Refine
H-BRS Bibliography
- yes (25)
Departments, institutes and facilities
- Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) (25) (remove)
Document Type
- Conference Object (21)
- Article (3)
- Preprint (1)
Language
- English (25)
Keywords
- Volterra-Wiener series (2)
- discrete optimisation (2)
- dispatching problem (2)
- efficiency (2)
- injection moulding (2)
- massively parallel calculations (2)
- ANN (1)
- ANN controller (1)
- Competition (1)
- Control (1)
- DC electric drives (1)
- Identification and control methods (1)
- Manipulator (1)
- Modelica (1)
- Modeling (1)
- Motion Control Systems (1)
- Multidimensional Z-transforms (1)
- Nonlinear sampled-data system (1)
- PID (1)
- PWM converters (1)
- Pulse-width modulation (1)
- artificial neural network (1)
- artificial neural networks (1)
- auxiliary power supply (1)
- battery (1)
- battery charging (1)
- biological object (1)
- boost converter (1)
- brushless motors (1)
- brute force algorithm (1)
- brute force methods (1)
- calculations modeling (1)
- calculations modelling (1)
- cancer cells detection (1)
- control (1)
- coordinated charging (1)
- dc electric drive (1)
- digital control system (1)
- drone (1)
- dynamic experiment (1)
- dynamic programming (1)
- error analysis (1)
- factor load (1)
- graphics processing units (1)
- headways optimisation (1)
- high accuracy drives (1)
- in-home charging (1)
- information parameter (1)
- maximum power point tracker (1)
- melting heater (1)
- motor drive (1)
- multidimensional Z-transforms (1)
- nonlinear sampled-data systems (1)
- optimisation of control system (1)
- optimization of telecommunications systems (1)
- parallel computing (1)
- partial-shaded photovoltaic (1)
- permanent magnet motors (1)
- persistent surveillance (1)
- photovoltaic (1)
- photovoltaic system (1)
- plastic industry (1)
- plastic manufacturing (1)
- plug-in electric vehicle (1)
- pulse width modulation (1)
- simulation (1)
- state of charge (1)
- switching-mode power supply (1)
- temperature control (1)
- temperature controller (1)
- transport systems (1)
- velocity stabilising systems (1)
- wearable photovoltaic system (1)
- wireless communication (1)
- wireless networks’ topology (1)
- youBot (1)
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.
Wireless sensor networks are widely used in a variety of fields including industrial environments. In case of a clustered network the location of cluster head affects the reliability of the network operation. Finding of the optimum location of the cluster head, therefore, is critical for the design of a network. This paper discusses the optimisation approach, based on the brute force algorithm, in the context of topology optimisation of a cluster structure centralised wireless sensor network. Two examples are given to verify the approach that demonstrate the implementation of the brute force algorithm to find an optimum location of the cluster head.
This paper proposes a new artificial neural network-based maximum power point tracker for photovoltaic application. This tracker significantly improves efficiency of the photovoltaic system with series-connection of photovoltaic modules in non-uniform irradiance on photovoltaic array surfaces. The artificial neural network uses irradiance and temperature sensors to generate the maximum power point reference voltage and employ a classical perturb and observe searching algorithm. The structure of the artificial neural network was obtained by numerical modelling using Matlab/Simulink. The artificial neural network was trained using Bayesian regularisation back-propagation algorithms and demonstrated a good prediction of the maximum power point. Relative number of Vmpp prediction errors in range of ±0.2V is 0.05% based on validation data.
The paper presents a new control strategy of management of transport companies operating in completive transport environment. It is aimed to optimise the headway of transport companies to provide the balance between costs and benefits of operation under competition. The model of transport system build using AnyLogic comprises agent-based and discrete-event techniques. The model combined two transport companies was investigated under condition of the competition between them. It was demonstrated that the control strategy can ensure the balance of interests of transport companies trying to find compromise between cost of operation and quality of service.
Synthesis of serving policies for objects flow in the system with refillable storage component
(2017)