Control of drinking water networks is an arduous task given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances due to the stochastic water demand/consumption, and optimize operational costs, this paper proposes three st...

We present a computationally efficient scheduled model predictive control (MPC) algorithm for constrained nonlinear systems with large operating regions. We design a set of local predictive controllers with estimates of their regions of stability covering the desired operating region, and implement them as a single scheduled MPC which on-line switches between the set of local controllers and ac...

Energy storage system has been widely applied in power distribution sectors as well as in renewable energy sources to ensure uninterruptible power supply. This paper presents a model predictive algorithm to control a bidirectional AC-DC converter, which is used in an energy storage system for power transferring between the three-phase AC voltage supply and energy storage devices. This model pre...

This paper proposes an approach to improve stability and active control of rotor vibration by the use of Model Predictive controller. Rotor vibrations in electrical machines are dampen out by model predictive control algorithm. The controlled system is the one dimensional Jeffcott-rotor. Model predictive control algorithm was designed, and the simulation results were obtained by Mat lab softwar...

Dynamic Matrix Control (DMC) is a widely used model predictive controller (MPC) in industrial plants. The successful implementation of DMC in practical applications requires a proper tuning of the controller. The available tuning procedures are mainly based on experience and empirical results. This paper develops an analytical tool for DMC tuning. It is based on the application of Analysis of V...

Model predictive control (MPC) is implemented on several distillation columns at the Kårstø gas processing plant, Norway. The paper describes the procedure in the implementation of MPC at a deethanizer using the SEPTIC ∗ MPC tool, including design, estimator development, model development and tuning. For the deethanizer, the variance in the product quality has been reduced with about 50%. The n...

Abstract: Model predictive control (MPC) has been widely studied for regulating frequency in stand-alone microgrids (MGs), owing to the advantages of MPC such as fast response and robustness against the parameter uncertainties. Understanding the impacts of system parameters on the control performance of MPC could be useful for the designing process of the controller to achieve better performanc...

This paper presents a model predictive control (MPC) of a utility interactive (UI) single phase inverter (SPI) for a photovoltaic (PV) system at residential/distribution level. The proposed model uses single-phase phase locked loop (PLL) to synchronize SPI with the grid and performs MPC control in a dq reference frame. SPI model consists of boost converter (BC), maximum power point tracking (MP...

This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize the TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of a boost converter (BC), maximum power point tracking (MPPT) co...

In AC-DC power conversion, active front end rectifiers offer several advantages over diode rectifiers such as bidirectional power flow capability, sinusoidal input currents and controllable power factor. A digital finite control set model predictive controller based on fixed-point computations of an active front end rectifier with unity displacement of input voltage and current to improve dynam...