Abstract
Aiming at dealing with the difficulty for traditional emergency rescue vehicle (ECV) to enter into limited rescue scenes, the electro-hydraulic steer-by-wire (SBW) system is introduced to achieve the multi-mode steering of the ECV. The overall structure and mathematical model of the SBW system are described at length. The fractional order proportional-integral-derivative (FOPID) controller based on fractional calculus theory is designed to control the steering cylinder’s movement in SBW system. The anti-windup problem is considered in the FOPID controller design to reduce the bad influence of saturation. Five parameters of the FOPID controller are optimized using the genetic algorithm by maximizing the fitness function which involves integral of time by absolute value error (ITAE), peak overshoot, as well as settling time. The time-domain simulations are implemented to identify the performance of the raised FOPID controller. The simulation results indicate the presented FOPID controller possesses more effective control properties than classical proportional-integral-derivative (PID) controller on the part of transient response, tracking capability and robustness.
摘要
针对传统应急救援车辆很难顺利通过狭小地域的救援现场, 本文设计电液线控转向系统, 实现 应急救援车辆的多模式转向。首先, 详细描述了电液线控转向系统的总体架构和数学模型。其次, 设 计基于分数阶微积分理论的分数阶 PID 控制器 控制线控转向系统中转向油缸的运动。进一步, 在分 数阶 PID 控制器设计中考虑抗饱和问题。然后, 通过遗传算法最大化适应度函数, 优化分数阶 PID 控 制器的 5 个参数。该适应度函数包括时间乘绝对值误差积分, 最大超调和调节时间。最后, 通过时域 仿真来判定分数阶 PID 控制器的性能。仿真结果表明, 本文所提出的分数阶 PID 控制器在瞬态响应, 跟踪能力和鲁棒性方面比传统 PID 控制器具有更好的控制特性。
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Foundation item: Project(2016YFC0802904) supported by the National Key Research and Development Program of China
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Xu, Fx., Liu, Xh., Chen, W. et al. Fractional order PID control for steer-by-wire system of emergency rescue vehicle based on genetic algorithm. J. Cent. South Univ. 26, 2340–2353 (2019). https://doi.org/10.1007/s11771-019-4178-4
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DOI: https://doi.org/10.1007/s11771-019-4178-4
Keywords
- steer-by-wire system
- emergency rescue vehicle
- fractional order proportional-integral-derivative (FOPID) controller
- parameter optimization
- genetic algorithm