船用核动力装置二回路系统预测控制方法研究
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摘要
一体化核动力装置二回路系统,由于强耦合、非线性和动态特性不同等特性,使其控制系统的设计具有一定的挑战性。随着核动力系统自动化程度的提高以及近年来数字设备的可靠性和性能日趋成熟,核动力系统的控制和仪表开始逐渐采用数字设备和网络技术,这使新的控制算法在核动力系统中的应用成为可能。预测控制作为近年来发展起来的一类新型控制算法,由于该方法对实际系统数学模型的依赖性弱、控制综合效果好等诸多优点,使其在核动力系统的应用中受到关注。为此,本文在深入研究核动力装置特性的基础上,对其建模和预测控制方法进行了研究。
在研究了直流蒸汽发生器的结构和换热等特点基础上,应用可移动边界,集总参数法,根据质量、能量和动量守恒方程,建立了直流蒸汽发生器的数学模型,并对其进行了动静态特性仿真研究,这些研究是实现核动力装置二回路系统控制的基础。
基于一体化核动力装置的特点,在直流蒸汽发生器和汽轮机等模型基础上,建立了核动力装置二回路的仿真系统,并对其动态特性进行仿真研究,揭示了其内在固有的特性。在此基础上,根据蒸汽发生器出口蒸汽压力恒定方案,对核动力装置二回路的非线性模型预测协调控制方法进行了研究。结果表明,在负荷动态变化过程中,尤其在大负荷变化时,二回路系统各主要参数(蒸汽发生器出口蒸汽压力和汽轮机功率)波动较大,这对核动力装置二回路系统在变负荷运行的安全性不利。
针对非线性模型预测协调控制方法解决核动力装置变工况及耦合性问题的能力不足,在预测控制算法基础上,应用模糊控制机理,给出了汽轮机转速和蒸汽发生器出口蒸汽压力的多变量模糊预测模型,实现了模糊辨识与预测控制的结合,据此给出了核动力装置二回路系统的多变量模糊模型预测控制方法。仿真结果表明,与非线性模型预测协调控制系统相比,多变量模糊模型预测控制系统获得了更好的控制性能。
由于核动力系统存在严重的耦合性与非线性,并且各设备的动态特性不同,为此,引入将人工神经网络模型与多变量线性预测模型相结合的集成模型,对预测模型进行动态优化,给出了核动力装置二回路多变量集成模型预测控制方法。仿真结果表明,在变工况特别是大负荷变化时,其表现出良好的控制性能,从而,证明了此种方法的可行性。但在控制过程中出现短暂的幅值较大的波动。
针对核动力装置二回路多变量集成模型预测控制过程中存在波动的缺点,引入模糊理论,建立核动力装置二回路控制系统输入量的模糊控制性能评价表,通过模糊决策选择最优输入量,实现了多变量集成模型模糊预测控制。仿真结果表明,应用多变量集成模型模糊预测控制系统后,减小了控制系统输出波动的幅度,取得了更好的控制性能。从而保证了核动力装置安全可靠地运行。
The control of the secondary system of the integrated nuclear power plant is challenging since 1) the control is a multi-objective task for which many manipulated variables are coordinated to achieve satisfactory plant transients; 2) the system is a nonlinear system; 3) the dynamic characteristics of the plant change with operating conditions. With the performance of digital devices is improved, digital devices and network technology is applied into the control system of nuclear power system, which makes advanced control arithmetic applying into the nuclear power system turn true. The predictive control is advanced control arithmetic of late years. It is noticed with its low depend on the real system math model and the well control result in the nuclear power system. Therefore, in the basis of studying deeply characteristic of the integrated nuclear power plant, modeling and predictive control of the integrated nuclear-powered system are researched in this paper.
In the basis of researching the structure and heat transfer features of once-through steam generator, and then according to the mass, energy and momentum balance equation, the steam generator's model is built by lumped parameters with moving boundary. With the built model, static and dynamic characteristics are analyzed. Accomplishing control system of the secondary system of the integrated nuclear power plant base these researches.
Aimed at the specialty of the integrated nuclear power plant, in the basis of the built once-through steam generator and turbine model, simulation system of the secondary system of the integrated nuclear power plant is built. The analysis of dynamic characteristic shows the intrinsic features. By the invariableness project of the pressure of outlet steam, the nonlinear model predictive coordinated control arithmetic is applied into the secondary system of the integrated nuclear power plant. The simulation results show the parameters of system fluctuate more greatly during dynamic variety of load, especially operating over a wide power range, which is not in favor of the security of nuclear power plant.
Aimed at nonlinear model predictive coordinated control arithmetic is lack of solving coupling and variety of load, in the base of predictive control arithmetic, the turbine speed and outlet steam pressure multi-variable fuzzy model predictive model is designed applying fuzzy control theory, which synthesizes the fuzzy recognition and predictive control arithmetic, and then multi-variable fuzzy model predictive control system is gotten. Compare with nonlinear model predictive coordinated control system, the simulation results show that multi-variable fuzzy model predictive control improves performance of control of the secondary system of the integrated nuclear power plant.
Because of serious coupling, nonlinearity and different dynamic characteristic, the multi-variable predictive control of the secondary system of the integrated nuclear power plant based on the integration model is presented. It synthesizes the artificial neural networks model and multi-variable linear predictive model which ameliorates the predictive model in line. The simulation results show that it improve the control capability of the whole system during dynamic variety of load, especially operating over a wide power range. Thereby, the feasibility of this control arithmetic is proved. But there is fluctuation in the control course.
Aimed at the lack of being fluctuation in the multi-variable nonlinear predictive control based on the integration model, the multi-variable fuzzy predictive control of the secondary system of the integrated nuclear power plant based on the integration model is designed applying fuzzy theory, which built the fuzzy control capability evaluate form of the input of the control system, selected the best input during fuzzy decision. The simulation results show that the multi-variable fuzzy predictive control based on the integration model improves briefly the dynamic feature of the secondary system of the integrated nuclear power plant and reduced the breadth of the fluctuation of the control system.
在研究了直流蒸汽发生器的结构和换热等特点基础上,应用可移动边界,集总参数法,根据质量、能量和动量守恒方程,建立了直流蒸汽发生器的数学模型,并对其进行了动静态特性仿真研究,这些研究是实现核动力装置二回路系统控制的基础。
基于一体化核动力装置的特点,在直流蒸汽发生器和汽轮机等模型基础上,建立了核动力装置二回路的仿真系统,并对其动态特性进行仿真研究,揭示了其内在固有的特性。在此基础上,根据蒸汽发生器出口蒸汽压力恒定方案,对核动力装置二回路的非线性模型预测协调控制方法进行了研究。结果表明,在负荷动态变化过程中,尤其在大负荷变化时,二回路系统各主要参数(蒸汽发生器出口蒸汽压力和汽轮机功率)波动较大,这对核动力装置二回路系统在变负荷运行的安全性不利。
针对非线性模型预测协调控制方法解决核动力装置变工况及耦合性问题的能力不足,在预测控制算法基础上,应用模糊控制机理,给出了汽轮机转速和蒸汽发生器出口蒸汽压力的多变量模糊预测模型,实现了模糊辨识与预测控制的结合,据此给出了核动力装置二回路系统的多变量模糊模型预测控制方法。仿真结果表明,与非线性模型预测协调控制系统相比,多变量模糊模型预测控制系统获得了更好的控制性能。
由于核动力系统存在严重的耦合性与非线性,并且各设备的动态特性不同,为此,引入将人工神经网络模型与多变量线性预测模型相结合的集成模型,对预测模型进行动态优化,给出了核动力装置二回路多变量集成模型预测控制方法。仿真结果表明,在变工况特别是大负荷变化时,其表现出良好的控制性能,从而,证明了此种方法的可行性。但在控制过程中出现短暂的幅值较大的波动。
针对核动力装置二回路多变量集成模型预测控制过程中存在波动的缺点,引入模糊理论,建立核动力装置二回路控制系统输入量的模糊控制性能评价表,通过模糊决策选择最优输入量,实现了多变量集成模型模糊预测控制。仿真结果表明,应用多变量集成模型模糊预测控制系统后,减小了控制系统输出波动的幅度,取得了更好的控制性能。从而保证了核动力装置安全可靠地运行。
The control of the secondary system of the integrated nuclear power plant is challenging since 1) the control is a multi-objective task for which many manipulated variables are coordinated to achieve satisfactory plant transients; 2) the system is a nonlinear system; 3) the dynamic characteristics of the plant change with operating conditions. With the performance of digital devices is improved, digital devices and network technology is applied into the control system of nuclear power system, which makes advanced control arithmetic applying into the nuclear power system turn true. The predictive control is advanced control arithmetic of late years. It is noticed with its low depend on the real system math model and the well control result in the nuclear power system. Therefore, in the basis of studying deeply characteristic of the integrated nuclear power plant, modeling and predictive control of the integrated nuclear-powered system are researched in this paper.
In the basis of researching the structure and heat transfer features of once-through steam generator, and then according to the mass, energy and momentum balance equation, the steam generator's model is built by lumped parameters with moving boundary. With the built model, static and dynamic characteristics are analyzed. Accomplishing control system of the secondary system of the integrated nuclear power plant base these researches.
Aimed at the specialty of the integrated nuclear power plant, in the basis of the built once-through steam generator and turbine model, simulation system of the secondary system of the integrated nuclear power plant is built. The analysis of dynamic characteristic shows the intrinsic features. By the invariableness project of the pressure of outlet steam, the nonlinear model predictive coordinated control arithmetic is applied into the secondary system of the integrated nuclear power plant. The simulation results show the parameters of system fluctuate more greatly during dynamic variety of load, especially operating over a wide power range, which is not in favor of the security of nuclear power plant.
Aimed at nonlinear model predictive coordinated control arithmetic is lack of solving coupling and variety of load, in the base of predictive control arithmetic, the turbine speed and outlet steam pressure multi-variable fuzzy model predictive model is designed applying fuzzy control theory, which synthesizes the fuzzy recognition and predictive control arithmetic, and then multi-variable fuzzy model predictive control system is gotten. Compare with nonlinear model predictive coordinated control system, the simulation results show that multi-variable fuzzy model predictive control improves performance of control of the secondary system of the integrated nuclear power plant.
Because of serious coupling, nonlinearity and different dynamic characteristic, the multi-variable predictive control of the secondary system of the integrated nuclear power plant based on the integration model is presented. It synthesizes the artificial neural networks model and multi-variable linear predictive model which ameliorates the predictive model in line. The simulation results show that it improve the control capability of the whole system during dynamic variety of load, especially operating over a wide power range. Thereby, the feasibility of this control arithmetic is proved. But there is fluctuation in the control course.
Aimed at the lack of being fluctuation in the multi-variable nonlinear predictive control based on the integration model, the multi-variable fuzzy predictive control of the secondary system of the integrated nuclear power plant based on the integration model is designed applying fuzzy theory, which built the fuzzy control capability evaluate form of the input of the control system, selected the best input during fuzzy decision. The simulation results show that the multi-variable fuzzy predictive control based on the integration model improves briefly the dynamic feature of the secondary system of the integrated nuclear power plant and reduced the breadth of the fluctuation of the control system.
引文
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