Fuzzy logic control approach is introduced to designthe iterative learning controller,which deals with point-to-pointproblem of nonlinear ***,the nonlinear system isrepresented by a Takagi-Sugeno(TS)type fuzzy ***,bas...
详细信息
Fuzzy logic control approach is introduced to designthe iterative learning controller,which deals with point-to-pointproblem of nonlinear ***,the nonlinear system isrepresented by a Takagi-Sugeno(TS)type fuzzy ***,based on the fuzzy model,a fuzzy iterative learning controller isdeveloped to achieve positioning error convergence via theso-called parallel distributed compensation(PDC)*** can sufficiently utilize clear concepts and simplemethods of linear multivariable control theory in designingnonlinear iterattve learning control system.A simulationexample is given to illustrate the design procedures and theeffectiveness of the fuzzy iterative learning scheme.
Daily activity rhythms of three radio-collared captive red pandas were monitored individually at 15 minute intervals for 3 continuous days each month at Yele Nature Reserve, Xiangling Mountains, June-October 1995. Our...
详细信息
Daily activity rhythms of three radio-collared captive red pandas were monitored individually at 15 minute intervals for 3 continuous days each month at Yele Nature Reserve, Xiangling Mountains, June-October 1995. Our data indicated that mean rate of activity(0.51)of captive red pandas was lower than that of wild red pandas. Three captive red pandas showed similar daily activity patterns, being least active during night and more active during daytime. Mean rate of activity during daylight(0.58)was higher than during nighttime (0.41). Daily mean durations of activity and rest were 12.21 hours and 11.79 hours, respectively. Active times of captive red pandas accounted for 50.6% of each 24 hours, of which 66.5% were recorded during daylight and 33.5% during night. Two active peaks appeared at 07:30-09:15 and 17:30-(19:00). We recorded a mean of 2.17, 2.13 and 0.88 long, mid-length, and short resting bouts daily, which had mean durations of 3.47, 1.65 and 0.87 hour, respectively. Among these long rests, 46.1% occurred during daytime and 53.8% during nighttime.
Fuzzy logic control approach is introduced to design the iterative learning controller, which deals with point-to-point problem of nonlinear system. First, the nonlinear system is represented by a Takagi-Sugeno (TS) t...
详细信息
Fuzzy logic control approach is introduced to design the iterative learning controller, which deals with point-to-point problem of nonlinear system. First, the nonlinear system is represented by a Takagi-Sugeno (TS) type fuzzy model. Second, based on the fuzzy model, a fuzzy iterative learning controller is developed to achieve positioning error convergence via the so-called parallel distributed compensation (PDC) scheme. The approach can sufficiently utilize clear concepts and simple methods of linear multivariable control theory in designing nonlinear iterative learning control system. A simulation example is given to illustrate the design procedures and the effectiveness of the fuzzy iterative learning scheme.
Tracking control designs are important issues for practical applications. Combining iterative learning control theory with Takagi-Sugeno (TS) fuzzy methodology, a fuzzy iterative learning control design method is desc...
详细信息
ISBN:
(纸本)0780384032
Tracking control designs are important issues for practical applications. Combining iterative learning control theory with Takagi-Sugeno (TS) fuzzy methodology, a fuzzy iterative learning control design method is described for output tracking of nonlinear discrete-time system. First, the TS fuzzy model is employed to approximate a nonlinear discrete-time system. Next, a model-based fuzzy iterative learning controller is developed to guarantee the convergence of the tracking error. The proposed approach can sufficiently utilize clear concepts and simple methods of iterative learning control theory to improve system tracking performance. A simulation example is provided to illustrate the design procedures and the effectiveness of the fuzzy iterative learning controller.
The fuzzy logic control approach is introduced to design the iterative learning controller, which deals with point-to-point problem of nonlinear system. First, the nonlinear system is represented by a Takagi-Sugeno (T...
详细信息
ISBN:
(纸本)0780382730
The fuzzy logic control approach is introduced to design the iterative learning controller, which deals with point-to-point problem of nonlinear system. First, the nonlinear system is represented by a Takagi-Sugeno (TS) type fuzzy model. Second, based on the fuzzy model, a fuzzy iterative learning controller is developed to achieve positioning error convergence via the so-called parallel distributed compensation (PDC) scheme. The approach can sufficiently utilize clear concepts and simple methods of linear multivariable control theory in designing nonlinear iterative learning control system. A simulation example is given to illustrate the design procedures and the effectiveness of the fuzzy iterative learning scheme.
In order to obtain large broadband, a novel travelling-wave modulator with nonperiodic domain inversions and ridge structure is proposed. The composite structure is designed to achieve velocity matching between the op...
详细信息
In order to obtain large broadband, a novel travelling-wave modulator with nonperiodic domain inversions and ridge structure is proposed. The composite structure is designed to achieve velocity matching between the optical wave and the microwave, to get a 50Ω characteristic impedance and to reduce the loss of the microwave electrodes with finite element method (FEM). The calculation results show that the frequency response of the new device is flat up to 350 GHz with interaction length of 1 cm, characteristic impedance of 49Ω, and microwave refractive index of 2.5.
Tracking control designs are important issues for practical applications. Combining iterative learning control theory with Takagi-Sugeno (TS) fuzzy methodology, a fuzzy iterative learning control design method is desc...
详细信息
ISBN:
(纸本)0780384032
Tracking control designs are important issues for practical applications. Combining iterative learning control theory with Takagi-Sugeno (TS) fuzzy methodology, a fuzzy iterative learning control design method is described for output tracking of nonlinear discrete-time system. First, the TS fuzzy model is employed to approximate a nonlinear discrete-time system. Next, a model-based fuzzy iterative learning controller is developed to guarantee the convergence of the tracking error. The proposed approach can sufficiently utilize clear concepts and simple methods of iterative learning control theory to improve system tracking performance. A simulation example is provided to illustrate the design procedures and the effectiveness of the fuzzy iterative learning controller.
暂无评论