Active Disturbance Compensation Based Robust Control for Speed Regulation System of Permanent Magnet Synchronous Motor

Ma, Yanfei; Li, Yunhua

doi:10.3390/app10020709

Cited by 15 publications

(12 citation statements)

References 28 publications

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“…Firstly, the parameters κ 1 and κ 2 of disturbance observers (37) are chosen to be as small as possible based on the sampling time to achieve high estimation accuracy; however, the selection of the excessively small disturbance observer gains may make the disturbance observers unstable. Consequently, the remaining parameters, including controller gains in (14) and (15), parameters of adaptation mechanisms (36), ( 40) and (47) of RBF-NNs, are designed based on the closed-loop system stability condition (54).…”

Section: Stability Analysismentioning

confidence: 99%

“…Although in these control methods, the system dynamics are taken into account in control design, they are sensitive to the modeling uncertainties and disturbances that naturally exist in EHSSs. In contrast, SMC [10][11][12][13][14] which was originally introduced by Utkin [15], is considered as a powerful candidate to deal with disturbances and uncertainties, satisfying the matching condition in nonlinear systems that are assumed to be bounded. However, it can be seen that all the above model-based control approaches for EHSSs require the system dynamics to be known, which are complicated and difficult to precisely acquire due to high nonlinearities in pressure dynamics and a number of unknown parameters that need to be identified from experimental input-output data [16].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Robust Position Control of Electro-Hydraulic Servo Systems with Large Uncertainties and Disturbances

2022

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In this paper, a novel adaptive robust control (ARC) scheme is proposed for electro-hydraulic servo systems (EHSSs) with uncertainties and disturbances. All dynamic functions in system dynamics are effectively approximated by multi-layer radial basis function neural network (RBF NN)-based approximators with online adaptive mechanisms. Moreover, neural network-based disturbance observers (NN-DOBs) are established to actively estimate and efficiently compensate for the effects of not only the matched/mismatched but also the imperfections of RBF NN-based approximators on the control system. Based on that, the nonlinear robust control law which integrates RBF NNs and NN-DOBs is synthesized via the sliding mode control (SMC) approach to guarantee the high-accuracy position tracking performance of the overall control system. Furthermore, the problem of the combination between DOBs and RBF NNs is first introduced in this paper to treat both disturbances and uncertainties in the EHSS. The stability of the recommended control mechanism is proven by using Lyapunov theory. Finally, numerical simulations with several distinct frequency levels of reference trajectory are conducted to convincingly demonstrate the effectiveness of the proposed approach.

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Section: Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Robust Position Control of Electro-Hydraulic Servo Systems with Large Uncertainties and Disturbances

2022

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“…Usually these are 1st order transfer functions where the time constant is in the order of milliseconds, thus allowing a simplified approach to the reduction of these transfer functions to constants. The transfer function of the inverter is as follows: (15) where:…”

Section: Mathematical Model Of Pmsm Transfer Function Representationmentioning

confidence: 99%

Sensorless Fractional Order Control of PMSM Based on Synergetic and Sliding Mode Controllers

Nicola¹,

Nicola

2020

Electronics

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The field oriented control (FOC) strategy of the permanent magnet synchronous motor (PMSM) includes all the advantages deriving from the simplicity of using PI-type controllers, but inherently the control performances are limited due to the nonlinear model of the PMSM, the need for wide-range and high-dynamics speed and load torque control, but also due to the parametric uncertainties which occur especially as a result of the variation of the combined rotor-load moment of inertia, and of the load resistance. Based on the fractional calculus for the integration and differentiation operators, this article presents a number of fractional order (FO) controllers for the PMSM rotor speed control loops, and id and iq current control loops in the FOC-type control strategy. The main contribution consists of proposing a PMSM control structure, where the controller of the outer rotor speed control loop is of FO-sliding mode control (FO-SMC) type, and the controllers for the inner control loops of id and iq currents are of FO-synergetic type. Superior performances are obtained by using the control system proposed, even in the case of parametric variations. The performances of the proposed control system are validated both by numerical simulations and experimentally, through the real-time implementation in embedded systems.

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“…Sliding mode control (SMC) is a non-linear strategy with a discontinuity that drives the system in a sliding surface [10]. The main advantage is the robustness against uncertainties and external disturbances.…”

Section: Introductionmentioning

confidence: 99%

Advanced Trajectory Control for Piezoelectric Actuators Based on Robust Control Combined with Artificial Neural Networks

et al. 2021

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In applications where high precision in micro- and nanopositioning is required, piezoelectric actuators (PEA) are an optimal micromechatronic choice. However, the accuracy of these devices is affected by a natural phenomenon called “hysteresis” that even increases the instability of the system. This anomaly can be counteracted through a material re-shape or by the design of a control strategy. Through this research, a novel control design has been developed; the structure contemplates an artificial neural network (ANN) feedforward to contract the non-linearities and a robust close-loop compensator to reduce the unmodelled dynamics, uncertainties and perturbations. The proposed scheme was embedded in a dSpace control platform with a Thorlabs PEA; the parameters were tuned online through specific metrics. The outcomes were compared with a conventional proportional-integral-derivative (PID) controller in terms of control signal and tracking performance. The experimental gathered results showed that the advanced proposed strategy had a superior accuracy and chattering reduction.

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Active Disturbance Compensation Based Robust Control for Speed Regulation System of Permanent Magnet Synchronous Motor

Cited by 15 publications

References 28 publications

Adaptive Robust Position Control of Electro-Hydraulic Servo Systems with Large Uncertainties and Disturbances

Adaptive Robust Position Control of Electro-Hydraulic Servo Systems with Large Uncertainties and Disturbances

Sensorless Fractional Order Control of PMSM Based on Synergetic and Sliding Mode Controllers

Advanced Trajectory Control for Piezoelectric Actuators Based on Robust Control Combined with Artificial Neural Networks

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