Model Predictive Control (MPC) refers to a class of algorithms that compute a sequence of manipulated variable adjustments in order to optimize the future behaviour of a plant. MPC technology can now be found in a wide variety of application areas. The neural network predictive controller that is discussed in this paper uses a neural network model of a nonlinear plant to predict future plant pe...

Over the recent years many advances in the area of nonlinear model predictive control have been made. However, with respect to the output feedback problem and predictive control only a limited number of results are available. Most of the existing approaches do only guarantee local stability. In this note we propose the use of a high gain observer in combination with a sampled nonlinear predicti...

Economic Model Predictive Control differs from conventional tracking model predictive control by directly addressing a plants economic cost as the stage cost, consequently leading to better economic performance. This paper extends current economic model predictive control theory to linear timeinvariant systems with periodic disturbances and cost functions, under mild assumptions. To ensure an i...

In modern inverter fed drive applications the power semiconductors used are typically designed to operate at their maximum thermal operation conditions. Semiconductors worst case thermal considerations in general define the uppermost inverter switching frequency dependent on maximum load current. Fixing this frequency to a constant value, the drive will not be operated with best possible perfor...

In order to prevent flooding along the Demer in Belgium, the local water administrations has installed hyraulic structures and flood reservoirs along the river. Though these actions have reduced the damage and frequency of flooding events, simulations have shown that an improved regulation could further decrease the flood risk. In this study a real time control procedure is being developed by m...

This paper aims to present the development, design and analysis of a control scheme named Thermal Model Predictive Control for Demand Side Management Cooling Strategies. The control is implemented on a building in Athens whose thermal model is derived using the Finite Difference Calculation Method. The development and testing of the thermal model is implemented on-line while the predictive cont...

This paper proposes the development of a fuzzy predictive control. Genetic algorithms (GA’s) are used to automatically tune the controller. A recurrent neural network is used to identify the process, and then provides predictions about the process behavior, based on control actions applied to the system. These predictions are used by the fuzzy controller, in order to accomplish a better control...