Model predictive control (MPC) has demonstrated exceptional success for the high-
performance control of complex systems. The conceptual simplicity of MPC as well as its …

In the past ten years many Stochastic Model Predictive Control (SMPC) algorithms have
been developed for systems subject to stochastic disturbances and model uncertainties …

One of the motivations behind this book was to collect together the many results of the
Oxford University predictive control group. For this reason we have, rather unashamedly …

Agriculture plays a decisive role in the survival of humankind. The efficient and precise
regulation of agriculture will ensure the welfare of people throughout the world. However …

For most atmospheric or exo-atmospheric spacecraft flight scenarios, a well-designed
trajectory is usually a key for stable flight and for improved guidance and control of the …

An output feedback stochastic model predictive control is proposed in this article for a class
of stochastic linear discrete-time systems, in which the uncertainties from external …

In this paper, we discuss the model predictive control algorithms that are tailored for
uncertain systems. Robustness notions with respect to both deterministic (or set based) and …

Autonomous racing is a high-performance, safety-critical task that inherently involves a high
degree of uncertainty (especially in off-road unstructured environments), as driving …

In autonomous systems, the ability to make forecasts and cope with uncertain predictions is
synonymous with intelligence. Model predictive control (MPC) is an established control …

In this paper we propose an output-feedback Model Predictive Control (MPC) algorithm for
linear discrete-time systems affected by a possibly unbounded additive noise and subject to …