The problem of deadbeat covariance controller design for sampled data feedback systems is considered. The purpose of considering this problem is to design linear discrete controllers such that the state covariance of...The problem of deadbeat covariance controller design for sampled data feedback systems is considered. The purpose of considering this problem is to design linear discrete controllers such that the state covariance of the closed loop system achieves its steady state value which is equal to a prespecified positive definite matrix during finite beats. This problem is reduced to the similar one for equivalent discrete time systems by taking intersample behaviour into account. Both the existence conditions and the explicit expression of the desired controllers are given.展开更多
To improve the dynamic performance of conventional deadbeat predictive current control(DPCC)under parameter mismatch,especially eliminate the current overshoot and oscillation during torque mutation,it is necessary to...To improve the dynamic performance of conventional deadbeat predictive current control(DPCC)under parameter mismatch,especially eliminate the current overshoot and oscillation during torque mutation,it is necessary to enhance the robustness of DPCC against various working conditions.However,the disturbance from parameter mismatch can deteriorate the dynamic performance.To deal with the above problem,firstly,traditional DPCC and the parameter sensitivity of DPCC are introduced and analyzed.Secondly,an extended state observer(ESO)combined with DPCC method is proposed,which can observe and suppress the disturbance due to various parameter mismatch.Thirdly,to improve the accuracy and stability of ESO,an adaptive extended state observer(AESO)using fuzzy controller based on ESO,is presented,and combined with DPCC method.The improved DPCC-AESO can switch the value of gain coefficients with fuzzy control,accelerating the current response speed and avoid the overshoot and oscillation,which improves the robustness and stability performance of SPMSM.Finally,the three methods,as well as conventional DPCC method,DPCC-ESO method,DPCC-AESO method,are comparatively analyzed in this paper.The effectiveness of the proposed two methods are verified by simulation and experimental results.展开更多
The traditional deadbeat control for UPS inverters has a robustness problem. The parametric imprecision can greatly harm the stability of the system, which restricts the application. A novel robust deadbeat control me...The traditional deadbeat control for UPS inverters has a robustness problem. The parametric imprecision can greatly harm the stability of the system, which restricts the application. A novel robust deadbeat control method is proposed in this paper to deal with the problem. In the proposed control method, a proportional element is added to the traditional deadbeat control in order to improve the robustness to parametric imprecision. To eliminate the error between output voltage and voltage reference caused by environmental noise and parametric deviation, a model reference adaptive regulator is also added to the control method. A 1kVA prototype is built based on DSP. Theoretical analysis and experimental results show that the robustness for parametric variation of the proposed method is much better than the traditional deadbeat control. The system can remain stable even when the systemic parameters have a large deviation from calculating parameters. The system has small static error and fast dynamic response with the new control method. This method is easy to realize in DSP and is suitable for full digital realization of UPS.展开更多
Deadbeat predictive current control(DPCC)has been widely applied in permanent magnet synchronous motor(PMSM)drives due to its fast dynamic response and good steady-state performance.However,the control accuracy of DPC...Deadbeat predictive current control(DPCC)has been widely applied in permanent magnet synchronous motor(PMSM)drives due to its fast dynamic response and good steady-state performance.However,the control accuracy of DPCC is dependent on the machine parameters’accuracy.In practical applications,the machine parameters may vary with working conditions due to temperature,saturation,skin effect,and so on.As a result,the performance of DPCC may degrade when there are parameter mismatches between the actual value and the one used in the controller.To solve the problem of parameter dependence for DPCC,this study proposes an improved model-free predictive current control method for PMSM drives.The accurate model of the PMSM is replaced by a first-order ultra-local model.This model is dynamically updated by online estimation of the gain of the input voltage and the other parts describing the system dynamics.After obtaining this ultra-local model from the information on the measured stator currents and applied stator voltages in past control periods,the reference voltage value can be calculated based on the principle of DPCC,which is subsequently synthesized by space vector modulation(SVM).This method is compared with conventional DPCC and field-oriented control(FOC),and its superiority is verified by the presented experimental results.展开更多
The main drawbacks of traditional finite set model predictive control are high computational load,large torque ripple,and variable switching frequency.A less complex deadbeat(DB)model predictive current control(MPCC)w...The main drawbacks of traditional finite set model predictive control are high computational load,large torque ripple,and variable switching frequency.A less complex deadbeat(DB)model predictive current control(MPCC)with improved space vector pulse-width modulation(SVPWM)under a single-phase open-circuit fault is proposed.The proposed method predicts the reference voltage vector in the a-β subspace by employing the deadbeat control principle on the machine predictive model;thus,the exhaustive exploration procedure is avoided to relieve the computational load.To perform the constant switching frequency operation and achieve better steady-state performance,a modified SVPWM strategy is developed with the same conventional structure,which modulates the reference voltage vector.This new approach is based on a redesigned and adjusted post-fault virtual voltage vector space distribution that eliminates the y-axis harmonic components in the x-y subspace and ensures the generation of symmetrical PWM pulses.Meanwhile,the combined merits of the DB,MPCC,and SVPWM methods are realized.To verify the effectiveness of the proposed control scheme,comparative experiments are performed on a five-phase permanent magnet synchronous motor(PMSM)drive system.展开更多
文摘The problem of deadbeat covariance controller design for sampled data feedback systems is considered. The purpose of considering this problem is to design linear discrete controllers such that the state covariance of the closed loop system achieves its steady state value which is equal to a prespecified positive definite matrix during finite beats. This problem is reduced to the similar one for equivalent discrete time systems by taking intersample behaviour into account. Both the existence conditions and the explicit expression of the desired controllers are given.
基金supported by the National Natural Science Foundation of China(No.52005037).
文摘To improve the dynamic performance of conventional deadbeat predictive current control(DPCC)under parameter mismatch,especially eliminate the current overshoot and oscillation during torque mutation,it is necessary to enhance the robustness of DPCC against various working conditions.However,the disturbance from parameter mismatch can deteriorate the dynamic performance.To deal with the above problem,firstly,traditional DPCC and the parameter sensitivity of DPCC are introduced and analyzed.Secondly,an extended state observer(ESO)combined with DPCC method is proposed,which can observe and suppress the disturbance due to various parameter mismatch.Thirdly,to improve the accuracy and stability of ESO,an adaptive extended state observer(AESO)using fuzzy controller based on ESO,is presented,and combined with DPCC method.The improved DPCC-AESO can switch the value of gain coefficients with fuzzy control,accelerating the current response speed and avoid the overshoot and oscillation,which improves the robustness and stability performance of SPMSM.Finally,the three methods,as well as conventional DPCC method,DPCC-ESO method,DPCC-AESO method,are comparatively analyzed in this paper.The effectiveness of the proposed two methods are verified by simulation and experimental results.
文摘The traditional deadbeat control for UPS inverters has a robustness problem. The parametric imprecision can greatly harm the stability of the system, which restricts the application. A novel robust deadbeat control method is proposed in this paper to deal with the problem. In the proposed control method, a proportional element is added to the traditional deadbeat control in order to improve the robustness to parametric imprecision. To eliminate the error between output voltage and voltage reference caused by environmental noise and parametric deviation, a model reference adaptive regulator is also added to the control method. A 1kVA prototype is built based on DSP. Theoretical analysis and experimental results show that the robustness for parametric variation of the proposed method is much better than the traditional deadbeat control. The system can remain stable even when the systemic parameters have a large deviation from calculating parameters. The system has small static error and fast dynamic response with the new control method. This method is easy to realize in DSP and is suitable for full digital realization of UPS.
文摘Deadbeat predictive current control(DPCC)has been widely applied in permanent magnet synchronous motor(PMSM)drives due to its fast dynamic response and good steady-state performance.However,the control accuracy of DPCC is dependent on the machine parameters’accuracy.In practical applications,the machine parameters may vary with working conditions due to temperature,saturation,skin effect,and so on.As a result,the performance of DPCC may degrade when there are parameter mismatches between the actual value and the one used in the controller.To solve the problem of parameter dependence for DPCC,this study proposes an improved model-free predictive current control method for PMSM drives.The accurate model of the PMSM is replaced by a first-order ultra-local model.This model is dynamically updated by online estimation of the gain of the input voltage and the other parts describing the system dynamics.After obtaining this ultra-local model from the information on the measured stator currents and applied stator voltages in past control periods,the reference voltage value can be calculated based on the principle of DPCC,which is subsequently synthesized by space vector modulation(SVM).This method is compared with conventional DPCC and field-oriented control(FOC),and its superiority is verified by the presented experimental results.
基金Supported in part by the National Natural Science Foundation of China under Grant 52025073in part by the Key Research and Development Program of Jiangsu Province under Grant BE2018107,and in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘The main drawbacks of traditional finite set model predictive control are high computational load,large torque ripple,and variable switching frequency.A less complex deadbeat(DB)model predictive current control(MPCC)with improved space vector pulse-width modulation(SVPWM)under a single-phase open-circuit fault is proposed.The proposed method predicts the reference voltage vector in the a-β subspace by employing the deadbeat control principle on the machine predictive model;thus,the exhaustive exploration procedure is avoided to relieve the computational load.To perform the constant switching frequency operation and achieve better steady-state performance,a modified SVPWM strategy is developed with the same conventional structure,which modulates the reference voltage vector.This new approach is based on a redesigned and adjusted post-fault virtual voltage vector space distribution that eliminates the y-axis harmonic components in the x-y subspace and ensures the generation of symmetrical PWM pulses.Meanwhile,the combined merits of the DB,MPCC,and SVPWM methods are realized.To verify the effectiveness of the proposed control scheme,comparative experiments are performed on a five-phase permanent magnet synchronous motor(PMSM)drive system.
