In order to effectively control the working state of the gyroscope in drive mode, the drive characteristics of the micro electromechanical system （MEMS） gyroscope are analyzed in principle. A novel drive circuit for...In order to effectively control the working state of the gyroscope in drive mode, the drive characteristics of the micro electromechanical system （MEMS） gyroscope are analyzed in principle. A novel drive circuit for the MEMS gyroscope in digital closed-loop control is proposed, which utilizes a digital phase-locked loop （PLL） in frequency control and an automatic gain control （AGC） method in amplitude control. A digital processing circuit with a field programmable gate array （FPGA） is designed and the experiments are carried out. The results indicate that when the temperature changes, the drive frequency can automatically track the resonant frequency of gyroscope in drive mode and that of the oscillating amplitude holds at a set value. And at room temperature, the relative deviation of the drive frequency is 0.624 ×10^-6 and the oscillating amplitude is 8.0 ×10^-6, which are 0. 094% and 18. 39% of the analog control program, respectively. Therefore, the control solution of the digital PLL in frequency and the AGC in amplitude is feasible.展开更多
In order to meet the requirements for zero value stability of direct sequence spread spectrum(DSSS) signal processing in high dynamic scenario,digital automatic gain control(AGC) is employed to regulate power.However,...In order to meet the requirements for zero value stability of direct sequence spread spectrum(DSSS) signal processing in high dynamic scenario,digital automatic gain control(AGC) is employed to regulate power.However,conventional AGC causes degradation in the synchronization performance of DSSS receiver.Based on the theoretical analysis of the influence of digital AGC on DSSS signal synchronization,this paper proposes a new AGC algorithm,which is applicable to multi-channel digital DSSS signal receiver.By making power adjustment cycle and synchronization cycle coherent with each other adaptively,the influence of digital AGC on subsequent synchronization processing has been eliminated.Theoretical analysis,simulation results and experimental data verify the validity of the proposed algorithm.By virtue of the proposed algorithm,the influence of digital AGC on DSSS signal synchronization is eliminated.This algorithm applies to an aerospace engineering project successfully.展开更多
An optimal experiment design (DED) with respect to the use of designing model-base controller was studied. The mean squared error at the setpoint is chosen as the performance criterion. Simple design formulas are deri...An optimal experiment design (DED) with respect to the use of designing model-base controller was studied. The mean squared error at the setpoint is chosen as the performance criterion. Simple design formulas are derived based on the asymptotic theory. The signal is used for the open loop experiment. The design constraint is the power of the process signal or the process input signal. The results give guideline for identification application.展开更多
As human beings,people coordinate movements and interact with the environment through sensory information and motor adaptation in the daily lives.Many characteristics of these interactions can be studied using optimiz...As human beings,people coordinate movements and interact with the environment through sensory information and motor adaptation in the daily lives.Many characteristics of these interactions can be studied using optimization-based models,which assume that the precise knowledge of both the sensorimotor system and its interactive environment is available for the central nervous system(CNS).However,both static and dynamic uncertainties occur inevitably in the daily movements.When these uncertainties are taken into consideration,the previously developed models based on optimization theory may fail to explain how the CNS can still coordinate human movements which are also robust with respect to the uncertainties.In order to address this problem,this paper presents a novel computational mechanism for sensorimotor control from a perspective of robust adaptive dynamic programming(RADP).Sharing some essential features of reinforcement learning,which was originally observed from mammals,the RADP model for sensorimotor control suggests that,instead of identifying the system dynamics of both the motor system and the environment,the CNS computes iteratively a robust optimal control policy using the real-time sensory data.An online learning algorithm is provided in this paper,with rigorous convergence and stability analysis.Then,it is applied to simulate several experiments reported from the past literature.By comparing the proposed numerical results with these experimentally observed data,the authors show that the proposed model can reproduce movement trajectories which are consistent with experimental observations.In addition,the RADP theory provides a unified framework that connects optimality and robustness properties in the sensorimotor system.展开更多
基金The National Natural Science Foundation of China(No. 60974116 )the Research Fund of Aeronautics Science (No.20090869007)Specialized Research Fund for the Doctoral Program of Higher Education (No. 200902861063)
文摘In order to effectively control the working state of the gyroscope in drive mode, the drive characteristics of the micro electromechanical system （MEMS） gyroscope are analyzed in principle. A novel drive circuit for the MEMS gyroscope in digital closed-loop control is proposed, which utilizes a digital phase-locked loop （PLL） in frequency control and an automatic gain control （AGC） method in amplitude control. A digital processing circuit with a field programmable gate array （FPGA） is designed and the experiments are carried out. The results indicate that when the temperature changes, the drive frequency can automatically track the resonant frequency of gyroscope in drive mode and that of the oscillating amplitude holds at a set value. And at room temperature, the relative deviation of the drive frequency is 0.624 ×10^-6 and the oscillating amplitude is 8.0 ×10^-6, which are 0. 094% and 18. 39% of the analog control program, respectively. Therefore, the control solution of the digital PLL in frequency and the AGC in amplitude is feasible.
基金support of the National High Technology Research and Development Program of China(863)(Grant No.2013AA1548)
文摘In order to meet the requirements for zero value stability of direct sequence spread spectrum(DSSS) signal processing in high dynamic scenario,digital automatic gain control(AGC) is employed to regulate power.However,conventional AGC causes degradation in the synchronization performance of DSSS receiver.Based on the theoretical analysis of the influence of digital AGC on DSSS signal synchronization,this paper proposes a new AGC algorithm,which is applicable to multi-channel digital DSSS signal receiver.By making power adjustment cycle and synchronization cycle coherent with each other adaptively,the influence of digital AGC on subsequent synchronization processing has been eliminated.Theoretical analysis,simulation results and experimental data verify the validity of the proposed algorithm.By virtue of the proposed algorithm,the influence of digital AGC on DSSS signal synchronization is eliminated.This algorithm applies to an aerospace engineering project successfully.
基金High Technology Research and Development Program me of China (No.2 0 0 1AA413 13 0 )
文摘An optimal experiment design (DED) with respect to the use of designing model-base controller was studied. The mean squared error at the setpoint is chosen as the performance criterion. Simple design formulas are derived based on the asymptotic theory. The signal is used for the open loop experiment. The design constraint is the power of the process signal or the process input signal. The results give guideline for identification application.
基金supported in part by the US National Science Foundation Grant Nos.ECCS-1101401 and ECCS-1230040
文摘As human beings,people coordinate movements and interact with the environment through sensory information and motor adaptation in the daily lives.Many characteristics of these interactions can be studied using optimization-based models,which assume that the precise knowledge of both the sensorimotor system and its interactive environment is available for the central nervous system(CNS).However,both static and dynamic uncertainties occur inevitably in the daily movements.When these uncertainties are taken into consideration,the previously developed models based on optimization theory may fail to explain how the CNS can still coordinate human movements which are also robust with respect to the uncertainties.In order to address this problem,this paper presents a novel computational mechanism for sensorimotor control from a perspective of robust adaptive dynamic programming(RADP).Sharing some essential features of reinforcement learning,which was originally observed from mammals,the RADP model for sensorimotor control suggests that,instead of identifying the system dynamics of both the motor system and the environment,the CNS computes iteratively a robust optimal control policy using the real-time sensory data.An online learning algorithm is provided in this paper,with rigorous convergence and stability analysis.Then,it is applied to simulate several experiments reported from the past literature.By comparing the proposed numerical results with these experimentally observed data,the authors show that the proposed model can reproduce movement trajectories which are consistent with experimental observations.In addition,the RADP theory provides a unified framework that connects optimality and robustness properties in the sensorimotor system.
