Online model predictive torque control for Permanent Magnet Synchronous Motors

Cimini, Gionata; Bernardini, Daniele; Bemporad, Alberto; Levijoki, Stephen

doi:10.1109/icit.2015.7125438

Cited by 49 publications

(31 citation statements)

References 24 publications

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“…The small size of the QP control structure used in this section allows its implementation for the control of a bilinear PMSM model in EMPC fashion. In comparison to the MPC scheme for PMSM developed in [12], the controller synthesis of this section directly deals with the bilinear model of the system, thus circumventing the need for using a linear discrete-time prediction model like in [12] which is valid only at nominal (or some other fixed and in advance chosen) rotational speed. Furthermore, the controller presented here is synthesized robust to the stator resistance variations caused by temperature changes, and also without the outer speedcontrol loop based on an additional PI controller, which are features both mentioned in [12] as desirable to be addressed in future research.…”

Section: A Qp-based Controller For a Bilinear System With Parametricmentioning

confidence: 99%

“…The first phase searches for feasible (i.e., stabilizing) control parameters η in (12). This is achieved by introducing a slack polynomial function into the stability certification constraint (8) (described in Section III-A) and then by minimizing its presence by using Bayesian optimization to obtain parameters η feasible in (12) (described in Section III-B).…”

Section: Controller Synthesismentioning

confidence: 99%

“…Let D be the set of tuning parameters η satisfying some basic design requirements, as defined in (12). The set containing the tuning parameters η with SOS stability certificate is {η | I σ (η) = 0 , η ∈ D}.…”

Section: B Search For Stabilizing Control Parametersmentioning

confidence: 99%

“…There is a great amount of flexibility in the choice of the cost term P(η) in (12), as it is allowed to be any performance criteria which can be evaluated for a fixed vector of tuning parameters η. A possible broadly applicable choice is an approximate evaluation of the integral of the infinite horizon trajectory cost over some set W:…”

Section: Optimization Of Performancementioning

confidence: 99%

“…the P(η) is a user-specified performance criteria for the closed-loop system with control parameters η, and the set D models some basic requirements on the tuning parameters η (e.g., a requirement that the Hessian in the cost function of a QP-based controller is symmetric positive definite) The solving of optimization problem (12) in what follows consists of two phases. The first phase searches for feasible (i.e., stabilizing) control parameters η in (12).…”

Section: Controller Synthesismentioning

confidence: 99%

See 4 more Smart Citations

Control of nonlinear systems with explicit-MPC-like controllers

Pejcic

Korda

Jones

2017

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

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Abstract-This paper describes synthesis of controllers involving Quadratic Programming (QP) optimization problems for control of nonlinear systems. The QP structure allows an implementation of the controller as a piecewise affine function, pre-computed offline, which is a technique extensively studied in the field of explicit model predictive control (EMPC). The method is based on a sum-of-squares (SOS) stability verification for polynomial discrete-time systems, described in continuous-time in this paper. The presented synthesis method allows a design of EMPC controllers with closed-loop stability guarantees without relying on a terminal cost and/or constraint, and even without using the prediction horizon concept to formulate the control optimization problem. In particular, for a specified QP structure the method directly searches for the stabilizing coefficients in the cost and/or the constraint set so that a polynomial Lyapunov function for the closed-loop system exists. The method involves two phases that are formulated as optimization problems which can be tackled by using a blackbox optimization technique, such as Bayesian optimization which is used in this paper. The synthesis is demonstrated on a numerical example involving a bilinear model of a permanent magnet synchronous machine (PMSM), where in order to demonstrate the modeling flexibility of the proposed synthesis method a QP-based controller for speed regulation of PMSM is synthesized that is robust to parametric uncertainty coming from the temperature-dependent stator resistance of the PMSM.

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Section: A Qp-based Controller For a Bilinear System With Parametricmentioning

confidence: 99%

Section: Controller Synthesismentioning

confidence: 99%

Section: B Search For Stabilizing Control Parametersmentioning

confidence: 99%

Section: Optimization Of Performancementioning

confidence: 99%

Section: Controller Synthesismentioning

confidence: 99%

See 3 more Smart Citations

Control of nonlinear systems with explicit-MPC-like controllers

Pejcic

Korda

Jones

2017

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

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Design of search space for improving the steady current control performance of PMSM current control system based on model predictive control

Shimaoka

Doki

2021

Electrical Engineering Japan

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This paper proposes a method to design the search space of Model Predictive Control (MPC) for improving the steady current control performance of Permanent Magnet Synchronous Motor (PMSM) current control system. A current control system based on MPC predicts the future current behaviors for considerable input voltage and determines the optimum input voltage by evaluating these behaviors. However, the basic MPC has inferior steady current control performance depending on the operating points. This is because the search space of basic MPC represented by voltage vectors is not suitable appropriate for PMSM current control. To overcome this problem, we consider difference of search space of basic MPC and current vector control with a modulator such as Pulse Width Modulation (PWM) or Space Vector Modulation (SVM) and clarify the necessary search space for improving the steady current control performance. Then, we propose a design method for the search space, and through experimentation, we show that proposed design method can improve the steady current control performance.

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Nonlinear model predictive torque control of PMSMs for high performance applications

Englert

Graichen

2018

Control Engineering Practice

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Online model predictive torque control for Permanent Magnet Synchronous Motors

Cited by 49 publications

References 24 publications

Control of nonlinear systems with explicit-MPC-like controllers

Control of nonlinear systems with explicit-MPC-like controllers

Design of search space for improving the steady current control performance of PMSM current control system based on model predictive control

Nonlinear model predictive torque control of PMSMs for high performance applications

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