In this paper, an alternating direction method of multipliers (ADMM) based realtime model predictive control (MPC) algorithm is presented. With the use of indicator function and by introducing extra consensus constraints, the constrained MPC problem can be formulated as a separable MPC problem, which can be computed very efficiently by projected gradient descent ADMM update steps and Riccati re...

This paper is a contribution to the theory of the infinitehorizon linear quadratic regulator (LQR) problem subject to inequality constraints on the inputs and states, extending an approach first proposed by Sznaier and Damborg [16]. A solution algorithm is presented, which requires solving a finite number of finite-dimensional positive definite quadratic programs. The constrained LQR outlined d...

An increasing number of applications ranging from multi-vehicle systems, largescale process control systems, transportation systems to smart grids call for the development of cooperative control theory. Meanwhile, when designing the cooperative controller, the state and control constraints, ubiquitously existing in the physical system, have to be respected. Model predictive control (MPC) is one...

Model Predictive Control (MPC) is an established control technique in a wide range of process industries. The reason for this success is its ability to handle multivariable systems and systems having input, output or state constraints. Neverthless comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers ha...

It is well-known that linear constrained model predictive control has a nonlinearity that is continuous and piecewise affine. Under certain feasibility conditions the nonlinearity may be sector bounded and shown to satisfy sufficient conditions for the existence of Zames-Falb multipliers. Thus the nonlinearity satisfies a wide class of integral quadratic constraint (IQC). Standard analysis then...

The paper addresses a case study of robust stabilization of a continuous stirred tank reactor using robust model-based predictive control with constrained input variables. One exothermic reaction runs in the reaction mixture and the reactor is modelled in the form of an uncertain polytopic system. The control approach is based on solution of a set of linear matrix inequalities. This formulation...