一种新PSO混合算法在直升机配平中的应用

直升机配平计算是动力学分析的基础，其实质是求解高维复杂的非线性方程组。针对经典算法与智能算法的特点与不足，提出了一种求解非线性方程组的新粒子群方法。在粒子群(Particle swarm optimization, PSO)算法的基础上，根据模拟退火(Simulated annealing, SA)思想，引入了嵌入式LM (Levenberg-marquardt)优化 算子。该方法充分发挥了3种算法的优势，克服了LM算法初值敏感性，PSO算法易陷入局部极值等问题。通过UH-60A直升机实例配平计算，验证了本文算例模型的准确性。在此基础 上，针对某一前飞状态下的配平算例，在收敛可靠性和计算效率上通过与其他算法进行对比，表明该算法具有可靠的收敛性和较高的计算效率，进一步验证了该算法在配平问题上的可信度与实用性，为直升机飞行动力学问题的处理提供了一种新的有效方法。

Application of New PSO Hybrid Algorithm to Helicopter Trim

Helicopter trim analysis is essential for helicopter rotor dynamics investigations. The core of it is the solution of high dimensional nonlinear equations. For the advantages and disadvantages of classical methods and intelligent algorithms, a new particle swarm optimization(PSO) method for nonlinear equations is proposed. According to the idea of simulated annealing(SA), Levenberg-marquardt(LM) operator is embedded in PSO. The method takes full advantages of above three methods, solving the problems such as initial value sensitivity of LM and falling into local extreme value of PSO. UH-60A helicopter trim proves the accuracy of the helicopter trim model. On this basis,experimental results of UH-60A helicopter in a certain forward flight, compared with other methods in convergence reliability and solving efficiency, show that the proposed method has reliable convergence probability and high computation rate. It proves the reliability and the practicality of method in dealing with helicopter dynamical problems.