A question that often process control engineers face is for what class of processes one should use model predictive control that requires solving numerically a constrained optimization problem repeatedly on-line. The alternative is to use analytical control, such as P, PI, PID and differential geometric control, which do not require the on-line optimization. In other words, for what class of pr...

Continued great efforts have been dedicated toward high-quality trajectory generation based on optimization methods; however, most of them do not suitably and effectively consider the situation with moving obstacles; more particularly, future position these obstacles in presence uncertainty within some possible prescribed prediction horizon. To cater to this rather major shortcoming, work shows...

In this paper, a regulation control problem for constrained nonlinear systems with quantized inputs is formulated as a Model Predictive Control (MPC) problem. The MPC problem is represented as a multi-parametric Nonlinear Integer Programming (mp-NIP) problem and a computational method to find an explicit approximate solution of this problem is considered. It consists in constructing a feasible ...

A hybrid control structure that unites bounded control with model predictive control (MPC) is proposed for the constrained stabilization of nonlinear systems. The structure consists of: (1) a finite-horizon model predictive controller, which can be linear or nonlinear, and with or without stability constraints, (2) a family of bounded nonlinear controllers for which the regions of constrained c...

Autonomous surface vehicles are with increasing popularity being seen in various applications where automatic control plays an important role. In this paper the problem of twodimensional trajectory tracking for autonomous marine surface vehicles is addressed using Model Predictive Control (MPC). At each time step, the reference trajectories of a vessel are assumed to be known over a finite time...

This work addresses the implementation issue of constrained Model Predictive Control (MPC) for the autonomous trajectory-tracking problem. The chosen process to control is a Wheeled Mobile Robot (WMR) described by a discrete, Multiple Input Multiple Output (MIMO), state-space and linear parameter varying kinematic model. The main motivation of the constrained MPC usage in this case relies on it...

This paper deals with the control of a powder coating radiative curing process by infrared flow. It is based on a unidirectional dynamic modelling where both heat transfert and cure phenomena are accounted for within the thicknessl. The control problem is the constrained optimization of the curing cycle. This is solved using a special model predictive control framework: it is designed such that...

We present CODEV, a Matlab-based tool for verifying systems employing Model Predictive Control (MPC). The MPC solution is computed offline and modeled together with the physical system as a hybrid automaton, whose continuous dynamics may be nonlinear with a control solution that remains affine. While MPC is a widely used synthesis technique for constrained and optimal control in industry, our t...

the control of fluidized-bed operations processes is still one of the major areas of research due to the complexity of the process and the inherent nonlinearity and varying dynamics involved in its operation. there are varieties of problems in chemical engineering that can be formulated as nonlinear programming (nlps). the quality of the developed solution significantly affects the performance ...