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[This paper considers longitudinal and lateral tire-stiffness estimation for road vehicles, using wheel-speed and inertial measurements. The deviations from nominal stiffness values are treated as disturbances acting on the vehicle, and are included in a nonlinear vehicle model. We formulate a Bayesian approach based on particle filtering, where the tire stiffness as well as the associated uncertainty...
We extend a recently developed design for indirect adaptive model predictive control (IAMPC) and presents additional results on its stability properties. The IAMPC guarantees constraints satisfaction including during the learning transient, is input-to-state stable (ISS) with respect to the parameter estimation error, and has computational burden comparable to that of non-adaptive MPC. In this paper...
For stabilizing model predictive control adjusting the prediction model requires the adjustment of the terminal set and terminal cost. However, the conventional methods to design these are not practical, and often impossible, to implement in microcontrollers. In this paper, we pre-compute the terminal cost and terminal set in a form that allows to adjust them with minimal computational effort, following...
This paper provides a tutorial overview of reference governors and command governors, which are add-on control schemes for reference supervision and constraint enforcement in closed-loop feedback control systems. The main approaches to the development of such schemes for linear and nonlinear systems are described. The treatment of unmeasured disturbances and parametric uncertainties is addressed....
We develop nonlinear reference governor and nonlinear model predictive control schemes for constrained spacecraft attitude control. The schemes use the nonlinear discrete-time model of spacecraft dynamics based on the Lie group variational integrator evolving on SO(3) × SO(3). The reference governor is a computationally simpler add-on to the nominal controller, while the model predictive controller...
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