To address the issues of functional conflicts in execution subsystems and the
deterioration of control performance due to model parameter uncertainties in the
motion control of distributed vehicle by wire, this article proposes an
integrated control strategy considering parameter robustness. This strategy aims
to compensate for model mismatch, resolve functional conflicts, and achieve
motion coordination. Based on the over-actuation characteristics of distributed
vehicle by wire, this article constructs the dynamic model and utilizes the tire
cornering properties along with phase portraits to delineate the working regions
of the execution subsystems. To deal with model parameter uncertainties and
mismatch, tube-based model predictive control (tube-based MPC) is applied to the
control strategy design, which compensates for model deviations through state
feedback and constructs a robust positively invariant set (RPI) to constrain the
system state. Correspondingly, the weights of control inputs are adjusted
adaptively, according to the working regions, to optimize the coordination logic
of integrated control. In order to verify the effectiveness and feasibility of
the strategy, extreme driving condition tests are executed on
hardware-in-the-loop (HIL) and real vehicle test platforms. The test results
indicate that the strategy proposed in this article is able to reduce the
sideslip angle and tracking error of yaw rate, improve driving stability under
extreme conditions through integrated control, and especially, it can still
maintain precise stability control performance under severe model mismatch,
exhibiting strong robustness facing parameter uncertainties.
