Model predictive control (MPC) based methods are gaining more and more attention in power converters and electrical drives. Nevertheless, high computational burden of MPC is an obstacle for its application, especially when the prediction horizon increases extends. At the same time, increasing the prediction horizon leads to a superior response. In this paper, a long horizon MPC is proposed to c...

Hardware complexity of a motor drive can be reduced by estimating controls rather than measuring using sensors. In this way the corresponding sensors are eliminated and the system becomes more robust. This article is about speed control of a sensor less induction motor with predictive current controller technique. This particular speed control technique does not require direct measurements of m...

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 ...

This paper proposes a new convex model predictive control strategy for dynamic optimal power flow between battery energy storage systems distributed in an AC microgrid. The proposed control strategy uses a new problem formulation, based on a linear d–q reference frame voltage-current model and linearised power flow approximations. This allows the optimal power flows to be solved as a convex opt...

In this paper an issue of data dropout in networked control systems is solved. The model predictive control approach is used where the future control inputs up to a given horizon are evaluated at each sampling instant. In case the current output value is lost and the control input can not be computed, the future control input calculated at previous sampling instant can be used instead. The prop...

The purpose of this paper is to describe the importance of the underlying relationship between control strategy design and model predictive control. Successes and problems encountered when implementing model predictive control (MPC) on chemical processes have revealed that understanding this relationship provides insight into the nature of the process control problem. Model predictive control (...

The excursion of maximum power point always exists due to nonlinear and time-varying characteristics of photovoltaic (PV) generation. To solve this problem, the maximum power point tracking (MPPT) control strategy based on generalized predictive control (GPC) is put forward. Firstly, the theory and feature of PV cell is analyzed, and the MPPT control model is constituted based on Boost circuit....