In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.T...In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.The control accuracy of ISP is fundamentally circumscribed by various disturbance torques in rotating shaft.Therefore,a dynamic model of ISP incorporating composite perturbations is established with regard to the stabilization of axis in the inertial reference frame.Subsequently,an online estimator for control loop uncertainties based on the sliding mode control algorithm is designed to estimate the aggregate disturbances of various parameters uncertainties and other unmodeled disturbances that cannot be accurately calibrated.Finally,the proposed DSMO is integrated into a classical proportional-integral-derivative(PID)control scheme,utilizing feedforward approach to compensate the composite disturbance in the control loop online.The effectiveness of the proposed disturbance observer is validated through simulation and hardware experimentation,demonstrating a significant improvement in the dynamic control performance and robustness of the classical PID controller extensively utilized in the field of engineering.展开更多
To achieve excellent tracking accuracy,a coarse-fine dual-stage control system is chosen for inertially stabilized platform.The coarse stage is a conventional inertially stabilized platform,and the fine stage is a sec...To achieve excellent tracking accuracy,a coarse-fine dual-stage control system is chosen for inertially stabilized platform.The coarse stage is a conventional inertially stabilized platform,and the fine stage is a secondary servo mechanism to control lens motion in the imaging optical path.Firstly,the dual-stage dynamics is mathematically modeled as a coupling multi-input multi-output(MIMO)control system.Then,by incorporating compensation of adaptive model to deal with parameter variations and nonlinearity,a systematic robust H∞control scheme is designed,which can achieve good tracking performance,as well as improve system robustness against model uncertainties.Lyapunov stability analysis confirmed the stability of the overall control system.Finally,simulation and experiment results are provided to demonstrate the feasibility and effectiveness of the proposed control design method.展开更多
Accurate parameter identification is essential when designing controllers for inertially stabilized platforms （lSPs）. But traditional identification methods suffer from observation measurement noise and operating re...Accurate parameter identification is essential when designing controllers for inertially stabilized platforms （lSPs）. But traditional identification methods suffer from observation measurement noise and operating restrictions of ISPs. To address this issue, a novel identification method based on current command design and multilevel coordinate search （MCS） algorithm without any higher order measurement differentiations was proposed. The designed current commands were adopted to obtain parameter decoupled models with the platform operating under allowable conditions. MCS algorithm was employed to estimate the parameters based on parameter decoupled models. A comparison experiment between the proposed method and non-linear least square method was carried out and most of the relative errors of identified parameters obtained by the proposed method were below 10%. Simulation and experiment based on identified parameters were conducted. A velocity control structure was also developed with disturbance observer （DOB） for application in disturbance compensation control system of an ISR Experimental results show that the control scheme based on the identified parameters with DOB has the best disturbance rejection performance. It reduces the peak to peak value （PPV） of velocity error integral to 0.8 mrad which is much smaller than the value （10 mrad） obtained by the single velocity controller without DOB. Compared with the control scheme based on sweep model with DOB compensation, the proposed control scheme improves the PPV of velocity error integral by 1.625 times.展开更多
LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensi...LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensive experimental observations of friction behaviors in the prestiction,some variables were abstracted to depict the rules in the prestiction regime.Based upon the knowledge of friction modeling,a novel friction model including the presliding regime,the gross sliding regime and the prestiction regime was then presented to overcome the shortcomings of the LuGre model.The reason that LuGre model cannot estimate the prestiction friction was analyzed in theory.Feasibility analysis of the proposed model in modeling the prestiction friction was also addressed.A parameter identification method for the proposed model based on multilevel coordinate search algorithm was presented.The proposed friction compensation strategy was composed of a nonlinear friction observer and a feedforward mechanism.The friction observer was designed to estimate the friction force in the presliding and the gross sliding regimes.And the friction force was estimated based on the model in the prestiction regime.The comparative trajectory tracking experiments were conducted on a simulator of inertially stabilization platforms among three control schemes:the single proportional–derivative(PD)control,the PD with LuGre model-based compensation and the PD with compensator based on the presented model.The experimental results reveal that the control scheme based on the proposed model has the best tracking performance.It reduces the peak-to-peak value(PPV)of tracking error to 0.2 mrad,which is improved almost 50%compared with the PD with LuGre model-based compensation.Compared to the single PD control,it reduces the PPV of error by 66.7%.展开更多
基金supported by the National Natural Science Foundation of China(61803015).
文摘In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.The control accuracy of ISP is fundamentally circumscribed by various disturbance torques in rotating shaft.Therefore,a dynamic model of ISP incorporating composite perturbations is established with regard to the stabilization of axis in the inertial reference frame.Subsequently,an online estimator for control loop uncertainties based on the sliding mode control algorithm is designed to estimate the aggregate disturbances of various parameters uncertainties and other unmodeled disturbances that cannot be accurately calibrated.Finally,the proposed DSMO is integrated into a classical proportional-integral-derivative(PID)control scheme,utilizing feedforward approach to compensate the composite disturbance in the control loop online.The effectiveness of the proposed disturbance observer is validated through simulation and hardware experimentation,demonstrating a significant improvement in the dynamic control performance and robustness of the classical PID controller extensively utilized in the field of engineering.
基金Project (61174203) supported by the National Natural Science Foundation of China
文摘To achieve excellent tracking accuracy,a coarse-fine dual-stage control system is chosen for inertially stabilized platform.The coarse stage is a conventional inertially stabilized platform,and the fine stage is a secondary servo mechanism to control lens motion in the imaging optical path.Firstly,the dual-stage dynamics is mathematically modeled as a coupling multi-input multi-output(MIMO)control system.Then,by incorporating compensation of adaptive model to deal with parameter variations and nonlinearity,a systematic robust H∞control scheme is designed,which can achieve good tracking performance,as well as improve system robustness against model uncertainties.Lyapunov stability analysis confirmed the stability of the overall control system.Finally,simulation and experiment results are provided to demonstrate the feasibility and effectiveness of the proposed control design method.
基金Project(50805144) supported by the National Natural Science Foundation of China
文摘Accurate parameter identification is essential when designing controllers for inertially stabilized platforms （lSPs）. But traditional identification methods suffer from observation measurement noise and operating restrictions of ISPs. To address this issue, a novel identification method based on current command design and multilevel coordinate search （MCS） algorithm without any higher order measurement differentiations was proposed. The designed current commands were adopted to obtain parameter decoupled models with the platform operating under allowable conditions. MCS algorithm was employed to estimate the parameters based on parameter decoupled models. A comparison experiment between the proposed method and non-linear least square method was carried out and most of the relative errors of identified parameters obtained by the proposed method were below 10%. Simulation and experiment based on identified parameters were conducted. A velocity control structure was also developed with disturbance observer （DOB） for application in disturbance compensation control system of an ISR Experimental results show that the control scheme based on the identified parameters with DOB has the best disturbance rejection performance. It reduces the peak to peak value （PPV） of velocity error integral to 0.8 mrad which is much smaller than the value （10 mrad） obtained by the single velocity controller without DOB. Compared with the control scheme based on sweep model with DOB compensation, the proposed control scheme improves the PPV of velocity error integral by 1.625 times.
基金Projects(51135009,51105371) supported by the National Natural Science Foundation of China
文摘LuGre model has been widely used in friction modeling and compensation.However,the new friction regime,named prestiction regime,cannot be accurately characterized by LuGre model in the latest research.With the extensive experimental observations of friction behaviors in the prestiction,some variables were abstracted to depict the rules in the prestiction regime.Based upon the knowledge of friction modeling,a novel friction model including the presliding regime,the gross sliding regime and the prestiction regime was then presented to overcome the shortcomings of the LuGre model.The reason that LuGre model cannot estimate the prestiction friction was analyzed in theory.Feasibility analysis of the proposed model in modeling the prestiction friction was also addressed.A parameter identification method for the proposed model based on multilevel coordinate search algorithm was presented.The proposed friction compensation strategy was composed of a nonlinear friction observer and a feedforward mechanism.The friction observer was designed to estimate the friction force in the presliding and the gross sliding regimes.And the friction force was estimated based on the model in the prestiction regime.The comparative trajectory tracking experiments were conducted on a simulator of inertially stabilization platforms among three control schemes:the single proportional–derivative(PD)control,the PD with LuGre model-based compensation and the PD with compensator based on the presented model.The experimental results reveal that the control scheme based on the proposed model has the best tracking performance.It reduces the peak-to-peak value(PPV)of tracking error to 0.2 mrad,which is improved almost 50%compared with the PD with LuGre model-based compensation.Compared to the single PD control,it reduces the PPV of error by 66.7%.
