电惯量模拟缩比系统改进及阻力矩补偿研究
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摘要
在承担的负载模拟项目,进行电惯量模拟研究过程中，已研制了800：1的单轴缩比台架以探讨模拟机理和控制算法。针对缩比台架中控制系统在惯量模拟方面存在的不足,提出改进方案并在DSP上实现。
为了解决缩比台架中单神经元PID控制算法的比例系数K对控制性能影响大且在模拟大惯量时控制性能变差的问题,提出可变论域模糊控制与Bang-Bang控制相结合的混合控制方法,达到改善惯量模拟响应速度和静态性能的目的。利用可变论域模糊控制算法进行精细控制,抑制系统的超调,减小系统的稳态误差；而由Bang-Bang控制迅速减小系统的大偏差,提高响应速度。两者之间采用模糊切换,以消除切换过程中出现的抖动。
针对阻力矩不易测量而导致系统模型辨识不准确的问题,根据做功和能量相互转换的原理,提出基于能量的阻力矩补偿算法,达到修正系统模型的目的。得到阻力矩在前一时间间隔内的能量损耗情况后,在下一时间内通过修正系统模型,实时对阻力矩进行补偿。整个阻力矩补偿过程由迭代计算完成。
鉴于PLC浮点运算能力差,而改进后的控制算法要求实时计算,研制了基于TMS320F2812的DSP控制系统。150MIPS的处理速度和强大的浮点运算能力,有力保障控制算法的实现；通过PCI总线与工控机通信,提高上位机监控程序与DSP控制系统的通信速度。
最后,在缩比台架上进行实验,分别对改进前后的控制系统进行分析对比,验证改进方案的有效性,为整车滚动试验台架的实现提供参考作用。
By studying the electric inertia simulation, an 800:1 reduction ratio of the uniaxial bench used to study the simulation principle and control algorithm, has been developed. Because of the unsatisfied effective of inertia simulation bench, an improvement program is proposed and implemented on DSP.
In the scaled bench, affected by the proportional coefficient K of the single neuron PID control algorithm, control performance becoming worse in the simulation of large inertia. A hybrid control method is proposed which integrates the advantages of variable universe fuzzy control theory and Bang-Bang control theory, to improve the response speed and static performance during inertia simulation. On the use of variable universe fuzzy control algorithm to suppress overshoot of the system, reduce steady-state error; and using Bang-Bang control theory to reduce rapidly the system's large deviations and improve the response speed. The fuzzy switching is used for eliminating the jitter caused by switching.
The system identification result is not accurate because the resistance moment is difficult to measure. According to the conversion between power and energy, we propose resistance moment compensation algorithm based on energy to amend system model. According to the energy loss of resistance moment in the previous process, the resistance is compensated real-timely in the next process. The whole compensation process for resistance moment is completed by the iterative calculation.
Taking into account PLC's poor floating-point operations and improved control algorithm requires real-time computing, a new control system is developed based on TMS320F2812. The control algorithm is successfully implemented because of the DSP chip owns 150MIPS processing speed and a powerful floating-point computing performance; PCI bus is used to improve the communication speed between DSP and IPC.
Finally, comparative analysis about the improved control system and old system is done in scaled bench to verify the effectiveness of the improved scheme, which can provide reference rolling test bed for the motor car.
为了解决缩比台架中单神经元PID控制算法的比例系数K对控制性能影响大且在模拟大惯量时控制性能变差的问题,提出可变论域模糊控制与Bang-Bang控制相结合的混合控制方法,达到改善惯量模拟响应速度和静态性能的目的。利用可变论域模糊控制算法进行精细控制,抑制系统的超调,减小系统的稳态误差；而由Bang-Bang控制迅速减小系统的大偏差,提高响应速度。两者之间采用模糊切换,以消除切换过程中出现的抖动。
针对阻力矩不易测量而导致系统模型辨识不准确的问题,根据做功和能量相互转换的原理,提出基于能量的阻力矩补偿算法,达到修正系统模型的目的。得到阻力矩在前一时间间隔内的能量损耗情况后,在下一时间内通过修正系统模型,实时对阻力矩进行补偿。整个阻力矩补偿过程由迭代计算完成。
鉴于PLC浮点运算能力差,而改进后的控制算法要求实时计算,研制了基于TMS320F2812的DSP控制系统。150MIPS的处理速度和强大的浮点运算能力,有力保障控制算法的实现；通过PCI总线与工控机通信,提高上位机监控程序与DSP控制系统的通信速度。
最后,在缩比台架上进行实验,分别对改进前后的控制系统进行分析对比,验证改进方案的有效性,为整车滚动试验台架的实现提供参考作用。
By studying the electric inertia simulation, an 800:1 reduction ratio of the uniaxial bench used to study the simulation principle and control algorithm, has been developed. Because of the unsatisfied effective of inertia simulation bench, an improvement program is proposed and implemented on DSP.
In the scaled bench, affected by the proportional coefficient K of the single neuron PID control algorithm, control performance becoming worse in the simulation of large inertia. A hybrid control method is proposed which integrates the advantages of variable universe fuzzy control theory and Bang-Bang control theory, to improve the response speed and static performance during inertia simulation. On the use of variable universe fuzzy control algorithm to suppress overshoot of the system, reduce steady-state error; and using Bang-Bang control theory to reduce rapidly the system's large deviations and improve the response speed. The fuzzy switching is used for eliminating the jitter caused by switching.
The system identification result is not accurate because the resistance moment is difficult to measure. According to the conversion between power and energy, we propose resistance moment compensation algorithm based on energy to amend system model. According to the energy loss of resistance moment in the previous process, the resistance is compensated real-timely in the next process. The whole compensation process for resistance moment is completed by the iterative calculation.
Taking into account PLC's poor floating-point operations and improved control algorithm requires real-time computing, a new control system is developed based on TMS320F2812. The control algorithm is successfully implemented because of the DSP chip owns 150MIPS processing speed and a powerful floating-point computing performance; PCI bus is used to improve the communication speed between DSP and IPC.
Finally, comparative analysis about the improved control system and old system is done in scaled bench to verify the effectiveness of the improved scheme, which can provide reference rolling test bed for the motor car.
引文
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