The Sliding-Mode Control Based on a Novel Reaching Technique for Permanent Magnet Synchronous Motors

Abstract

In order to improve the robustness, disturbance rejection and dynamic response performance of permanent magnet synchronous motor (PMSM) speed servo system, a novel sliding mode control (NSMC) strategy is adopted to replace the traditional proportion integral (PI) regulator in the design of speed controller. The mathematical model of PMSM is analyzed and a sliding mode controller based on a novel reaching technique is proposed. The integral of speed error is introduced into sliding mode surface to avoid the requirements of acceleration signal and reduced the steady-state error of the system. Meanwhile, a variable speed reaching method is imported to make the approaching speed correlate with the change of system state |s|, so as to improve the dynamic quality. In addition, the sigmoid function is used to replace the sign function in the conventional SMC, which further reduces chattering phenomena. Simulation and experimental results show that the proposed NSMC method based on the new reaching technique can realize precise speed control. Compared with the conventional PI and SMC control, this method not only achieves a fastest and best response speed, but also has a strongest robustness of resisting the external disturbance.     

基于改进遗传算法的串联小水电群优化调度

建立了由沙畈水库和金兰水库组成的串联小水电群优化调度的数学模型，采用了改进遗传算法对该模型进行优化计算。算法设计编程简单、计算工作量小、收敛速度快。利用两个水库的入库径流实测值进行了仿真实验，结果说明优化调度能比常规调度取得更大的经济效益，同时也说明了遗传算法是求解小水电群优化调度的可行而有效的方法。     

Hybrid current loop timing control method for permanent magnet AC servo systems

Journal of Mechanical Science and Technology - The relationship between current loop bandwidth and time delay was analyzed on the basis of the mathematical model of a current loop. The time delays...     

小水电优化调度数学模型及其基于文化算法的比较研究

小水电优化调度常以发电量最大为目标,不考虑下游生态需水,为了满足小水电生态调度需求,本文提出了以控制水位和弃水最小为目标的小水电优化调度数学模型,并将文化算法应用于求解数学模型.算法中种群空间全局搜索采用改进遗传算法,文化空间对其的影响采用自适应粒子群优化算法.通过实例仿真比较分析了三个不同目标和不同流量约束边界的模型,验证了本文提出的模型和文化算法用于小水电优化问题的可行性和有效性.     

遗传算法在水电站机组优化组合中的研究与应用

建立了水电站机组优化组合数学模型,提出了基于二进制与浮点数混合编码的遗传算法工程实现方法,把问题分解为机组状态组合与机组负荷分配两个子问题,分别对其优化。对实例计算分析表明：遗传算法具有计算速度快,计算结果好的优点,其对发电机组优化组合问题的求解是可行的、有效的,具有较强的实用价值。     

水电站机组优化组合的混合粒子群优化算法

机组组合是水电站短期发电计划中一个非常重要的问题,合理的组合运行能带来显著的经济效益,开展对机组优化组合的可行性和有效性研究有重大的现实意义。建立了该问题的数学模型,并提出了混合粒子群算法（Hybrid Particle Swarm Optimization,HPSO）的工程实现方法,采用量子粒子群算法解决机组方案的确立,并采用粒子群算法求解负荷经济分配。设计了粒子的适应度计算方法和速度更新方法,提出了HPSO算法的求解步骤。仿真分析表明：HPSO算法求解机组优化组合问题是可行和有效的,该算法实现简单,具有更快更好的收敛性能。     

Process research on micro-machining diamond microgroove by femtosecond laser

Abstract

Using micro-nano processing system of 120 fs and 800?nm low-frequency femtosecond laser, the microgroove was processed on the CVD diamond. The effects of some processing parameters on the microgroove size were studied. The results showed that the depth and width of microgrooves increase with the increase of laser power, scanning times, while with the decrease of scanning speed. Moreover, the suitable scanning speed of femtosecond laser processing diamond is about 0.1?mm/s, and focusing on diamond can improve material removal efficiency and processing quality. It is indicated that these research work has certain guiding significance for processing diamond microchannels for heat dissipation of electronic chips.     

Deep reinforcement learning for permanent magnet synchronous motor speed control systems

Neural Computing and Applications - The permanent magnet synchronous motor (PMSM) servo system is widely applied in many industrial fields due to its unique advantages. In this paper, we study the...     

基于改进遗传算法的串联小水电群优化调度

建立了由沙畈水库和金兰水库组成的串联小水电群优化调度的数学模型，采用了改进遗传算法对该模型进行优化计算。算法设计编程简单、计算工作量小、收敛速度快。利用两个水库的入库径流实测值进行了仿真实验，结果说明优化调度能比常规调度取得更大的经济效益，同时也说明了遗传算法是求解小水电群优化调度的可行而有效的方法。     

基于自适应粒子群算法的梯级小水电群优化调度研究

针对以发电为主的梯级小水电群,以各水库的发电引用流量为决策变量,建立了以发电量最大为目标的梯级小水电群优化调度数学模型;设计了PSO算法和APSO算法的工程实现方法,具体包括编码设计、迭代方法设计以及惯性权重设计等;通过一个具有两库串联的梯级小水电群实例,将PSO算法和APSO算法的仿真寻优过程进行了比较,结果显示两种算法是有效的,并且APSO算法具有更强、更快的全局搜索能力;将APSO算法的仿真结果与同一条件下的GA算法的仿真结果进行了比较,结果显示APSO算法的仿真结果更优,更能充分利用水能资源.