ADRC design for folding wing vehicles based on improved equilibrium optimization algorithm
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摘要:
针对折叠翼飞行器(FWV)模型误差和抗扰动能力较差及自抗扰控制器(ADRC)人工参数整定难的问题,提出一种基于莱维飞行的改进平衡优化(LEO)算法。给出典型FWV动力学模型,基于ADRC结构设计一种FWV的姿态控制器;在此基础上用所提算法整定了ADRC参数,并从控制性能和抗干扰的角度对经参数优化后的ADRC和传统ADRC进行仿真对比;将所提算法与经典平衡优化算法、粒子群优化(PSO)算法等进行仿真对比。仿真结果表明:所提算法优化的控制器能提高FWV的控制精度和扰动抑制性能,验证了所提算法在解决ADRC参数优化问题时的优越性。对搭载优化后ADRC的样机进行实飞验证,结果表明:在风扰之下,FWV样机仍具有较好的飞行性能指标,进一步验证了所提算法优化的ADRC对FWV抗扰能力的提升。
Abstract:In view of the modeling errors and poor anti-disturbance ability of folding wing vehicles (FWV) and the difficulty in manual parameter setting of active disturbance rejection controllers (ADRC), an optimization algorithm based on improved equilibrium optimizer based on Lévy(LEO)was proposed. A dynamics model of typical FWV was established, and an attitude controller for the FWV was designed based on the ADRC structure. The parameters of the ADRC were adjusted by the proposed algorithm, and a comparison between the optimized ADRC and the traditional ADRC by the simulation was made from the perspective of control performance and anti-disturbance. The proposed algorithm was compared with the classical equilibrium optimizer, particle swarm optimization (PSO) algorithm, and so on. The simulation results show that the controller optimized by the proposed algorithm can improve the control accuracy and disturbance suppression performance of FWV, and the superiority of the algorithm in the parameter optimization of ADRC was verified. The prototype equipped with the improved ADRC was verified in real flight. The results show that the FWV prototype still has a good flight performance index under wind disturbance, which further verifies that ADRC optimized by the proposed algorithm improves the anti-disturbance of FWV.
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表 1 控制参数优化前后
Table 1. Control parameters before and after optimization
控制器 ${\beta _{01}}$ ${\beta _{02}}$ ${\beta _{03}}$ ${\beta _1}$ ${\beta _2}$ ADRC 100.00 60 000.00 1 000 000.00 2 500.00 134.00 LEO算法优化后
ADRC300.00 50 415.00 897 390.00 10 000 134 -
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