Model Predictive Control (MPC) is increasingly being proposed for application to miniaturized devices, fast and/or embedded systems. A major obstacle to this is its computation time requirement. Continuing our previous studies of implementing constrained MPC on Field Programmable Gate Arrays (FPGA), this paper begins to exploit the possibilities of parallel computation, with the aim of speeding...

In this paper we present a framework for achieving constrained optimal real-time control for large-scale systems with fast dynamics. The methodology uses the explicit solution of the model predictive control (MPC) problem combined with model reduction, in an output-feedback implementation. The explicit solution of the MPC problem leads to online MPC functionality without having to solve an opti...

In this work, an investigation has been made in to the performance of latent variable MPC (LV-MPC) in the specific application of reactor temperature control of an exothermic batch process. The paper analyzes the LV-MPC control law derivation and its performance within a batch application. The article considers both constrained and unconstrained applications.

Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) describes systems with nonlinear models and/or constraints. Continuation MPC, suggested by T. Ohtsuka in 2004, uses Krylov-Newton iterations. Continuation MPC is suitable for nonlinear problems and has been recently adopted for minimum time problems. We extend the continuation MPC ...

In this paper we present the design of a linear constrained MPC controller for magnetic actuated small satellites. The controller may be derived by formulating a linear constrained MPC problem as a multi-parametric quadratic program (mpQP). The solution will be a piecewise affine (PWA) function, which may be evaluated at each sample to obtain the optimal control law. We apply this approach to t...

One of the strengths of Model Predictive Control (MPC) is its ability to incorporate constraints in the control formulation. Often a disturbance drives the system into a region where the MPC problem is infeasible and hence no control action can be computed. Feasibility can be recovered by softening the constraints using slack variables. This approach does not necessarily guarantee that the cons...

This paper presents a constrained finite horizon model predictive control (MPC) scheme for regulation of the annular pressure in a well during managed pressure drilling from a floating vessel subject to heave motion. In addition the robustness of a controller to deal with heave disturbances despite uncertainties in the friction factor and bulk modulus is investigated. The stochastic model descr...

Model predictive control (MPC) includes a receding-horizon control techniques based on the process model for predictions of the plant output. Since late 1970’s several MPC approaches have been reported in the literature. Selection of the most appropriate MPC approach depend on the specific problem. In this paper, discrete time MPC is applied to a inverted pendulum system coupled to a cart. The ...