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Hopf Bifurcation Research of Hydraulic Turbine Governing System with a saturation nonlinearity

Journal of Harbin Institute of Technology(New Series) 2016年第6期23卷 54-60页

作者： Qijuan Chen Haifeng Guo Junyi Li Power and Mechanical Engineering Wuhan University

A nonlinear mathematical model for hydro turbine governing system with saturation nonlinearity in small perturbation has been proposed with all the essential components,i.e. turbine,PID type governor with saturation part and generator included in the model. Existence,stability and direction of Hopf bifurcation of an example HTGS are investigated in detail and presented in forms of bifurcation diagrams and time waveforms. The analysis show that a supercritical Hopf bifurcation may exist in hydraulic turbine systems in some certain conditions. Moreover,the dynamic behavior of system with different parameters such as Tw,Tab,Tyand K are studied extensively. An example with numerical simulations is presented to illustrate the theoretical results. The researches provide a reasonable explanation for the Hopf phenomenon happened in operation of hydroelectric generating unit.

关键词： hydro turbine governing system saturation nonlinearity supercritical Hopf bifurcation dynamic behavior

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Recursive Forgetting Factor Stochastic Gradient Estimation Algorithm for Wiener Systems with saturation nonlinearity

Recursive Forgetting Factor Stochastic Gradient Estimation A...

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第32届中国过程控制会议(CPCC2021)

作者： Junxia Ma Wenfeng Pan Yanjun Liu Weili Xiong Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) School of Internet of Things EngineeringJiangnan University

In this paper,the problem of the parameter estimation for Wiener systems with saturation nonlinearity is considered.Stochastic gradient(SG) and modified stochastic gradient identification algorithms are developed.Due to the special structure of the saturation nonlinearity,a switching function is employed to transform the expression of the nonlinearity so that all the unknown parameters are included in one vector.Then the system model is transformed as a regression form.In order to obtain the unknown intermediate variables,the auxiliary model technique is applied to construct an auxiliary model and then the unknown inner variables in the information vector are replaced with the outputs of the auxiliary model.To improve the convergence rate of the SG algorithm,an auxiliary model-based variable forgetting factor SG algorithm is proposed.By assigning a variable forgetting factor,the proposed algorithm can generate more accurate parameter estimates and owns faster convergence rate than the traditional SG algorithm.The numerical simulation example is provided to further verify the effectiveness of the proposed algorithms.

关键词： Parameter Estimation Stochastic Gradient saturation nonlinearity Variable Forgetting Factor

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