The Tianma 65 m radio telescope(TMRT)at Shanghai is a fully steerable single-dish radio telescope in China,operating at centimeter to millimeter wavelengths(1.25 GHz to 50 GHz).This paper presents details on the main ...The Tianma 65 m radio telescope(TMRT)at Shanghai is a fully steerable single-dish radio telescope in China,operating at centimeter to millimeter wavelengths(1.25 GHz to 50 GHz).This paper presents details on the main specifications,design,performance analysis,testing,and construction of the telescope antenna.The measured total efficiency is better than 50%over the whole elevation angle range,first sidelobe levels are less than−20 dB,antenna system noise temperatures are less than 70 K at 30°elevation angle,and pointing accuracy is less than 3″.The measured and calculated results are in good agreement,verifying the effectiveness of the design and analysis.展开更多
Purpose–Micro aerial vehicle is nonlinear plant;it is difficult to obtain stable control for MAV attitude due to uncertainties.The purpose of this paper is to propose one robust stable control strategy for MAV to acc...Purpose–Micro aerial vehicle is nonlinear plant;it is difficult to obtain stable control for MAV attitude due to uncertainties.The purpose of this paper is to propose one robust stable control strategy for MAV to accommodate system uncertainties,variations,and external disturbances.Design/methodology/approach–First,by employing interval type-II fuzzy neural network(ITIIFNN)to approximate the nonlinearity function and uncertainty functions in the attitude angle dynamic model of micro aircraft vehicle(MAV).Then,the Lyapunov stability theorem is used to testify the asymptotic stability of the closed-loop system,the parameters of the ITIIFNN and gain of sliding mode control can be tuned on-line by adaptive laws based on Lyapunov synthesis approach,and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system.Findings–The validity of the proposed control method has been verified through real-time experiments.The experimental results show that the performance of interval type-II fuzzy neural network based gain adaptive sliding mode controller(GASMC-ITIIFNN)is significantly improved compared with conventional adaptive sliding mode controller(CASMC),type-I fuzzy neural network based sliding mode controller(GASMC-TIFNN).Practical implications–This approach has been used in one MAV,the controller works well,and which could guarantee the MAV control system with good performances under uncertainties,variations,and external disturbances.Originality/value–The main original contributions of this paper are:the proposed control scheme makes full use of the nominal model of the MAV attitude control model;the overall closed-loop control system is globally stable demonstrated by Lyapunov stable theory;the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates;and the MAV attitude control system based on GASMC-ITIIFNN controller can achieve favourable tracking performance than GASMC-TIFNN and CASMC.展开更多
文摘The Tianma 65 m radio telescope(TMRT)at Shanghai is a fully steerable single-dish radio telescope in China,operating at centimeter to millimeter wavelengths(1.25 GHz to 50 GHz).This paper presents details on the main specifications,design,performance analysis,testing,and construction of the telescope antenna.The measured total efficiency is better than 50%over the whole elevation angle range,first sidelobe levels are less than−20 dB,antenna system noise temperatures are less than 70 K at 30°elevation angle,and pointing accuracy is less than 3″.The measured and calculated results are in good agreement,verifying the effectiveness of the design and analysis.
文摘Purpose–Micro aerial vehicle is nonlinear plant;it is difficult to obtain stable control for MAV attitude due to uncertainties.The purpose of this paper is to propose one robust stable control strategy for MAV to accommodate system uncertainties,variations,and external disturbances.Design/methodology/approach–First,by employing interval type-II fuzzy neural network(ITIIFNN)to approximate the nonlinearity function and uncertainty functions in the attitude angle dynamic model of micro aircraft vehicle(MAV).Then,the Lyapunov stability theorem is used to testify the asymptotic stability of the closed-loop system,the parameters of the ITIIFNN and gain of sliding mode control can be tuned on-line by adaptive laws based on Lyapunov synthesis approach,and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system.Findings–The validity of the proposed control method has been verified through real-time experiments.The experimental results show that the performance of interval type-II fuzzy neural network based gain adaptive sliding mode controller(GASMC-ITIIFNN)is significantly improved compared with conventional adaptive sliding mode controller(CASMC),type-I fuzzy neural network based sliding mode controller(GASMC-TIFNN).Practical implications–This approach has been used in one MAV,the controller works well,and which could guarantee the MAV control system with good performances under uncertainties,variations,and external disturbances.Originality/value–The main original contributions of this paper are:the proposed control scheme makes full use of the nominal model of the MAV attitude control model;the overall closed-loop control system is globally stable demonstrated by Lyapunov stable theory;the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates;and the MAV attitude control system based on GASMC-ITIIFNN controller can achieve favourable tracking performance than GASMC-TIFNN and CASMC.
