| 季 力.改进粒子群算法在空压机联动控制中的应用[J].轻工机械,2014,32(4): |
| 改进粒子群算法在空压机联动控制中的应用 |
| Process Control Technology of Continuous Dynamic Countercurrent Extraction on Traditional Chinese Medicine |
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| DOI： |
| 中文关键词: 多目标优化 改进粒子群算法 灰色理论 空压机组功耗 均衡调度 管网波动 |
| 英文关键词:multi-objective optimization improved particle swarm optimization ( PSO) algorithm Grey Theory air
compressor ' s power balance scheduling pressure variance |
| 基金项目: |
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| 摘要点击次数: 1398 |
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| 中文摘要: |
| 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。 |
| 英文摘要: |
| ln 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 mertia 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. |
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