多电机伺服系统协同预测控制方法及不确定性扰动抑制

The performance of the cooperative control method is critical to the machining accuracy and response speed of multi-motor servo systems. As a control strategy that could easily deal with multivariable and complex constraints, model predictive control is suitable for building the high-performance cooperative control methods, but there are still many technical gaps to be studied. This project conducts the research about key issues of multi-motor cooperative predictive control method under uncertain disturbance environment. Firstly, the frequency domain accurate modeling method for the disturbances of the multi-motor systems is studied, then the harmonic current generation mechanism in the system is revealed. Secondly, targeting the goal of unified modeling and unified optimization, this project studies the optimization methods of the predictive models and optimization methods, in order to integrate the traditional multi-level closed loop into one control loop. On this basis, this project proposes the "integrated" cooperative predictive control architecture with disturbance suppression capability, which could make sure the efficient interaction between the control information of each motor and realizes the high precision and high dynamic performance operation of the system. Finally, this project compares the variation of control precision and speed in the different cooperative predictive control architectures under various operating conditions, and the stability and robustness of cooperative predictive control method is studied. Furthermore, the cooperative control theory and technical based on model predictive control of the multi-motor system is achieved. The efficient and stable cooperative predictive control method could improve the overall performance and reliability of multi-motor servo systems, and the development of the model predictive control theory in the field of multi-motor control will be promoted.

协同控制方法的性能对多电机伺服系统加工精度和响应速度至关重要。模型预测控制作为一种易于处理多变量、复杂约束问题的控制策略，特别适合构建高性能协同控制方法，但尚有许多问题有待解决。本项目针对不确定扰动下的多电机协同预测控制关键问题进行研究，首先研究多电机系统扰动频域精确建模方法，揭示扰动作用下系统谐波电流的产生机理；然后以统一建模、统一寻优为目标，研究预测模型和寻优方式的优化途径，将传统多级闭环结构整合为一个控制环，提出具备扰动抑制能力的“整合型”多电机协同预测控制架构，保证各电机间的高效信息交互，实现系统高精度、高动态性能运行与控制；最后对比研究不同协同预测控制架构在复杂工况下控制精度、速度等指标的变化情况，分析采用协同预测控制方法的系统稳健性，形成基于模型预测控制的多电机协同控制理论与技术体系。项目的实施将提高多电机伺服系统运行品质，推动模型预测控制理论在多电机控制领域的发展和应用。

在高档数控机床、大型精密转台等国家重大制造设备中，仅含有单台电机的变流系统已经不能适应制造设备对性能和产品质量不断提升的需求，需要采用由多台电机组成的伺服系统进行协同驱动，以达到高精度的生产要求。协同控制方法的性能对多电机伺服系统加工精度和响应速度至关重要。模型预测控制作为一种易于处理多变量、复杂约束问题的控制策略，特别适合构建高性能协同控制方法。本项目针对不确定扰动下的多电机协同预测控制关键问题进行研究，首先研究了多电机系统扰动频域精确建模方法，揭示了扰动作用下系统谐波电流的产生机理；然后以统一建模、统一寻优为目标，研究预测模型和寻优方式的优化途径，将传统多级闭环结构整合为一个控制环，提出具备扰动抑制能力的“整合型”多电机协同预测控制架构，分别设计了具备高效信息交互的力矩/速度/位置多电机协同控制方案，并提出了多电机显式模型预测控制实现方案，所有策略均结合仿真和实验结果进行了详细分析，结果证明了所设计算法的有效性和可行性。最后对比研究了不同协同预测控制架构在复杂工况下控制精度、速度等指标的变化情况，分析了采用协同预测控制方法的系统稳健性，形成基于模型预测控制的多电机协同控制理论与技术体系。项目相关研究成果有助于提高多电机伺服系统对复杂运动轨迹的跟踪能力，推动了模型预测控制理论在伺服控制领域的应用。

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