时滞系统的辨识与控制
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摘要
时滞系统的辨识与控制是工业上经常遇到的问题。由于时滞的存在，使得被控量不能及时反映系统所承受的扰动，产生明显的超调，调节时间变长，控制难度加大。尤其是当被控对象包含不稳定环节时，更加难于控制。针对以上情况，本文提出两种方法，对时滞系统进行控制和辨识。
文章第一部分针对工业控制过程中的时滞不稳定过程，提出改进内模控制(MIMC)设计方法，为避免开环不稳定极点对系统的鲁棒稳定性和抑制扰动能力的影响，对控制器进行了鲁棒稳定性以及抑制扰动能力的分别设计，首先利用反馈方法整定内环的不稳定系统，然后设计前馈反馈控制来抑制被控过程的扰动；最后使用内模控制方法对时滞被控过程进行串级外环控制，以达到对给定值的跟踪。仿真结果表明所提出的控制方法能很好地解决鲁棒稳定性和抑制扰动的均衡，且对于控制系统中过程变化引起的模型失配，可通过调整内模控制器的滤波器时间常数，来提高控制系统的鲁棒性。
文章第二部分介绍了支持向量机原理，并利用支持向量机(SVM)对函数逼近的能力，采用高斯RBF核函数，进行时滞系统的正，逆辨识。同时将内模控制与支持向量机逆辨识结合，提出支持向量机内模控制(SVM—IMC)。首先由支持向量机逆辨识得到逆辨识模型，根据内模控制器设计原理，将辨识模型作为内模控制器，并根据模型的变化进行调整。同时调节滤波器保持系统稳定。仿真结果表明，基于支持向量机的正，逆模型辨识方法在处理时滞被控对象时，辨识精度高，辨识速度快，而且泛化能力较强；支持向量机内模控制，所需样本少，稳定性好，实现简单，是一种具有重要研究价值的方法。
The problem of identification and control for processes with time-delay is always encountered in industry. Because of the time-delay, the controlled processes can not reflect the disturbance of systems in time, and which brings obvious overshoot. In addition, the adjusting time becomes longer and the difficulty of control becomes larger. This paper proposed two methods to solve this problem.
Based on modified internal model control (MIMC) scheme, a control strategy which introduce to the inner-loop control named feedforward-feedback control is proposed in the first part of this paper. The separately design method can be used to design the feedforward-feedback controller for disturbance rejection and the MIMC controller for set-point tracking. Furthermore, a method of choosing the inner-loop controller is applied when normalization of time delay is different. Moreover, by tuning the filter time constant, the robustness is improved when model mismatch between process and plant exits. The results of simulations show good disturbance rejection and robustness of the controller.
The principle of SVM is introduced in the second part of the article, which has performed excellent ability of non-linear function approximation. Thus, the Gauss RBF kernel-based function is applied to identify the positive-model and inverse-model of the processes with time-delay. Combining the IMC with the identification of inverse-model, the internal model controller of SVM (SVM-IMC) is proposed. Firstly, according to the SVM inverse identification, the inverse-model can be acquired. Then using the principle of internal model control, the identification model can be seen as the internal model controller. Moreover, by tuning the filter time constant, the stability of processes can be maintained. Simulation results proved the good performance of SVM which based on positive-model and inverse-model identification, and SVM-IMC in many aspects, including identification precision; identification speed; less dependence on sample, and stronger generalization ability.
文章第一部分针对工业控制过程中的时滞不稳定过程，提出改进内模控制(MIMC)设计方法，为避免开环不稳定极点对系统的鲁棒稳定性和抑制扰动能力的影响，对控制器进行了鲁棒稳定性以及抑制扰动能力的分别设计，首先利用反馈方法整定内环的不稳定系统，然后设计前馈反馈控制来抑制被控过程的扰动；最后使用内模控制方法对时滞被控过程进行串级外环控制，以达到对给定值的跟踪。仿真结果表明所提出的控制方法能很好地解决鲁棒稳定性和抑制扰动的均衡，且对于控制系统中过程变化引起的模型失配，可通过调整内模控制器的滤波器时间常数，来提高控制系统的鲁棒性。
文章第二部分介绍了支持向量机原理，并利用支持向量机(SVM)对函数逼近的能力，采用高斯RBF核函数，进行时滞系统的正，逆辨识。同时将内模控制与支持向量机逆辨识结合，提出支持向量机内模控制(SVM—IMC)。首先由支持向量机逆辨识得到逆辨识模型，根据内模控制器设计原理，将辨识模型作为内模控制器，并根据模型的变化进行调整。同时调节滤波器保持系统稳定。仿真结果表明，基于支持向量机的正，逆模型辨识方法在处理时滞被控对象时，辨识精度高，辨识速度快，而且泛化能力较强；支持向量机内模控制，所需样本少，稳定性好，实现简单，是一种具有重要研究价值的方法。
The problem of identification and control for processes with time-delay is always encountered in industry. Because of the time-delay, the controlled processes can not reflect the disturbance of systems in time, and which brings obvious overshoot. In addition, the adjusting time becomes longer and the difficulty of control becomes larger. This paper proposed two methods to solve this problem.
Based on modified internal model control (MIMC) scheme, a control strategy which introduce to the inner-loop control named feedforward-feedback control is proposed in the first part of this paper. The separately design method can be used to design the feedforward-feedback controller for disturbance rejection and the MIMC controller for set-point tracking. Furthermore, a method of choosing the inner-loop controller is applied when normalization of time delay is different. Moreover, by tuning the filter time constant, the robustness is improved when model mismatch between process and plant exits. The results of simulations show good disturbance rejection and robustness of the controller.
The principle of SVM is introduced in the second part of the article, which has performed excellent ability of non-linear function approximation. Thus, the Gauss RBF kernel-based function is applied to identify the positive-model and inverse-model of the processes with time-delay. Combining the IMC with the identification of inverse-model, the internal model controller of SVM (SVM-IMC) is proposed. Firstly, according to the SVM inverse identification, the inverse-model can be acquired. Then using the principle of internal model control, the identification model can be seen as the internal model controller. Moreover, by tuning the filter time constant, the stability of processes can be maintained. Simulation results proved the good performance of SVM which based on positive-model and inverse-model identification, and SVM-IMC in many aspects, including identification precision; identification speed; less dependence on sample, and stronger generalization ability.
引文
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[3] Li J C, Jron J C. A new learning controller based on the P-integratorconcept[J]. Fuzzy Sets and System, 1992, 48 (3) : 297-303
[4] Hagglund T. A predictive PI controller for process with long deadtime[J]. IEEE Control System Magazine, 1992, 12 (1) : 57-60
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[6] 陈建勤，陈来九．一种新的PID调节器参数自整定方法[J]．控制与决策，1993，8(1)：13-18
[7] 柴天佑，张贵军．基于给定相角裕度和幅值裕度的PID参数自整定新方法[J]．自动化学报，1997，23 (2)：167-172
[8] 汪洋，褚键．一种基于递推参数估计的PID参数自整定方法[J]．信息与控制，1996，3：182-185
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[10] 刘开培．基于Pade逼近的纯滞后系统增益自适应内模PID控制[J]．武汉大学学报，2001，34 (4)：93-95
[11] De Paor A M, O'Malley M. Controllers of Ziegler-Nichols type for unstable process with time delay[J]. Int. J. Control, 1985, 49: 1273-1284.
[12] 仇俊杰，王文海．典型大时变时滞系统神经网络模糊PID控制及应用[J]．化工自动化及仪表，2006，33 (4)：30-32
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