mpC is a medium-level parallel language for programming heterogeneous networks of computers. It allows to write libraries of parallel routines adaptable to peculiarities of any particular executing mul-tiprocessor system to ensure eecient running. The adaptable routines distribute data and computations in accordance with performances of participating processors. In this case even the problems t...

This paper presents a MPC (Model Predictive Control) algorithm for MEMS vibratory gyroscopes based on force-balancing control strategy. In the proposed MPC method, using a set of orthonormal basis functions named Laguerre functions, a new prediction and optimization technique is designed. To enhance the capability of proposed MPC method for tracking time-varying reference trajectories, first a ...

The feasibility of model predictive control (MPC) applied to a laboratory gas turbine installation is investigated. MPC explicitly incorporates (input and output) constraints in its optimizations, which explains the choice for this computationally demanding control strategy. Strong nonlinearities, displayed by the gas turbine installation, cannot always be handled adequately by standard linear ...

Data model, planning restrictions, and objectives related to manufacturing planning and control (MPC) strongly depend on the given production process and workshop. In our opinion, these individual properties are the reason, why standard software fails to properly support decisions in MPC. In this paper, we introduce a platform, which enables a configuration process to create affordable individu...

This work presents some preliminary results of a project aimed at the application of industrial Model Predictive Control (MPC) to thermal Power Plants. The rationale which motivates this research is the need to improve the efficiency of power plants to cope with the high levels of competitions induced by the liberalization of the energy market. A detailed plant simulator is coupled to an indust...

In this paper, we study a tracking control problem for linear time-invariant systems, with model parametric uncertainties, under input and states constraints. We apply the idea of modular design introduced in [1], to solve this problem in the model predictive control (MPC) framework. We propose to design an MPC with input-to-state stability (ISS) guarantee, and complement it with an extremum se...

In this paper we present a framework for robust explicit/multi–parametric model predictive control (MPC). Based on four key steps, the proposed framework offers a systematic method for the off–line design, validation/testing and implementation of robust explicit MPC controllers for embedded systems. An important feature of the framework, is the use of a robust explicit/multi–parametric MPC tech...

Continuation model predictive control (MPC), introduced by T. Ohtsuka in 2004, uses Krylov-Newton approaches to solve MPC optimization and is suitable for nonlinear and minimum time problems. We suggest particle continuation MPC in the case, where the system dynamics or constraints can discretely change on-line. We propose an algorithm for on-line controller implementation of continuation MPC f...

BACKGROUND As a poorly water-soluble drug, the oral application of morin is limited by its low oral bioavailability. In this study, a new self-nanoemulsifying drug delivery system (SNEDDS), based on the phospholipid complex technique, was developed to improve the oral bioavailability of morin. METHODS Morin-phospholipid complex (MPC) was prepared by a solvent evaporation method and characteri...

Mineralized polymer composites (MPC) are recognized as potential fillers of bone defects. Though bioceramics exhibits quite a good bone-bonding and vascularization, it is considered to be too stiff and brittle for using alone. Thus, the use of polymer scaffold instead of bioceramics has several advantages including combining the osteoconductivity and bonebonding potential of the inorganic phase...