Abstract
In a photovoltaic power plant (PVPP), the DC-AC converter (inverter) is one of the components most prone to faults. Even though they are key equipment in such installations, their fault detection techniques are not as much explored as PV module-related issues, for instance. In that sense, this paper is motivated to find novel tools for detection focused on the inverter, employing machine learning (ML) algorithms trained using a hybrid dataset. The hybrid dataset is composed of real and synthetic data for fault-free and faulty conditions. A dataset is built based on fault-free data from the PVPP and faulty data generated by a digital twin (DT). The combination DT and ML is employed using a Clarke/space vector representation of the inverter electrical variables, thus resulting in a novel feature engineering method to extract the most relevant features that can properly represent the operating condition of the PVPP. The solution that was developed can classify multiple operation conditions of the inverter with high accuracy.

Abstract
This paper describes the newly developed Vector Control Signal Processing (VCSP) blockset for use with Matlab(R) and Simulink(R). The originality of this blockset consists on the extension of Simulink for design, simulation and prototyping of signal processing algorithms in motion control systems. This blockset is the first know collection of Simulink blocks to bridge the gap between digital algorithm development and subsequent implementation in motion control systems. The VCSP blockset together with Real-Time Workshop uses the inherent visual programming techniques of Simulink and a number of pre-built blocks to reach the above goals. Due to its open and flexible nature this approach is also very useful as a tool for teaching. This paper is focused on modelling and simulation of motion control systems, in particular employing rotating AC machines and vector control methods. The basic of blockset functions and some examples of modelling techniques for simple drive and complex drive structures are presented, Simulations results are also presented and discussed.

Abstract

Abstract

Abstract
Sliding mode controllers are derived for the control of the average output voltage in DC/DC power converters. The controller design is carried out on the basis of well-known bilinear models of such circuits. A cascaded control structure is chosen for ease of control realization and to exploit the motion separation property of this power converter. The performance of the proposed sliding mode controllers is tested for the buck and boost converter type. The numerical simulations will demonstrate the efficiency of sliding mode techniques in this field as a powerful alternative to other existing methods. © 2003 IFAC.

Abstract
This paper describes a surveillance system for forest environments and protected natural areas. The surveillance system has a capacity for detecting fires and other ecological crimes. The system uses a digital camera that is controlled remotely by a system operator. Using the software the operator may choose to zoom a special spot or even take measures to strategically fight the fire right before it becomes uncontrollable. Since this system is operated in the middle of forests, aspects like effectiveness, robustness and reliability are crucial. In positioning the camera, the system uses a stepper motor for the vertical movement of the camera and a DC motor for the horizontal movement. The system also captures information about the temperature, humidity, wind speed and direction. All the processing is realized by a PIC16f877 microcontroller. © 2003 IEEE.