAVs) coordinated control. This paper proposes a new method to achieve close formation tracking control of multiple UAVs by applying Particle Swarm Optimization (PSO) based Proportional plus Integral (PI) controller. Due to its simple structure and effectiveness, multi-criteria PI control strategy is employed to design the controller for multiple UAVs formation, while PSO is used to optimize the controller parameters on-line. With the inclusion of overshoot, rise time, and system accumulated absolute error in the multi-criteria performance index, the overall performance of multi-criteria PI controller is optimized to be satisfactory. Simulation results show the feasibility and effectiveness of the proposed approach.

Design of Multi-Criteria PI Controller Using Particle Swarm Optimization for Multiple UAVs Close Formation

2012 ◽  
pp. 99-113
Author(s):  
Xiangyin Zhang ◽  
Haibin Duan ◽  
Shan Shao ◽  
Yunhui Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Absolute Error ◽  
Pi Controller ◽  
Swarm Optimization ◽  
Formation Tracking ◽  
Multiple Uavs ◽  
On Line ◽  
Overall Performance ◽  
Uninhabited Aerial Vehicles

Close formation flight is one of the most complicated problems on multiple Uninhabited Aerial Vehicles (UAVs) coordinated control. This paper proposes a new method to achieve close formation tracking control of multiple UAVs by applying Particle Swarm Optimization (PSO) based Proportional plus Integral (PI) controller. Due to its simple structure and effectiveness, multi-criteria PI control strategy is employed to design the controller for multiple UAVs formation, while PSO is used to optimize the controller parameters on-line. With the inclusion of overshoot, rise time, and system accumulated absolute error in the multi-criteria performance index, the overall performance of multi-criteria PI controller is optimized to be satisfactory. Simulation results show the feasibility and effectiveness of the proposed approach.

A Novel Control Scheme for PWM Boost Converter based on Sliding Mode Control using Particle Swarm Optimization

2020 ◽  
Vol 14 ◽  
Author(s):  
Gang Liu ◽  
Dong Qiu ◽  
Xiuru Wang ◽  
Ke Zhang ◽  
Huafeng Huang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Steady State ◽  
Sliding Mode ◽  
Particle Swarm ◽  
Mathematic Model ◽  
Absolute Error ◽  
Boost Converter ◽  
Sliding Mode Controller ◽  
Swarm Optimization ◽  
Steady State Performance

Background: The PWM Boost converter is a strongly nonlinear discrete system, especially when the input voltage or load varies widely, therefore, tuning the control parameters of which is a challenge work. Objective: In order to overcome the issues, particle swarm optimization (PSO) is employed for tuning the parameters of a sliding mode controller of a boost converter. Methods: Based on the analysis of the Boost converter model and its non-linear characteristics, a mathematic model of a boost converter with a sliding mode controller is built firstly. Then, the parameters of the Boost controller are adjusted based on the integrated time and absolute error (ITAE), integral square error (ISE) and integrated absolute error (IAE) indexes by PSO. Results: Simulation verification was performed, and the results show that the controllers tuned by the three indexes all have excellent robust stability. Conclusion: The controllers tuned by ITAE and ISE indexes have excellent steady-state performance, but the overshoot is large during the startup. The controller tuned by IAE index has better startup performance and slightly worse steady-state performance.

Sign in / Sign up

Export Citation Format

Share Document