Estimation of Load Disturbance Torque for DC Motor Drive Systems Under Robustness and Sensitivity Consideration

Grignion, Danny; Chen, Xiang; Kar, Narayan C.; Qian, Huijie

doi:10.1109/tie.2013.2257138

Cited by 32 publications

(9 citation statements)

References 23 publications

(30 reference statements)

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“…Simulation is conducted for the DC motor control system in Matlab, and the sampling period of the system is chosen as Ts=0.001s. The values of the parameters used in simulation are given in Table 1 (Grignion et al., 2014).…”

Section: Applicationsmentioning

confidence: 99%

Input–output stabilization-based finite-time robust control of disturbed systems using linear matrix inequality approach

Zhang

Pang

2017

Journal of Vibration and Control

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In this paper, finite-time robust control problems are considered for a class of uncertain systems subject to exogenous disturbances, and an input–output finite-time stabilization (IO-FTS) method is presented with finite-time boundedness (FTB) constraints. For an uncertain system, a state feedback controller is designed, via linear matrix inequalities (LMIs), to ensure the IO-FTS and FTB of the closed-loop system. By using Lyapunov stability theory, sufficient conditions for IO-FTS and FTB are given. These conditions are expressed as a feasibility problem of a set of LMIs. The direct current motor control problem and roll autopilot design of a skid-to-turn missile are considered for a case study. Simulation results are presented to show the effectiveness of the proposed method as a promising approach to controlling similar uncertain systems.

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Section: Applicationsmentioning

confidence: 99%

Input–output stabilization-based finite-time robust control of disturbed systems using linear matrix inequality approach

Zhang

Pang

2017

Journal of Vibration and Control

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“…To this end, several advanced control approaches have been investigated to enhance the performance specifications from different aspects, i.e. hierarchical/nonlinear PID control [11]- [14], [19], passivity-based control [9], [17], [18], model predictive control [27], adaptive control approach [16], [28], robust control [6], fuzzy control [29], H ∞ control [30], and active disturbance rejection control [6], [15] for converter driven DC motor systems.…”

Section: Introductionmentioning

confidence: 99%

Robust Predictive Speed Regulation of Converter-Driven DC Motors via a Discrete-Time Reduced-Order GPIO

Yang

et al. 2019

IEEE Trans. Ind. Electron.

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Converter-driven direct current (DC) motors exhibit various advantages in industry, but impose several challenges to higher-precision speed regulation in the presence of parametric uncertainties and exogenous, timevarying load torque disturbances. In this paper, the robust predictive speed regulation problem of a generic DC-DC buck converter-driven permanent magnet DC motors is addressed by using an output feedback discrete-time model predictive control (MPC) algorithm. A new discrete-time reduced-order generalized proportional-integral observer (GPIO) is proposed to reconstruct the virtual system states as well as the lumped disturbances. The estimates of GPIO are then collected for output speed prediction. An optimized duty ratio law of the converter is obtained by solving a constrained receding horizon optimization problem, where the operational constraint on control input is explicitly taken into account. Finally, the effectiveness of the proposed new algorithm is demonstrated by various experimental testing results.

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“…34 Hence, it is important to estimate the external disturbances during the trajectory tracking process. The concept of disturbance estimation observer was firstly proposed by Grignion et al, 35 as compensating disturbances. Due to the powerful applicability of disturbance estimation technique, a series of achievements had been obtained in recent years.…”

Section: Introductionmentioning

confidence: 99%

An adaptive iterative learning control approach based on disturbance estimation for manipulator system

Liu

Chai

Sun

et al. 2019

International Journal of Advanced Robotic Systems

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An adaptive iterative learning control approach based on disturbance estimation has been developed for trajectory tracking of manipulators with uncertain parameters and external disturbances. The external disturbances are estimated by the feedback iterative learning method, whereas the uncertain parameters are compensated by adaptive control. This approach which is based on the disturbance estimation technique provides a rapid convergence of trajectory tracking errors. According to the Lyapunov theory, the sufficient condition of the asymptotic stability has been developed for the 2-degrees of freedom (DOFs) manipulator system. The numerical results show that the adaptive iterative learning control approach based on disturbance estimation is feasible and effective for the 2-DOFs manipulator. A comparison of the adaptive iterative learning control method and the iterative learning control method is completed, which shows that the adaptive iterative learning control method performs a faster convergence of the disturbance to the steady state.

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Estimation of Load Disturbance Torque for DC Motor Drive Systems Under Robustness and Sensitivity Consideration

Cited by 32 publications

References 23 publications

Input–output stabilization-based finite-time robust control of disturbed systems using linear matrix inequality approach

Input–output stabilization-based finite-time robust control of disturbed systems using linear matrix inequality approach

Robust Predictive Speed Regulation of Converter-Driven DC Motors via a Discrete-Time Reduced-Order GPIO

An adaptive iterative learning control approach based on disturbance estimation for manipulator system

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