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基于灰狼优化算法的茶园拖拉机转角控制器

Steering controller of tea garden tractor based on grey wolf optimization algorithm

  • 摘要: 比例积分微分(proportional-integral-derivative, PID)控制算法被广泛用于茶园拖拉机的转角控制系统,但是PID控制器带来大量的参数整定以及滞后性,必然会降低控制精度和控制效率.为了解决这一问题,提出了基于灰狼优化算法(grey wolf optimization algorithm, GWOA)的茶园拖拉机转角控制器.首先,建立了简化的茶园拖拉机电动助力转向(electric power steering, EPS)系统的数学模型;其次,采用了基于PID的电动机电流-转向盘转角双闭环的控制策略;接着,设计了灰狼优化算法来对传统PID控制器的参数进行优化,构建了基于灰狼优化算法的PID转角控制器(GWOA-PID);最终,利用CARSIM和MATLAB实时模拟拖拉机运行情况,对提出的基于灰狼优化算法的茶园拖拉机转角控制器进行验证,结果表明:传统PID控制器的电流总谐波畸变(total harmonic distortion,THD)为11.46%,基于粒子群算法(particle swarm optimization, PSO)的PID控制器的THD为8.12%,所提出的GWOA-PID控制器的THD为6.28%,使得电流谐波在原来的基础上降低了45.2%.

     

    Abstract: Proportional-integral-derivative(PID) control algorithm is widely used in the angle control system of tea garden tractor, but the PID controller brings a lot of parameters setting and hysteresis, which can inevitably reduce the control accuracy and control efficiency. To solve the problem, a tea garden tractor angle controller based on the grey wolf optimization algorithm(GWOA) was proposed. A simplified mathematical model for electric power steering(EPS) system of tea garden tractor was established, and a PID-based motor current-steering wheel angle double closed-loop control strategy was adopted. The GWOA was designed to optimize the parameters of the traditional PID controller, and the PID angle controller based on GWOA was constructed. CARSIM and MATLAB were used to simulate the tractor operation in real time, and the proposed tea garden tractor angle controller algorithm based on GWOA was verified. The results show that the total current harmonic distortion(THD) of the traditional PID controller is 11.46%, and the THD of the particle swarm optimization(PSO)PID controller is 8.12%. The THD of the proposed GWOA-PID controller is 6.28%, which reduces the current harmonics by 45.2%.

     

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