A Novel Nonlinear Model Predictive Control Strategy for a Class of Nonlinear Systems with Multiple Actuators’ Response Time-Delays

<div class="section abstract"><div class="htmlview paragraph">This paper investigates the problem of nonlinear model predictive control (NMPC) strategy for a class of nonlinear systems with multiple actuators’ response time-delays. Conventional approaches that incorporate these time-delays into the NMPC formulation typically result in a significant increase in the optimization problem's scale. To address these problems, we propose a novel NMPC strategy. In the first stage, the NMPC strategy is designed for the nonlinear system without considering actuator’s response time-delay, thereby maintaining the original scale of the optimization problem. The optimal control sequence derived from this NMPC is then fitted to a time-continuous polynomial function, serving as a reference signal for the actuators' response time-delay models. In the second stage, combining inverse model and inverse Laplace transform techniques, a novel inverse model compensation control (IMCC) strategy is designed for actuators’ response time-delays. This IMCC strategy enables tracking of the reference signal without phase time-delay or amplitude deviation. For comparative analysis, we also implement a model augmentation NMPC strategy that directly incorporates actuators’ time-delays, inevitably increasing the scale of the optimization problem. By quantitative analysis, the model augmentation NMPC strategy will increase the number of optimal variables and equality constraints of the optimization problem. Finally, vehicle control of transport vehicle in open-pit mine is taken as simulation example, the simulation results show that both the proposed novel NMPC and IMCC algorithms and model augmentation NMPC algorithm can achieve high precision control performance, the maximum and average calculation time of the proposed novel NMPC and IMCC algorithms are 31.9% and 46.2% lower than that of model augmentation NMPC algorithm, respectively.</div></div>

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Publication Details

Journal
SAE technical papers on CD-ROM/SAE technical paper series
Published
2025-03-31
DOI
https://doi.org/10.4271/2025-01-8028
Citations
1
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
1.21
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article

A Novel Nonlinear Model Predictive Control Strategy for a Class of Nonlinear Systems with Multiple Actuators’ Response Time-Delays

Bin Wang
1 citations
SAE technical papers on CD-ROM/SAE technical paper series
Advanced Control Systems Optimization
1.21
article

A Novel Nonlinear Model Predictive Control Strategy for a Class of Nonlinear Systems with Multiple Actuators’ Response Time-Delays

Bin Wang
article en
1 citations

Abstract

<div class="section abstract"><div class="htmlview paragraph">This paper investigates the problem of nonlinear model predictive control (NMPC) strategy for a class of nonlinear systems with multiple actuators’ response time-delays. Conventional approaches that incorporate these time-delays into the NMPC formulation typically result in a significant increase in the optimization problem's scale. To address these problems, we propose a novel NMPC strategy. In the first stage, the NMPC strategy is designed for the nonlinear system without considering actuator’s response time-delay, thereby maintaining the original scale of the optimization problem. The optimal control sequence derived from this NMPC is then fitted to a time-continuous polynomial function, serving as a reference signal for the actuators' response time-delay models. In the second stage, combining inverse model and inverse Laplace transform techniques, a novel inverse model compensation control (IMCC) strategy is designed for actuators’ response time-delays. This IMCC strategy enables tracking of the reference signal without phase time-delay or amplitude deviation. For comparative analysis, we also implement a model augmentation NMPC strategy that directly incorporates actuators’ time-delays, inevitably increasing the scale of the optimization problem. By quantitative analysis, the model augmentation NMPC strategy will increase the number of optimal variables and equality constraints of the optimization problem. Finally, vehicle control of transport vehicle in open-pit mine is taken as simulation example, the simulation results show that both the proposed novel NMPC and IMCC algorithms and model augmentation NMPC algorithm can achieve high precision control performance, the maximum and average calculation time of the proposed novel NMPC and IMCC algorithms are 31.9% and 46.2% lower than that of model augmentation NMPC algorithm, respectively.</div></div>

SAE technical papers on CD-ROM/SAE technical paper seriesVol. 1
Tongji University (CN)
Openalex Percentile: Top 23%
Advanced Control Systems Optimization
1.21
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A Novel Nonlinear Model Predictive Control Strategy for a Class of Nonlinear Systems with Multiple Actuators’ Response Time-Delays — Bin Wang · SAE technical papers on CD-ROM/SAE technical paper series (2025) | TGRS Research Map | TGRS