This paper proposes a new artificial neural network-based position controller for a full-electric injection moulding machine. Such a controller improves the dynamic characteristics of the positioning for hot runners, pin valve and the injection motors for varying moulding parameters. Practical experimental data and Matlab's System Identification Toolbox have been used to identify the transfer functions of the motors. The structure of the artificial neural network, which used positioning error and speed of error, was obtained by numerical modelling in Matlab/Simulink. The artificial neural network was trained using back-propagation algorithms to provide control of the motor current thus ensuring the required position and velocity. The efficiency of the proposed ANN-based controller has been estimated and verified in Simulink using real velocity data and the position of the injection moulding machine and pin valve motors.
This paper describes a model predictive control (MPC) algorithm for the interleaved dc-dc bidirectional converter with coupled inductors for Photovoltaic (PV) applications. An averaged discrete state space model of the converter was developed. The main control objective was to regulate the output voltage to its reference value despite changes in the load and battery voltage. The receding horizon strategy with extrapolation was used to reduce calculation complexity of the prediction. We propose some enhancements in the control signal duty cycle enumeration process, which is a part of the objective function minimization. The results of simulation experiments demonstrated good performance of the proposed control algorithm.
This paper provides a performance analysis of a wearable photovoltaic system mounted on the outer surface of a backpack. Three types of photovoltaic materials, commonly used for electricity generation, have been investigated under various conditions including sun irradiance, angle-of-incidence and sun inclination. The results of the investigation have shown that the system equipped with the rigid mono-Si panels performs 3.5 to 4.9 times better than the system equipped with a-Si flexible PV modules. The average power generated by the wearable photovoltaic system is about 30% of the maximum installed power for any photovoltaic type. This paper presents the test data resulting from the evaluation of the daily energy production of a wearable photovoltaic power supply.
1 December 2020 in IEEE Journal of Emerging and Selected Topics in Power Electronics
This article presents a non-conventional approach to a multi-coil wireless power transfer system based on a Z-source network. The novelty of the approach lies in the use of a Z-source as a voltage source for energy transmission through the wireless power transfer coils. The main advantage is in a reduced number of semiconductors. This paper provides the design approach, simulation and experimental study. Feasibility and possible application fields are presented in the conclusions.
This paper proposes an approach to an ANN-based temperature controller design for a plastic injection moulding system. This design approach is applied to the development of a controller based on a combination of a classical ANN and integrator. The controller provides a fast temperature response and zero steady-state error for three typical heaters (bar, nozzle, and cartridge) for a plastic moulding system. The simulation results in Matlab Simulink software and in comparison to an industrial PID regulator have shown the advantages of the controller, such as significantly less overshoot and faster transient (compared to PID with autotuning) for all examined heaters. In order to verify the proposed approach, the designed ANN controller was implemented and tested using an experimental setup based on an STM32 board.