CONTROLLER design is more troublesome in aerospace systems due to, inter alia, diversity
of mission platforms, convoluted nonlinear dynamics, predominantly strict mission and …

The paper provides a reasonably accessible and self-contained tutorial exposition on model
predictive control (MPC). It is aimed at readers with control expertise, particularly …

We present a general-purpose solver for convex quadratic programs based on the
alternating direction method of multipliers, employing a novel operator splitting technique …

Data-driven discovery of dynamics via machine learning is pushing the frontiers of modelling
and control efforts, providing a tremendous opportunity to extend the reach of model …

Data-driven transformations that reformulate nonlinear systems in a linear framework have
the potential to enable the prediction, estimation, and control of strongly nonlinear dynamics …

The control problem was formulated in the previous chapters considering all signals to
possess an unlimited range. This is not very realistic because in practice all processes are …

This paper provides an overview of commercially available model predictive control (MPC)
technology, both linear and nonlinear, based primarily on data provided by MPC vendors. A …

This paper provides a novel solution to the problem of robust model predictive control of
constrained, linear, discrete-time systems in the presence of bounded disturbances. The …

In this paper, we present an automatic C-code generation strategy for real-time nonlinear
model predictive control (NMPC), which is designed for applications with kilohertz sample …

An efficient Newton-type scheme for the approximate on-line solution of optimization
problems as they occur in optimal feedback control is presented. The scheme allows a fast …