基于粒子群算法的航天器控制参数优化设计

PSO-Based Controller Parameters Design for Spacecraft

  • 摘要: 针对大角度姿态快速机动的航天器姿态控制器进行参数优化设计. 采用四元数方法描述航天器的姿态运动,针对一类基于Lyapunov方法设计的姿态控制器,设计了描述控制器全局姿态调整能力的指标,量化了控制器参数对控制性能的影响,采用粒子群算法对控制器参数选择进行优化,避免了传统设计中基于经验选择设计参数,通过引入粒子间信息共享的机制求解优化问题. 仿真结果表明:粒子群算法采用简洁的位置和速度更新实现系统寻优,在有输出力矩约束的条件下,进入最优解67s所需的进化代数为31,可较快收敛到系统全局最优解.

     

    Abstract: This paper presents the parameters design and optimization of large angle attitude and rapid maneuver for spacecraft. Quaternion is used to describe spacecraft kinematics. Based on Lyapunov theory, a global attitude adjusting ability standard is defined for a series of spacecraft attitude controller. The influence of the parameters to the control capacity is discussed numerically. Particle swarm optimization (PSO) is proposed to optimize the parameters of controller, avoiding selecting parameters by traditional experience. The mechanism of sharing information among particles is introduced to obtain solution. Numerical simulation results show that PSO can reach the optimal solution 67s of system within 31 generations under the limits of output torque. By updating the position and velocity of particles to seek solutions, PSO provides strong global search ability and convergent performance.

     

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