Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has seve...Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has severely restricted the applications of high-precision FOGs.The conventional methods for suppressing vibration-induced errors mostly concentrate on reinforcing the mechanical structure and optical path as well as the compensation under some specific operation parameters,which have very limited effects for high-precision FOGs maintaining performances under vibration.In this work,a technique of suppressing the vibration-induced bias deviation through removing the part related to the varying gain from the rotation-rate output is put forward.Particularly,the loop gain is extracted out by adding a gain-monitoring wave.By demodulating the loop gain and the rotation rate simultaneously under distinct frequencies and investigating their quantitative relationship,the vibrationinduced bias error is compensated without limiting the operating parameters or environments,like the applied modulation depth.The experimental results show that the proposed method has achieved the reduction of bias error from about 0.149°/h to0.014°/h during the random vibration with frequencies from20 Hz to 2000 Hz.This technique provides a feasible route for enhancing the performances of high-precision FOGs heading towards high environmental adaptability.展开更多
The open-loop crossover frequency is pointed as an important parameter for practical autopilot design. Since different gain designs may achieve the same open-loop crossover frequency, it should be neither considered a...The open-loop crossover frequency is pointed as an important parameter for practical autopilot design. Since different gain designs may achieve the same open-loop crossover frequency, it should be neither considered as a performance objective of the optimal autopilot design-schemes nor neglected. Besides, the main assignment of the autopilot is to drive the missile to track the acceleration commands, so the autopilot gain design should be evaluated directly according to the resultant tracking performance. For this purpose, an optimal design methodology of the three-loop missile autopilot is introduced based on constraint optimization technique, where the tracking performance is established analytically as the design objective and the open-loop crossover frequency is formed as inequality constraint function, both are manipulated in terms of stable characteristic parameters of the autopilot closed-loop. The proposed technique is implemented with the assistance of a numerical optimization algorithm which automatically adjusts the design parameters. Finally, numerical simulation results are provided to demonstrate the effectiveness and feasibility of the proposed approach compared with that in some references.展开更多
For the robustness problem of open-loop P-type iterative learning control under the influence of measurement noise which is inevitable in actual systems, an adaptive adjustment algorithm of iterative learning nonlinea...For the robustness problem of open-loop P-type iterative learning control under the influence of measurement noise which is inevitable in actual systems, an adaptive adjustment algorithm of iterative learning nonlinear gain matrix based on error amplitude is proposed and two nonlinear gain functions are given. Then with the help of Bellman-Gronwall lemma, the robustness proof is derived. At last, an example is simulated and analyzed. The results show that when there exists measurement noise, the proposed learning law adjusts the learning gain matrix on line based on error amplitude, thus can make a compromise between learning convergence rate and convergence accuracy to some extent： the fast convergence rate is achieved with high gain in initial learning stage, the strong robustness and high convergence accuracy are achieved at the same time with small gain in the end learning stage, thus better learning results are obtained.展开更多
良好的控制策略是实现并联型有源电力滤波器(active power filter,APF)补偿功能的关键。由于并联型APF常规电流PI控制方法的闭环增益受系统稳定性条件约束,并联型APF对负载主要谐波分量补偿不充分。针对该问题,提出一种用于APF的新型选...良好的控制策略是实现并联型有源电力滤波器(active power filter,APF)补偿功能的关键。由于并联型APF常规电流PI控制方法的闭环增益受系统稳定性条件约束,并联型APF对负载主要谐波分量补偿不充分。针对该问题,提出一种用于APF的新型选择性谐波电流控制策略。该控制策略在常规电流PI控制策略的基础上,对负载电流主要谐波(该文主要指5次、7次谐波)单独提取与控制,而对其余次谐波采用一个常规电流PI控制器控制。该设计方法,增大了系统对主要谐波分量的跟踪增益,提高了APF对谐波的补偿率,实现了控制系统更好的频率响应。将该方法应用于实验室制作的一台30 kVA并联型APF实验装置,可将电流总谐波畸变率(total harmonic distortion,THD)由23.21%补偿为3.75%。仿真与实验结果证明了以上结论。展开更多
基金Fundamental Research Funds for the Central Universities(YWF-23-L-1225)National Natural Science Foundation of China(62201025)Chinese Aeronautical Establishment(2022Z037051001)。
文摘Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has severely restricted the applications of high-precision FOGs.The conventional methods for suppressing vibration-induced errors mostly concentrate on reinforcing the mechanical structure and optical path as well as the compensation under some specific operation parameters,which have very limited effects for high-precision FOGs maintaining performances under vibration.In this work,a technique of suppressing the vibration-induced bias deviation through removing the part related to the varying gain from the rotation-rate output is put forward.Particularly,the loop gain is extracted out by adding a gain-monitoring wave.By demodulating the loop gain and the rotation rate simultaneously under distinct frequencies and investigating their quantitative relationship,the vibrationinduced bias error is compensated without limiting the operating parameters or environments,like the applied modulation depth.The experimental results show that the proposed method has achieved the reduction of bias error from about 0.149°/h to0.014°/h during the random vibration with frequencies from20 Hz to 2000 Hz.This technique provides a feasible route for enhancing the performances of high-precision FOGs heading towards high environmental adaptability.
文摘The open-loop crossover frequency is pointed as an important parameter for practical autopilot design. Since different gain designs may achieve the same open-loop crossover frequency, it should be neither considered as a performance objective of the optimal autopilot design-schemes nor neglected. Besides, the main assignment of the autopilot is to drive the missile to track the acceleration commands, so the autopilot gain design should be evaluated directly according to the resultant tracking performance. For this purpose, an optimal design methodology of the three-loop missile autopilot is introduced based on constraint optimization technique, where the tracking performance is established analytically as the design objective and the open-loop crossover frequency is formed as inequality constraint function, both are manipulated in terms of stable characteristic parameters of the autopilot closed-loop. The proposed technique is implemented with the assistance of a numerical optimization algorithm which automatically adjusts the design parameters. Finally, numerical simulation results are provided to demonstrate the effectiveness and feasibility of the proposed approach compared with that in some references.
基金supported by the Specialized Research Fund for the Doctoral Program of Higher Education(20106102110032)
文摘For the robustness problem of open-loop P-type iterative learning control under the influence of measurement noise which is inevitable in actual systems, an adaptive adjustment algorithm of iterative learning nonlinear gain matrix based on error amplitude is proposed and two nonlinear gain functions are given. Then with the help of Bellman-Gronwall lemma, the robustness proof is derived. At last, an example is simulated and analyzed. The results show that when there exists measurement noise, the proposed learning law adjusts the learning gain matrix on line based on error amplitude, thus can make a compromise between learning convergence rate and convergence accuracy to some extent： the fast convergence rate is achieved with high gain in initial learning stage, the strong robustness and high convergence accuracy are achieved at the same time with small gain in the end learning stage, thus better learning results are obtained.
