This paper presents an Iterative Learning Control design applied to homing guidance of missiles against maneuvering targets. According to numerical experiments, although an increase of the control energies is apprecia...This paper presents an Iterative Learning Control design applied to homing guidance of missiles against maneuvering targets. According to numerical experiments, although an increase of the control energies is appreciated with respect to a previous published base controller for comparison, this strategy, which is simple to realize, is able to reduce the time to reach the head-on condition to target destruction. This fact is important to minimize the missile lateral force-level to fulfill engaging in hyper-sonic target persecutions.展开更多
The development of iterative learning control combined with disturbance-observer-based(DOB)control for the digital low-level radio frequency(LLRF)system of the International Linear Collider project is presented.The ob...The development of iterative learning control combined with disturbance-observer-based(DOB)control for the digital low-level radio frequency(LLRF)system of the International Linear Collider project is presented.The objective of this study is to compensate for both repetitive(or predictable)and unpredictable disturbances in a radio frequency system(e.g.,beam loading,Lorentz force detuning,and microphonics).The DOB control approach was verified using the LLRF system at the Superconducting Test Facility(STF)at KEK in the absence of a beam.The method comprising DOB control combined with an iterative learning control algorithm was then demonstrated in a cavity-simulator-based test bench,where a simulated beam was available.The results showed that the performance of the LLRF system was improved,as expected by this combined control approach.We plan to further generalize this approach to LLRF systems at the STF and the future International Linear Collider project.展开更多
This paper proposes a self-tuning iterative learning control method for the attitude control of a flexible solar power satellite,which is simplified as an Euler-Bernoulli beam moving in space.An orbit-attitude-structu...This paper proposes a self-tuning iterative learning control method for the attitude control of a flexible solar power satellite,which is simplified as an Euler-Bernoulli beam moving in space.An orbit-attitude-structure coupled dynamic model is established using absolute nodal coordinate formulation,and the attitude control is performed using two control moment gyros.In order to improve control accuracy of the classic proportional-derivative control method,a switched iterative learning control method is presented using the control moments of the previous periods as feedforward control moments.Although the iterative learning control is a model-free method,the parameters of the controller must be selected manually.This would be undesirable for complicated systems with multiple control parameters.Thus,a self-tuning method is proposed using fuzzy logic.The control frequency of the controller is adjusted according to the averaged control error in one control period.Simulation results show that the proposed controller increases the control accuracy greatly and reduces the influence of measurement noise.Moreover,the control frequency is automatically adjusted to a suitable value.展开更多
A point-to-point iterative learning control method with the current-cycle feedback is proposed to enable aircraft to achieve an accurate four-dimensional(4D) trajectory tracking. To this end,the 4D trajectory tracking...A point-to-point iterative learning control method with the current-cycle feedback is proposed to enable aircraft to achieve an accurate four-dimensional(4D) trajectory tracking. To this end,the 4D trajectory tracking control problem is formulated into a point-to-point tracking control issue with an external disturbance. Then,the optimal point-to-point iterative learning control law is derived based on the successive projection method. Further,the current-cycle feedback error is added to the control law,so that the tracking error is reduced in both time and iteration domains. Finally,a numerical simulation is carried out using the kinematic model of an unmanned aerial vehicle and 4D trajectory data. Obtained results demonstrate that the proposed method can quickly reduce the trajectory tracking error even in the presence of gust interferences. Compared with the commonly used average velocity method and the velocity correction method,the proposed method makes full use of the past and current running data,and can continuously improve the accuracy of 4D trajectory tracking with the repetitive operation of aircraft between city pairs.展开更多
基金partially supported by the Spanish Ministry of Economy and Competitiveness under grant number DPI2015-64170-R(MINECO/FEDER)
文摘This paper presents an Iterative Learning Control design applied to homing guidance of missiles against maneuvering targets. According to numerical experiments, although an increase of the control energies is appreciated with respect to a previous published base controller for comparison, this strategy, which is simple to realize, is able to reduce the time to reach the head-on condition to target destruction. This fact is important to minimize the missile lateral force-level to fulfill engaging in hyper-sonic target persecutions.
文摘The development of iterative learning control combined with disturbance-observer-based(DOB)control for the digital low-level radio frequency(LLRF)system of the International Linear Collider project is presented.The objective of this study is to compensate for both repetitive(or predictable)and unpredictable disturbances in a radio frequency system(e.g.,beam loading,Lorentz force detuning,and microphonics).The DOB control approach was verified using the LLRF system at the Superconducting Test Facility(STF)at KEK in the absence of a beam.The method comprising DOB control combined with an iterative learning control algorithm was then demonstrated in a cavity-simulator-based test bench,where a simulated beam was available.The results showed that the performance of the LLRF system was improved,as expected by this combined control approach.We plan to further generalize this approach to LLRF systems at the STF and the future International Linear Collider project.
基金supported by the Guangdong Basic and Applied Basic Research Foundation(No.2019A1515110730)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2021QNRC001)the Fundamental Research Funds for the Central Universities of Sun Yat-sen University(No.22qntd0703)。
文摘This paper proposes a self-tuning iterative learning control method for the attitude control of a flexible solar power satellite,which is simplified as an Euler-Bernoulli beam moving in space.An orbit-attitude-structure coupled dynamic model is established using absolute nodal coordinate formulation,and the attitude control is performed using two control moment gyros.In order to improve control accuracy of the classic proportional-derivative control method,a switched iterative learning control method is presented using the control moments of the previous periods as feedforward control moments.Although the iterative learning control is a model-free method,the parameters of the controller must be selected manually.This would be undesirable for complicated systems with multiple control parameters.Thus,a self-tuning method is proposed using fuzzy logic.The control frequency of the controller is adjusted according to the averaged control error in one control period.Simulation results show that the proposed controller increases the control accuracy greatly and reduces the influence of measurement noise.Moreover,the control frequency is automatically adjusted to a suitable value.
基金supported by the Fundamental Research Funds for the Central Universities(No. 3122019131)。
文摘A point-to-point iterative learning control method with the current-cycle feedback is proposed to enable aircraft to achieve an accurate four-dimensional(4D) trajectory tracking. To this end,the 4D trajectory tracking control problem is formulated into a point-to-point tracking control issue with an external disturbance. Then,the optimal point-to-point iterative learning control law is derived based on the successive projection method. Further,the current-cycle feedback error is added to the control law,so that the tracking error is reduced in both time and iteration domains. Finally,a numerical simulation is carried out using the kinematic model of an unmanned aerial vehicle and 4D trajectory data. Obtained results demonstrate that the proposed method can quickly reduce the trajectory tracking error even in the presence of gust interferences. Compared with the commonly used average velocity method and the velocity correction method,the proposed method makes full use of the past and current running data,and can continuously improve the accuracy of 4D trajectory tracking with the repetitive operation of aircraft between city pairs.
