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模型预测控制(Model Predictive Control,MPC)亦称预测控制,是一种基于模型的先进控制技术,该算法直接产生于工业过程控制的实际应用,并在与工业应用的紧密结合中不断完善和成熟。模型预测控制对模型精度要求不高,对模型失配、非最小相位系统、不确定干扰的影响具有较强的鲁棒性，具有较高的控制性能。动态矩阵控制则是模型预测控制中的一种典型的控制算法，将传统自校正技术的单步预测扩展为多步预测，在实际反馈信息基础上反复优化，从而有效地 抑制了算法对于模型参数变化的灵敏性，对建模误差和环境干扰等不确定性具有很强的适应能力。 但是由于动态矩阵控制设计通常基于一个较低阶的线性近似模型，而复杂的工业过程，在模型阶次、非线性、环境扰动、时延等方面存在较大不确定性，因而研究动态矩阵控制的改进，探讨参数设计对其鲁棒性的影响具有重要的理论意义与实际应用价值。本文主要提出了PID-DMC控制算法。由于PID控制原理简单，直观易懂，易于工程实现，鲁棒性强，适用面广，仍然是工业过程控制中应用最广泛的一类基本控制律。然而，实际的生产过程也往往具有非线性、时变不确定性，应用常规PID控制不能达到理想的控制效果。因此，本文在分析PID算法和动态矩阵控制算法的基础上，推导了PID动态矩阵控制算法(PID-DMC)。 由于基函数概念的引入，预测函数控制量的输入有明显的规律性，提高了系统的控制精度。对于一阶加纯滞后的预测函数控制系统的仿真说明，预测函数控制响应速度快，而且增强了系统的抗干扰能力、鲁棒性和稳定性。 关键词： 预测控制；动态矩阵算法；参数设定；PID-DMC;预测函数 [ Last edited by 莘菲晶晶521 on 2009-4-16 at 18:18 ] |
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2楼2009-04-20 11:22:08
仅供参考
★ ★ ★ ★ ★ ★ ★ ★ ★ ★
莘菲晶晶521(金币+10,VIP+0):其实已经过期了，还是感谢 5-14 10:37
莘菲晶晶521(金币+10,VIP+0):其实已经过期了，还是感谢 5-14 10:37
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Model predictive control (Model Predictive Control, MPC), also known as predictive control, is an advanced model-based control technology, the algorithm directly from the actual industrial process control applications, and industrial applications with the close integration of continuous improvement and maturity .Model predictive control the accuracy of the model do not ask for much on the model mismatch, non-minimum phase systems, the impact of uncertain interference robustness, higher performance. Dynamic matrix control is model predictive control of a typical control algorithm, the traditional self-tuning technology, the expansion of single-step prediction for the multi-step prediction, the actual basis of repeated feedback optimization, in order to effectively curb the algorithm for model parameters changes in sensitivity to modeling errors and uncertainties, such as environmental interference has a strong adaptability. However, due to the design of dynamic matrix control is usually based on a low-order linear approximation model, and complex industrial processes, in the model order, nonlinearity, environmental perturbations, and so there is a big time delay uncertainty, and thus research Improved matrix control to explore the parameters of the design robustness of the impact of its great theoretical significance and practical application value.In this paper, a PID-DMC control algorithm. As a result of PID control theory is simple, intuitive and easy to understand, easy to work to achieve robustness for a wide range of industrial process control is still the most widely used basic control law for a class. However, the actual production process is often non-linear, time-varying uncertainty, the application of conventional PID control can not achieve the desired control effect.Therefore, PID algorithm and the analysis of dynamic matrix control algorithm based on dynamic matrix derived PID control algorithm (PID-DMC). As a result of the introduction of the concept of basis functions, the amount of predictive functional control of the regularity of a clear input to improve the control accuracy of the system. For first-order plus time delay system of predictive functional control of the simulation show that predictive functional control in response to fast and enhanced system of anti-interference ability, robustness and stability. Key words: predictive control; dynamic matrix algorithm; parameters; PID-DMC; forecast function |
3楼2009-04-20 12:37:51
★ ★ ★ ★ ★ ★ ★ ★ ★ ★
莘菲晶晶521(金币+10,VIP+0):很感谢，其实我当时要的很急，回答得已经晚了 5-14 10:37
莘菲晶晶521(金币+10,VIP+0):很感谢，其实我当时要的很急，回答得已经晚了 5-14 10:37
|
Model predictive control (Model Predictive Control, MPC), also known as predictive control, is an advanced model-based control technology, the algorithm directly from the actual industrial process control applications, and industrial applications with the close integration of continuous improvement and maturity . Model predictive control the accuracy of the model do not ask for much on the model mismatch, non-minimum phase systems, the impact of uncertain interference robustness, higher performance. Dynamic matrix control is model predictive control of a typical control algorithm, the traditional self-tuning technology, the expansion of single-step prediction for the multi-step prediction, the actual basis of repeated feedback optimization, in order to effectively Inhibition of the algorithm parameters for the model sensitivity to modeling errors and uncertainties, such as environmental interference has a strong adaptability. However, due to the design of dynamic matrix control is usually based on a low-order linear approximation model, and complex industrial processes, in the model order, nonlinearity, environmental perturbations, and so there is a big time delay uncertainty, and thus research Improved matrix control to explore the parameters of the design robustness of the impact of its great theoretical significance and practical application value. In this paper, a PID-DMC control algorithm. As a result of PID control theory is simple, intuitive and easy to understand, easy to work to achieve robustness for a wide range of industrial process control is still the most widely used basic control law for a class. However, the actual production process is often non-linear, time-varying uncertainty, the application of conventional PID control can not achieve the desired control effect. Therefore, PID algorithm and the analysis of dynamic matrix control algorithm based on dynamic matrix derived PID control algorithm (PID-DMC). As a result of the introduction of the concept of basis functions, the amount of predictive functional control of the regularity of a clear input to improve the control accuracy of the system. For first-order plus time delay system of predictive functional control of the simulation show that predictive functional control in response to fast and enhanced system of anti-interference ability, robustness and stability. Key words: predictive control; dynamic matrix algorithm; parameters; PID-DMC; forecast function |
4楼2009-04-21 23:23:40