首页|干涉式闭环光纤陀螺仪的PSO-PID控制优化方法

干涉式闭环光纤陀螺仪的PSO-PID控制优化方法

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控制系统的设计会对响应速度快且应用范围较广的数字干涉式闭环光纤陀螺(ICFOG)动态性能产生影响.通过分析ICFOG的工作原理,推导出闭环离散控制系统,并利用粒子群优化算法(Particle Swarm Optimization,PSO)对传统的PID控制器参数进行优化.基于这个优化过程,设计一种新型的PSO-PID复合控制器,以取代传统的PID控制器.通过与其他BP神经网络、模糊控制等方法进行对比凸显该控制方法的优越.通过数字仿真分析显示,跟踪速度相较于BP-PID控制方法提高了1.91倍,相对于PID控制方法提高了 3.5倍,相对于F-PID控制方法提高了 1.75倍.同时,控制精度相对于BP-PID控制方法提高了 46.03%,相对于PID控制方法提高了 66.30%,相对于F-PID控制方法提高了 45.27%.结果显示,采用PSO-PID控制器能够快速达到控制目标且具有较小的超调量.
Optimization method of PSO-PID control for interferometric closed-loop fiber optic gyroscope
Objective PSO-PID control optimization algorithm based on the interferometric closed-loop fiber optic gyroscope has been widely used in military and civil fields,such as aerospace,defense equipment,navigation survey,vehicle inertial navigation system and other industrial systems.These applications are developing in the direction of lightness,low power consumption,long life,high reliability,no self-locking and mass production.PSO-PID controller can improve the dynamic response of fiber optic gyroscope and effectively track the angular rate input of fiber optic gyroscope.Fiber optic gyroscope is based on Sagnac effect in closed optical path,so its bandwidth is much larger than that of traditional gyroscope.In digital closed-loop fiber optic gyroscope,the response speed of optical path is very fast,and the system bandwidth is mainly determined by the detection circuit.Choosing a suitable digital controller is helpful to improve the dynamic performance of fiber optic gyroscope.Methods The system block diagram of fiber optic gyroscope(Fig.1)is established,and the ICFOG closed-loop system is equivalent to a mathematical model(Fig.2)by analyzing the working principle of fiber optic gyroscope,and finally the closed-loop discrete control system is deduced.On this basis,a new PSO-PID compound controller is designed(Fig.3),and the optimization algorithm steps of PID controller of standard PSO are analyzed(Fig.4).The controller can adjust parameters Kp,Ki and Kd online during operation(Fig.15).At the same time,by comparing with the PID parameter tuning method of BP neural network(Fig.5),fuzzy PID parameter tuning method(Fig.6)and PID control method,the advantages of PSO-PID control are illustrated by comparing the angular rate input tracking speed of fiber optic gyro(Fig.12)and the angular rate input tracking error of fiber optic gyro(Fig.13).Results and Discussions Using PSO-PID control method,it is found that the fitness value changes rapidly.When the number of iterations is 15,the fitness value can reach the optimal solution,and the optimal solution is 21.892 5.At the same time,the tracking time of FOG angular rate input is 1.2 s.Compared with BP-PID,PID,and F-PID control methods,the tracking speed is increased by 1.91,3.5 and 1.75 times respectively.After the PSO-PID control method,the tracking error is 4.7 ×104 m,which is smaller than other control methods.Compared with F-PID,BP-PID and PID control methods,its control accuracy is improved by 45.27%,46.03%and 66.30%respectively.According to the comparison of dynamic performance of different control methods(Tab.1),it is known that PSO-PID controller can achieve the control goal quickly and has a small tracking error.Conclusions Based on the mathematical model of fiber optic gyro,this paper puts forward an optimization scheme of fiber optic gyro digital controller.The traditional digital controller is improved,and the PSO-PID controller is proposed and simulated.Compared with many control methods,the simulation results show that PSO-PID controller can shorten the adjustment time and reduce overshoot,thus effectively improving the dynamic performance of fiber optic gyroscope on the premise of ensuring stability,and has important engineering significance and practical value.To apply this optimization scheme to engineering practice,more external factors and more detailed control parameter analysis need to be considered,which will be the focus of later research.

ICFOGsmall overshootPSO-PIDBP neural networkfuzzy controller

刘尚波、丹泽升、廉保旺、徐金涛、曹辉

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西北工业大学电子信息学院,陕西西安 710072

西安中科华芯测控有限公司,陕西西安 710100

西北工业大学 自动化学院,陕西西安 710072

干涉式光纤陀螺 小超调量 粒子群优化PID方法 BP神经网络 模糊控制器

陕西省自然科学基础研究计划青年项目

2023-JC-QN-0760

2024

红外与激光工程
中国航天科工集团公司第三研究院第八三五八研究所

红外与激光工程

CSTPCD北大核心
影响因子:0.754
ISSN:1007-2276
年,卷(期):2024.53(3)
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