改进粒子群算法在空压机联动控制中的应用

针对空压机控制系统中的节能减排、均衡调度和管网压力波动等问题,提出了空压机联动控制的多目标优化调度模型,并以改进惯性权重的粒子群算法进行求解。以灰色系统理论中的灰色关联度作为改进粒子群算法的适应度函数,对影响空压机联动系统的机组功耗、生产均衡调度和管网压力波动等多目标进行了优化求解。引入的非线性动态调整惯性权重策略改进了算法的全局收敛能力,有效地提高了粒子搜索过程中的智能性。通过某饮料罐装车间的技术改造,证明了本算法的有效性。

Application of Improved Particle Swarm Optimization Algorithm in Air Compressor Associated Controlling System

In order to solve the energy-saving and emission-reduction, balanced dispatching and pressure variance in pipe network, a multi-objective optimization scheduling model of air compressor associated controlling system was presented, which used the particle swarm optimization based on the improved inertia weight. Using the grey relation in grey theory as the fitness function of the improved algorithm, it optimized the air compressor＇s power, the balance scheduling and the pressure variance reduce in pipe network. The nonlinear dynamic inertia weight strategy improved the algorithm＇s global convergence ability, and increased the intelligence in the search process of the particle. The algorithm was proved effectively by the technical transformation in a canning workshop.