The local multiple regression fuzzy(LMRF)model based on Takagi-Sugeno fuzzy logical system and its application in traffic forecasting is proposed. Besides its prediction accuracy is testified and the model is proved m...The local multiple regression fuzzy(LMRF)model based on Takagi-Sugeno fuzzy logical system and its application in traffic forecasting is proposed. Besides its prediction accuracy is testified and the model is proved much better than conventional forecasting methods. According to the regional traffic system, the model perfectly states the complex non-linear relation of the traffic and the local social economy. The model also efficiently deals with the system lack of enough data.展开更多
In this paper, the output consensus problem of general heterogeneous nonlinear multi-agent systems subject to different disturbances is considered. A kind of Takagi-Sukeno fuzzy modeling method is used to describe the...In this paper, the output consensus problem of general heterogeneous nonlinear multi-agent systems subject to different disturbances is considered. A kind of Takagi-Sukeno fuzzy modeling method is used to describe the nonlinear agents' dynamics. Based on the model, a distributed fuzzy observer and controller are designed based on parallel distributed compensation scheme and internal reference models such that the heterogeneous nonlinear multi-agent systems can achieve output consensus. Then a necessary and sufficient condition is presented for the output consensus problem. And it is shown that the consensus trajectory of the global fuzzy model is determined by the network topology and the initial states of the internal reference models. Finally, some simulations are given to illustrate and verify the effectiveness of the proposed scheme.展开更多
To improve the control performance of nonlinear ultra-supercritical(USC)thermal power units,an improved min-max fuzzy model predictive tracking control(FMPTC)strategy is proposed.First,a T-S fuzzy model is established...To improve the control performance of nonlinear ultra-supercritical(USC)thermal power units,an improved min-max fuzzy model predictive tracking control(FMPTC)strategy is proposed.First,a T-S fuzzy model is established to approximate the dynamics of the nonlinear boiler-turbine system.Then,based on an extended fuzzy model containing state variables and output variables,a min-max FMPTC is derived for output regulation while ensuring the closed-loop system stability and the inputs in their given constraints.For greater controller design freedom,the developed controller adopts a new state-and output-based objective function.In addition,the observer estimation error is regarded as a bounded disturbance,ensuring the stability of the entire closed-loop control system.Simulation results on a 1000 MW USC boiler-turbine model illustrate the effectiveness of the proposed approach.展开更多
文摘The local multiple regression fuzzy(LMRF)model based on Takagi-Sugeno fuzzy logical system and its application in traffic forecasting is proposed. Besides its prediction accuracy is testified and the model is proved much better than conventional forecasting methods. According to the regional traffic system, the model perfectly states the complex non-linear relation of the traffic and the local social economy. The model also efficiently deals with the system lack of enough data.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.61375105 and 61403334Chinese Postdoctoral Science Fundation under Grant No.2015M581318
文摘In this paper, the output consensus problem of general heterogeneous nonlinear multi-agent systems subject to different disturbances is considered. A kind of Takagi-Sukeno fuzzy modeling method is used to describe the nonlinear agents' dynamics. Based on the model, a distributed fuzzy observer and controller are designed based on parallel distributed compensation scheme and internal reference models such that the heterogeneous nonlinear multi-agent systems can achieve output consensus. Then a necessary and sufficient condition is presented for the output consensus problem. And it is shown that the consensus trajectory of the global fuzzy model is determined by the network topology and the initial states of the internal reference models. Finally, some simulations are given to illustrate and verify the effectiveness of the proposed scheme.
基金The National Natural Science Foundation of China(No.51936003).
文摘To improve the control performance of nonlinear ultra-supercritical(USC)thermal power units,an improved min-max fuzzy model predictive tracking control(FMPTC)strategy is proposed.First,a T-S fuzzy model is established to approximate the dynamics of the nonlinear boiler-turbine system.Then,based on an extended fuzzy model containing state variables and output variables,a min-max FMPTC is derived for output regulation while ensuring the closed-loop system stability and the inputs in their given constraints.For greater controller design freedom,the developed controller adopts a new state-and output-based objective function.In addition,the observer estimation error is regarded as a bounded disturbance,ensuring the stability of the entire closed-loop control system.Simulation results on a 1000 MW USC boiler-turbine model illustrate the effectiveness of the proposed approach.
