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 …

Model Predictive Control (MPC), the dominant advanced control approach in industry over
the past twenty-five years, is presented comprehensively in this unique book. With a simple …

This paper describes a concept for a collision avoidance system for ships, which is based on
model predictive control. A finite set of alternative control behaviors are generated by …

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 …

For discrete-time linear time invariant systems with constraints on inputs and states, we
develop an algorithm to determine explicitly, the state feedback control law which minimizes …

This paper gives an overview of robustness in Model Predictive Control (MPC). After
reviewing the basic concepts of MPC, we survey the uncertainty descriptions considered in …

For discrete-time linear time-invariant systems with constraints on inputs and states, we
describe a method to determine explicitly, as a function of the initial state, the solution to …

This paper is concerned with the optimal control of linear discrete-time systems subject to
unknown but bounded state disturbances and mixed polytopic constraints on the state and …

For discrete-time uncertain linear systems with constraints on inputs and states, we develop
an approach to determine state feedback controllers based on a min-max control …

In this chapter we study the solution to optimal control problems for discrete time linear
hybrid systems. First, we show that the closed form of the state feedback solution to finite …