predictive controller

This paper presents a novel event-triggered predictive control (ETPC) approach for the stabilization of discrete-time output-feedback networked control systems (NCSs). The studied NCS is considered to be subject to both random external input and output disturbances, and network imperfections including random communication delay, random packet dropout, packet disorder, limitation of network bandwidth, and network resources. In the proposed algorithm, an observer-based event detector is designed for reducing the number of sent packets through the communication network using the estimated system states by the Luenberger observer. In this way, the system’s energy resources are saved and network-induced effects are skipped. A switched predictive controller with multiple gains are used to compensate for network-induced effects. Controller gains are designed compatible with different possible values of delays and packet dropouts. A novel augmented representation of the state-space equations of the system is derived to design observer gain and controller gains. The asymptotic stability of the system is guaranteed by designing the observer and controller based on the Lyapunov function through solving linear matrix inequalities (LMIs). Putting all the aforementioned points together has made the whole framework presented in this paper a comprehensive one. The effectiveness of the proposed approach is demonstrated by comparative simulation results.

The power generation from wind turbine are variable because of dependence on environmental conditions and it is important to extract maximum energy from wind. This paper proposes a new method to extract maximum energy from wind turbine systems. The artificial neural network (ANN) is used to estimate the wind speed based on the rotor speed and the output power. In addition to ANN, a predictive controller is used to maximize the efficiency of the boost converter. In predictive controller, duty cycle of boost converter is controlled to obtain the maximum power point based on the slope method. One of the most interesting advantages of this controller is simplicity of control and implementation that is leads to fast response and exact tracking. The method has been developed and analyzed by utilizing a turbine directly driven permanent-magnet synchronous generator (PMSG). The simulation results verify the performance of the proposed method. Results show that this method maximizes wind energy extraction with more accuracy and fastness.