Parameters Optimization of PID Controller for an Artillery Coordinator Based on Multi-Objective Genetic Algorithm

The Artillery coordinator is vital important to the accuracy of artillery firing. However, state-of-the-art optimization methods to the control parameters of artillery coordinator, always utilize single subject modeling and analysis, which result in the coupling effects between different disciplines...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:International Conference on Industrial Mechatronics and Automation (Online) s. 1332 - 1337
Hlavní autoři: Chen, Junhua, Chen, Longmiao, Miao, Wei, Chen, Guangsong
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 13.10.2020
Témata:
Analytical models
Coordinator
Couplings
Evolutionary computation
Hydraulic control
Hydraulic systems
Multi-objective evolutionary algorithm
Multidisciplinary optimization
PI control
Simulation
Vibrations
ISSN:2152-744X
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:The Artillery coordinator is vital important to the accuracy of artillery firing. However, state-of-the-art optimization methods to the control parameters of artillery coordinator, always utilize single subject modeling and analysis, which result in the coupling effects between different disciplines are not considered, In this paper, we propose a multi-objective optimization analysis method to decrease the mechanical vibration of the artillery coordinator and improve its control performance. Specifically, we take the mechanical structure, control parameters and hydraulic characteristics of the artillery coordinator into consideration and formulate the mathematical multidisciplinary model of the artillery. For this model, we target on the PID controller's variables optimization, and adopt the genetic algorithm to realize the multi-objective optimization analysis. Finally, three examples are adopted to verify the effectiveness of the optimization results. Simulation results show that the proposed multi-objective model is efficient and feasible.
ISSN:2152-744X
DOI:10.1109/ICMA49215.2020.9233838