Nonlinear control of synchronous servo drive

Grcar, B.; Cafuta, P.; Znidaric, M.

doi:10.1049/cp:19940307

Cited by 18 publications

(13 citation statements)

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“…With the development of modern control theory techniques, many researchers have proposed some control schemes to control servo system, such as backstepping method [5], robust control [6], adaptive control [7,8], input-output linearization control [9], slidingmode control (SMC) [10], and feedback linearization technique. Moreover, the artificial intelligent techniques have also been used for PMSM, e.g., neural network (NN) [11,12], fuzzy logic system (FLs) [13].…”

Section: Introductionmentioning

confidence: 99%

Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction

Wang

Ren

et al. 2016

2016 35th Chinese Control Conference (CCC)

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Section: Introductionmentioning

confidence: 99%

Robust Integral of Sign of Error and Neural Network Control for Servo System with Continuous Friction

Wang

Ren

et al. 2016

2016 35th Chinese Control Conference (CCC)

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“…However, the precise control of PMSM is susceptible to motor parameter, load torque and unmodeled dynamic, and the traditional proportional-integral (PI) control method can not guarantee a sufficiently high performance for PMSM control system. To enhance the control performance, many advanced control methods have been developed for the PMSM system, such as linearization control [1], sliding mode control [2], backstepping control [3], predictive control [4], and so on. These approaches can improve the control performance of the motor from different aspects.…”

Section: Introductionmentioning

confidence: 99%

Robust current control of PMSM based on PCH and disturbance observer

Liu

Sun

et al. 2014

Proceedings of the 33rd Chinese Control Conference

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A new robust current control method of permanent magnet synchronous motor (PMSM) based on Port-controlled Hamiltonian (PCH) theory and disturbance observer is proposed in this paper. Firstly, the electromagnetic subsystem of PMSM is expressed as the PCH form. Then, the current tracking control is realized using the energy-shaping method of interconnection and damping assignment, and the stability in the equilibrium is proved. In addition, according to the parameter perturbation of the PMSM, a disturbance observer is designed to estimate the disturbance, which is used to the feedforward compensation control of the current loop. The simulation results show that the proposed control method has good current tracking performance and robustness.

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“…Linear control methods such as proportional-integral (PI) control scheme are already widely used in PMSM systems due to their easy implementation. However, PMSM system is a nonlinear system with unavoidable and unmeasured disturbances and parameter variations [2], it is difficult to achieve a satisfactory performance in the entire operating rage when using such linear control methods [3,4]. Hence, nonlinear control methods become natural improved solutions for PMSM system.…”

Section: Introductionmentioning

confidence: 99%

“…With the development of microprocessor technology, especially digital signal processors (DSPs), power electronics and modern control theories, more and more advanced control methods are introduced to the PMSM control problem, e.g., adaptive control [5][6][7][8], robust control [9], sliding mode control [10,11], inputoutput linearization control [3,12], backstepping control [13,14], fractional order control [15], neural network control [4], fuzzy control [16], and finite-time control [17], etc. These methods can improve the performance of the PMSM systems from different aspects.…”

Section: Introductionmentioning

confidence: 99%