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Model Predictive Control for Automatic Carrier Landing with Time Delay
International Journal of Aerospace Engineering ( IF 1.1 ) Pub Date : 2021-08-18 , DOI: 10.1155/2021/8613498
Kaikai Cui 1 , Wei Han 1 , Yujie Liu 1 , Xinwei Wang 2 , Xichao Su 1 , Jie Liu 3
Affiliation  

This paper focuses on the problem of automatic carrier landing control with time delay, and an antidelay model predictive control (AD-MPC) scheme for carrier landing based on the symplectic pseudospectral (SP) method and a prediction error method with particle swarm optimization (PE-PSO) is designed. Firstly, the mathematical model for carrier landing control with time delay is given, and based on the Padé approximation (PA) principle, the model with time delay is transformed into an equivalent nondelay one. Furthermore, a guidance trajectory based on the predicted trajectory shape and position deviation is designed in the MPC framework to eliminate the influence of carrier deck motion and real-time error. At the same time, a rolling optimal control block is designed based on the SP algorithm, in which the steady-state carrier air wake compensation is introduced to suppress the interference of the air wake. On this basis, the PE-PSO delay estimation algorithm is proposed to estimate the unknown delay parameter in the equivalent control model. The simulation results show that the delay estimation error of the PE-PSO algorithm is smaller than 2 ms, and the AD-MPC algorithm proposed in this paper can limit the landing height error within ±0.14 m under the condition of multiple disturbances and system input delay. The control accuracy of AD-MPC is much higher than that of the traditional pole assignment algorithm, and its computational efficiency meets the requirement of real-time online tracking.

中文翻译:

航母时滞自动着陆模型预测控制

本文重点研究具有时延的航母自动着陆控制问题,以及基于辛伪谱(SP)方法和粒子群优化(PE)预测误差方法的航母着陆抗延迟模型预测控制(AD-MPC)方案。 -PSO) 的设计。首先给出了航母时滞着陆控制的数学模型,并基于Padé近似(PA)原理,将时滞模型转化为等效的无时滞模型。此外,在 MPC 框架中设计了基于预测轨迹形状和位置偏差的制导轨迹,以消除载体甲板运动和实时误差的影响。同时,基于SP算法设计了滚动优化控制块,其中引入稳态载气尾流补偿来抑制空气尾流的干扰。在此基础上,提出PE-PSO时延估计算法来估计等效控制模型中的未知时延参数。仿真结果表明,PE-PSO算法的时延估计误差小于2 ms,本文提出的AD-MPC算法在多重扰动和系统输入条件下,能够将着陆高度误差限制在±0.14 m以内。延迟。AD-MPC的控制精度远高于传统的极点分配算法,其计算效率满足实时在线跟踪的要求。提出了PE-PSO延迟估计算法来估计等效控制模型中的未知延迟参数。仿真结果表明,PE-PSO算法的时延估计误差小于2 ms,本文提出的AD-MPC算法在多重扰动和系统输入条件下,能够将着陆高度误差限制在±0.14 m以内。延迟。AD-MPC的控制精度远高于传统的极点分配算法,其计算效率满足实时在线跟踪的要求。提出了PE-PSO延迟估计算法来估计等效控制模型中的未知延迟参数。仿真结果表明,PE-PSO算法的时延估计误差小于2 ms,本文提出的AD-MPC算法在多重扰动和系统输入条件下,能够将着陆高度误差限制在±0.14 m以内。延迟。AD-MPC的控制精度远高于传统的极点分配算法,其计算效率满足实时在线跟踪的要求。14 m 在多重干扰和系统输入延迟的情况下。AD-MPC的控制精度远高于传统的极点分配算法,其计算效率满足实时在线跟踪的要求。14 m 在多重干扰和系统输入延迟的情况下。AD-MPC的控制精度远高于传统的极点分配算法,其计算效率满足实时在线跟踪的要求。
更新日期:2021-08-19
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