基于fpga - soc的新型工业机器人HSPICS:建模与制作

F. S. M. Alkhafaji, W. Hasan
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摘要

为了提高机器人中常用的直流电机的速度性能,人们对基于遗传算法的PI控制器进行了大量的优化研究。在PID控制器中,克服经典遗传算法缺点的研究很少,而且很少关注以微秒为单位来提高待测直流电机的速度性能。通过设计和制造高速比例积分控制系统(HSPICS),主要目标是最大限度地降低阶跃响应特性。主要方法包括三个子方法,使用几种新技术和程序来实现三个目标。首先,提出了一种改进的遗传算法(IGA),以提高PI控制器的性能,更好地搜索约束条件。其次,生成基于VHDL的Simulink模型,无需昂贵的软件。最后,利用嵌入式编码器和FPGA in the loop (FIL)技术集成基于FPGA soc的控制器,运行基于设计的模型。为了证明该建议的有效性,它使用了三个不同的直流电机。仿真结果表明,与经典遗传算法和粒子群算法相比,该控制器实现了更高的阶跃响应缩减率(RSRR),进一步缩短了以微秒为单位测量的阶跃响应特性。性能分析表明,电机1、2和3的RSRR分别比经典遗传算法提高了8倍、9倍和35倍,比PSO分别提高了3倍、3倍和10倍。仿真结果与实验结果的对比表明,所研究电机的稳态时间比(SST)明显减小。
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A Novel HSPICS for Industrial Robotic Controller Based on FPGA_SoC: Modelling and Fabrication
Tremendous studies have been proposed to optimize PI controller based Genetic Algorithm (GA) to improve the speed performance of DC motor commonly required in robotic applications. In PID controller, there are very few studies to overcome the drawbacks of classical GA, besides little pay attention to improving the speed performance of a DC motor to be measured in the microsecond unit. The main target is to maximize reduction step response characteristics, by proposing to design and fabricate a high speed proportional integral controller system (HSPICS). The primary methodology includes three sub methodologies using several new techniques and procedures to achieve three objectives. Firstly, to propose an improved genetic algorithm (IGA) to enhance the performance for better searching constraints for PI controller. Secondly, generate VHDL based Simulink model without needing expensive software. Finally, integrate the proposed controller-based on FPGA_SoC using Embedded Coder and FPGA in the loop (FIL) techniques to run the design based model. To show the effectiveness of the proposal, it was used three different DC motors. Simulation results show that the proposed controller achieves much higher reduction step response ratios (RSRR) compared with classical GA and PSO, further shortened step response characteristics to be measured in the microsecond unit. Analyzing the performance demonstrates that the RSRR has been enhanced for motors 1, 2, and 3 by 8, 9, and 35 times over classical GA, and 3, 3, and 10 over PSO, respectively. The comparison response time results between simulation and experimental for the studied motors show that the steady state time ratios (SST) were minimized significantly.
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