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预测函数控制及其在火电厂中的应用研究

Predictive Functional Control and Its Application Research in Thermal Power Plant

【作者】 王国玉

【导师】 韩璞;

【作者基本信息】 华北电力大学(河北) , 热能工程, 2004, 博士

【摘要】 本文首先对预测控制(MPC)进行了简要概述,特别关注了预测函数控制(PFC),MPC在火电厂中的应用现状,以及研究热点之一的分布式预测控制。介绍了PFC的基本原理,推导了一阶加纯滞后系统PFC算法。根据PFC的基本原理,结合前人的研究结果,提出了新型PFC算法和控制策略,使得PFC系统的设计更加方便,并进一步提高了PFC系统性能。基于易于测取的有限脉冲响应(FIR)模型,推导了一种新型PFC算法,给出了采用一个基函数(阶跃函数)和两个基函数(阶跃函数、斜坡函数)两种情形下的控制律的解析解,并分析了闭环系统稳态特性,结果表明,系统对于设定值变化和输出扰动均无余差。该算法适用于开环稳定系统。针对非自衡对象,基于易于测取的阶跃响应模型,提出了非自衡对象PFC增量型算法,给出了控制律的解析解,并分析了闭环系统稳态性能,结果表明,系统对于设定值变化、输入和输出阶跃扰动均无余差。针对只存在右半平面极点(开环不稳定)的非最小相位系统,设计PD反馈补偿器,将PD反馈补偿环节和被控对象组成的回路视为广义被控对象,并采用一阶加纯滞后系统PFC算法对其实施控制,仿真研究表明了该方法的有效性。针对只存在右半平面零点(开环稳定)的非最小相位系统,提出了一种参考轨迹自调整PFC策略,仿真研究显示了该策略的优越性。将PFC应用到火电厂热工过程控制中,并进行了大量的仿真研究,为其工程实际应用打下了坚实的基础。综合了PFC算法和串级控制策略的优点,设计了PFC-PID串级主汽温控制系统,其中,PFC算法分别采用基于一阶加纯滞后系统和基于FIR模型的算法,仿真结果表明,该系统动态品质明显优于采用PID串级控制策略的系统,具有较强的鲁棒性和抗干扰能力。为了克服蒸汽量(负荷)变化对主汽温的影响,在PFC的预测模型中加入蒸汽量扰动下汽温对象模型,提出了具有对负荷变化前馈补偿的主汽温系统PFC策略。根据考虑可测扰动的PFC策略,采用基于一阶加纯滞后系统的PFC算法,推导了控制算法。仿真结果表明,系统克服负荷扰动能力得到了明显提高。为了克服工况变化对主汽温对象动态特性的影响,给出了两种控制策略:主汽温系统多模型PFC策略和主汽温系统模糊自适应PFC策略。其中,第一种策略在若干典型的工作点建立多个固定模型,运行时根据系统工况变化,利用相应的模型进行输出预测,计算控制输出,从而进一步改善采用PFC算法的主汽温系统性能;第二种策略与多模型策略的基本思想一致,但是由于模糊模型的插值机理使得辨识模型的输出有很强的泛化能力,因此,可以用少得多的子模型来反映整个系统<WP=5>的动态特征,且模型与模型之间的切换更加平滑,更为突出的优点是对工况变化的适应性。针对一大类过程通道可用一阶加纯滞后模型等价描述的多输入多输出系统,提出了基于前馈解耦的多变量系统PFC算法,并以双入双出系统为例,给出了解析解。针对某国产200MW火电机组带汽-汽换热器的多变量强耦合汽温系统,应用该算法,进行了仿真研究,结果表明,系统达到了动态近似解耦、静态完全解耦和无静差跟踪,同时具有较强的鲁棒性和抗干扰能力。在分析给水控制对象的动态特征和控制要求的基础上,指出非自衡对象PFC增量型算法能够满足给水控制系统的要求,有望取得成功应用。采用考虑可测扰动的PFC策略和非自衡对象PFC增量型算法,设计了新型给水控制系统。仿真结果表明,系统具有良好的动态特性以及很强的鲁棒性能和抗干扰能力。系统设计简单,控制品质好,具有很大的工程实际应用潜力。将基于FIR模型的PFC算法推广到多变量情形,并考虑了控制输入幅值和速度约束。将其应用到单元机组负荷控制系统,仿真结果表明,系统具有优良的负荷跟踪能力和较强的鲁棒性。最后对全文进行了总结,并指出了PFC理论研究及其在火电厂热工过程控制中的工程实际应用方面有待进一步研究的问题。

【Abstract】 A brief review of Model Predictive Control (MPC) is addressed firstly, which pays much attention to Predictive Functional Control (PFC), applications of MPC in thermal power plant and one of research hotpots, Distributed Model Predictive Control (DMPC). The basic principles of PFC are introduced, and PFC algorithm for first-order plus dead-time system is delivered.According to the basic principles of PFC, combining prevenient research results, novel PFC algorithms and control strategies are presented, which lead to easier design and better performances of PFC systems.A novel PFC algorithm based on Finite Response Impulse (FIR) model is presented. Analytical control laws with both one base function (step function) and two base functions (step and ramp functions) are provided. Closed-loop system steady state performance is discussed, which shows that the control system both has not remnant difference due to the variety of set point and output disturbance. The algorithm is fit for open-loop stable systems.A novel PFC algorithm for integrating plants is presented based on step response model that can be acquired easily. Analytical control law is provided. Closed-loop system steady state performance analysis show that the control system has not remnant difference due to the variety of set point, step disturbances of manipulated variable and output.For the non-minimum phase system that only has right-half plane poles, i.e. the open-loop unstable non-minimum phase system, PD feedback compensator is designed, and the PD feedback compensator and the controlled plant are treated as generalized controlled plant. PFC algorithm for first-order plus dead-time system is applied to control the generalized plant. And simulation results show its availability. Considering the non-minimum phase system that only has right-half plane zeros, i.e. the open-loop stable non-minimum phase system, a novel PFC scheme based on reference trajectory self-tuning is presented, and simulation results demonstrate its superiority.PFC algorithms are applied to thermal processes in thermal power plant, and plenty of simulation researches are carried out, which provides a solid basis for their practical applications.Combining the advantages of PFC algorithms and cascade control strategy, PFC-PID cascade superheated steam temperature systems are designed. The PFC algorithm for first-order plus dead-time system and the PFC algorithm based on FIR model are adopted respectively. Simulation results show that the superheated steam <WP=7>temperature system adopted PFC-PID cascade control strategy has more favorable dynamic characteristics than the system with PID cascade control strategy, and has good robustness and disturbance rejection. In order to overcome the influences of steam flow (load) on superheated steam temperature, PFC strategy with feedforward compensation for load fluctuation is provided in superheated steam temperature system, adding steam flow disturbance model to PFC prediction model. According to PFC scheme taking measurable disturbances into account, control algorithm is presented, adopting PFC algorithm for first-order plus dead-time system. Simulation results show that the system has obvious improvement in load disturbance rejection.In order to get over the influences of operating regime on superheated steam temperature dynamic characteristics, two strategies are provided: multi-model PFC strategy and fuzzy adaptive PFC strategy in superheated steam temperature system. In the first strategy, fixed models are established in some operating regimes, model prediction output is obtained with corresponding model according to system operating regime, and then manipulated input is worked out, thereby the performances of the superheated steam temperature system adopted PFC algorithm are improved once more. The basic idea of the second strategy is same as that of the first strategy. However, identified model output has strong generalization ability because of the interpolation mechanism of fuzzy model, therefore, system dynamic chara

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