Fault tolerant longitudinal control of an over-actuated off-road vehicle

Vera, S.; Basset, Michel; Khelladi, Faïza

doi:10.1016/j.ifacol.2022.04.133

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…The study indicates it could realize the different control objectives with different control allocations. In studies of coordinating the operations of healthy and fault motors, usually direct control allocation [36], pseudoinverse [37], linear programming methods [38], and quadratic programming methods [39] in fault conditions.…”

Section: Introductionmentioning

confidence: 99%

Torque Fault-Tolerant Hierarchical Control of 4WID Electric Vehicles Based on Improved MPC and SMC

Huang,

Zha,

et al. 2023

IEEE Access

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The 4-wheel independent drive (4WID) electric vehicle has better safety and stability. However, the multi-motor drive system would lead to an increased fault probability in the vehicle. In particular, the uncertainty of fault motors and parameter disturbances could lead to uncertainties in control. This study presents a fault-tolerant hierarchical control approach that utilizes an improved Model Predictive Control (MPC) to address the problem. The proposed method employs Sliding Mode Control (SMC) in the upper layer to generate the vehicle's yaw moment, which could inhibit system parameter disturbance and improve the system's robustness. Incorporating the fault matrix induced by motor malfunctions, the statespace equation of the vehicle is modified to establish a vehicle dynamics model under motor faults. In the lower layer, the torque reconstruction allocation strategy is designed to coordinate the four motors under the motor fault condition by the MPC rolling optimization online, which could reduce the impact of the motor fault uncertainty for fault-tolerant control. The multi-constraint conditions of MPC are set up according to the vehicle state parameters. To address the additional yaw moment caused by the MPC torque reconfiguration allocation control strategy, the torque transfer method is used as the input allocation for MPC. Finally, the proposed control strategy is verified by online simulation. The simulation outcomes demonstrate the effectiveness of the proposed hierarchical fault-tolerant control approach in achieving fault-tolerant control of the 4WID electric vehicle, with the improved MPC outperforming the conventional MPC in terms of performance.INDEX TERMS 4-wheels independent drive electric vehicle, fault-tolerant hierarchical control, failure factor, improved MPC, SMC

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Section: Introductionmentioning

confidence: 99%

Torque Fault-Tolerant Hierarchical Control of 4WID Electric Vehicles Based on Improved MPC and SMC

Huang,

Zha,

et al. 2023

IEEE Access

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Deep Reinforcement Learning-Based Failure-Safe Motion Planning for a 4-Wheeled 2-Steering Lunar Rover

Park

Chung

2023

Aerospace

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The growing trend of onboard computational autonomy has increased the need for self-reliant rovers (SRRs) with high efficiency for unmanned rover activities. Mobility is directly associated with a successful execution mission, thus fault response for actuator failures is highly crucial for planetary exploration rovers in such a trend. However, most of the existing mobility health management systems for rovers have focused on fault diagnosis and protection sequences that are determined by human operators through ground-in-the-loop solutions. This paper presents a special four-wheeled two-steering lunar rover with a modified explicit steering mechanism, where each left and right wheel is controlled by only two actuators. Under these constraints, a new motion planning method that combines reinforcement learning with the rover’s kinematic model without the need for dynamics modeling is devised. A failure-safe algorithm is proposed to address the critical loss of mobility in the case of steering motor failure, by expanding the devised motion planning method, which is designed to ensure mobility for mission execution in a four-wheeled rover. The algorithm’s performance and applicability are validated through simulations on high-slip terrain scenarios caused by steering motor failure and compared with a conventional control method in terms of reliability. This simulation validation serves as a preliminary study toward future works on deformable terrain such as rough or soft areas and optimization of the deep neural network’s weight factor for fine-tuning in real experiments. The failure-safe motion planning provides valuable insights as a first-step approach toward developing autonomous recovery strategies for rover mobility.

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Fault tolerant longitudinal control of an over-actuated off-road vehicle

Cited by 2 publications

References 13 publications

Torque Fault-Tolerant Hierarchical Control of 4WID Electric Vehicles Based on Improved MPC and SMC

Torque Fault-Tolerant Hierarchical Control of 4WID Electric Vehicles Based on Improved MPC and SMC

Deep Reinforcement Learning-Based Failure-Safe Motion Planning for a 4-Wheeled 2-Steering Lunar Rover

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