Trajectory-Following and Off-Tracking Minimization of Long Combination Vehicles: A Comparison Between Nonlinear and Linear Model Predictive Control
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| Title: | Trajectory-Following and Off-Tracking Minimization of Long Combination Vehicles: A Comparison Between Nonlinear and Linear Model Predictive Control |
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| Authors: | Ghandriz, Toheed, 1982, Jacobson, Bengt J H, 1962, Nilsson, Peter, 1976, Laine, Leo, 1972 |
| Source: | Distribuerad framdrivning mellan enheter i en lång fordonskombination High Capacity Vehicles with ELectrically PropellEd Dolly (HELPED) Vehicle System Dynamics. 62(2):277-310 |
| Subject Terms: | nonlinear model predictive control, direct optimal control, motion control, long combination vehicles, off-tracking minimization, vehicle dynamics |
| Description: | In this paper, we compared the linear and nonlinear motion prediction models of a long combination vehicle (LCV). We designed a nonlinear model predictive control (NMPC) for trajectory-following and off-tracking minimisation of the LCV. The used prediction model allowed coupled longitudinal and lateral dynamics together with the possibility of a combined steering, propulsion and braking control of those vehicles in long prediction horizons and in all ranges of forward velocity. For LCVs where the vehicle model is highly nonlinear, we showed that the control actions calculated by a linear time-varying model predictive control (LTV-MPC) are relatively close to those obtained by the NMPC if the guess linearisation trajectory is sufficiently close to the nonlinear solution, in contrast to linearising for specific operating conditions that limit the generality of the designed function. We discussed how those guess trajectories can be obtained allowing off-line fixed time-varying model linearisation that is beneficial for real-time implementation of MPC in LCVs with long prediction horizons. The long prediction horizons are necessary for motion planning and trajectory-following of LCVs to maintain stability and tracking quality, e.g. by optimally reducing the speed prior to reaching a curve, and by generating control actions within the actuators limits. |
| File Description: | electronic |
| Access URL: | https://research.chalmers.se/publication/518834 https://research.chalmers.se/publication/534182 https://research.chalmers.se/publication/534182/file/534182_Fulltext.pdf |
| Database: | SwePub |
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Nájsť tento článok vo Web of Science | Abstract: | In this paper, we compared the linear and nonlinear motion prediction models of a long combination vehicle (LCV). We designed a nonlinear model predictive control (NMPC) for trajectory-following and off-tracking minimisation of the LCV. The used prediction model allowed coupled longitudinal and lateral dynamics together with the possibility of a combined steering, propulsion and braking control of those vehicles in long prediction horizons and in all ranges of forward velocity. For LCVs where the vehicle model is highly nonlinear, we showed that the control actions calculated by a linear time-varying model predictive control (LTV-MPC) are relatively close to those obtained by the NMPC if the guess linearisation trajectory is sufficiently close to the nonlinear solution, in contrast to linearising for specific operating conditions that limit the generality of the designed function. We discussed how those guess trajectories can be obtained allowing off-line fixed time-varying model linearisation that is beneficial for real-time implementation of MPC in LCVs with long prediction horizons. The long prediction horizons are necessary for motion planning and trajectory-following of LCVs to maintain stability and tracking quality, e.g. by optimally reducing the speed prior to reaching a curve, and by generating control actions within the actuators limits. |
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| ISSN: | 17445159 00423114 |
| DOI: | 10.1080/00423114.2022.2164513 |