In the last few years, the application of Model Predictive Control (MPC) for energy management
in buildings has received significant attention from the research community. MPC is …

Model-based design is well recognized in industry as a systematic approach to the development,
evaluation, and implementation of feedback controllers. Model predictive control (MPC) …

This paper proposes a framework for modeling and controlling systems described by
interdependent physical laws, logic rules, and operating constraints, denoted as mixed logical …

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 optimal …

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 a …

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

Explicit solutions to constrained linear model predictive control problems can be obtained
by solving multi-parametric quadratic programs (mp-QP) where the parameters are the …

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 establishes equivalences among five classes of hybrid systems: mixed logical
dynamical (MLD) systems, linear complementarity (LC) systems, extended linear …

Decentralized and distributed model predictive control (DMPC) addresses the problem of
controlling a multivariable dynamical process, composed by several interacting subsystems …