scholarly journals A Reference-Model-Based Artificial Neural Network Approach for a Temperature Control System

Processes ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 50
Author(s):  
Song Xu ◽  
Seiji Hashimoto ◽  
YuQi Jiang ◽  
Katsutoshi Izaki ◽  
Takeshi Kihara ◽  
...  
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Digital Signal Processor ◽  
Reference Model ◽  
Learning Performance ◽  
Temperature Control System ◽  
Neural Network Approach ◽  
Model Based ◽  
Artificial Neural ◽  
Self Learning

Artificial neural networks (ANNs), which have excellent self-learning performance, have been applied to various applications, such as target detection and industrial control. In this paper, a reference-model-based ANN controller with integral-proportional-derivative (I-PD) compensation has been proposed for temperature control systems. To improve the ANN self-learning efficiency, a reference model is introduced for providing the teaching signal for the ANN. System simulations were carried out in the MATLAB/SIMULINK environment and experiments were carried out on a digital-signal-processor (DSP)-based experimental platform. The simulation and experimental results were compared with those for a conventional I-PD control system. The effectiveness of the proposed method was verified.

scholarly journals Recurrent Neural Network-Based Temperature Control System Weight Pruning Based on Nonlinear Reconstruction Error

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 44
Author(s):  
Yuan Liu ◽  
Takahiro Kawaguchi ◽  
Song Xu ◽  
Seiji Hashimoto
Keyword(s):  
Control System ◽  
Real Time ◽  
Temperature Control ◽  
Reference Model ◽  
Reconstruction Error ◽  
Control Model ◽  
Temperature Control System ◽  
Pruning Method ◽  
Parameterized Model ◽  
Weight Pruning

Recurrent Neural Networks (RNNs) have been widely applied in various fields. However, in real-world application, because most devices like mobile phones are limited to the storage capacity when processing real-time information, an over-parameterized model always slows down the system speed and is not suitable to be employed. In our proposed temperature control system, the RNN-based control model processes the real-time temperature signals. It is necessary to compress the trained model with acceptable loss of control performance for further implementation in the actual controller when the system resource is limited. Inspired by the layer-wise neuron pruning method, in this paper, we apply the nonlinear reconstruction error (NRE) guided layer-wise weight pruning method on the RNN-based temperature control system. The control system is established based on MATLAB/Simulink. In order to compress the model size to save the memory capacity of temperature controller devices, we first prove the validity of the proposed reference-model (ref-model) guided RNN model for real-time online data processing on an actual temperature object; relative experiments are implemented based on a digital signal processor. On this basis, we then verified the NRE guided layer-wise weight pruning method on the well-trained temperature control model. Compared with the classical pruning method, experiment results indicate that the pruned control model based on NRE guided layer-wise weight pruning can effectively achieve the high accuracy at targeted sparsity of the network.

Temperature Control System for Transformer Three-Phase 50 Hz 2500 kVA

2017 ◽  
Vol 3 (2) ◽  
pp. 88
Author(s):  
Suci Rahmatia ◽  
Marsah Zaysi Makhudzia
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Heat Loss ◽  
Temperature Control ◽  
Electrical Energy ◽  
Temperature Control System ◽  
Iron Core ◽  
Electrical Device ◽  
Optimal Control System ◽  
Three Phase

<p><em>Abstrak <strong>- </strong></em><strong>Transformator adalah peralatan listrik yang sangat vital dalam proses pembangkitan maupun transmisi energi listrik karena transformator dapat menaikkan atau menurunkan tegangan. Pada proses menaikkan dan menurunkan tegangan biasanya sering timbul panas akibat rugi – rugi tembaga pada inti besi dan kumparannya sehingga pada kondisi overload akan menimbulkan pemanasan yang berlebih dan dapat mempengaruhi kinerja transformator. Oleh karena itu dibuat sistem kontrol temperatur pada transformer yang dapat mengontrol temperatur di dalam transformator saat bekerja pada kondisi overload, sehigga transformatornya tidak terbakar. Dial thermometer digunakan sebagai alat yang mengontrol temperatur transformator pada sistem kontrol temperatur. Agar mendapatkan sistem kontrol yang optimal, maka setting temperatur pada dial thermometer di sesuaikan dengan temperatur maksimal tranformator dapat bekerja. Sehingga pada saat temperatur tertentu dial thermometer dapat memberikan sinyal untuk membunyikan alarm dan mengaktifkan kontrol kipas sehingga kipas dapat bekerja menurunkan temperatur transformator.<em></em></strong></p><p><strong><em> </em></strong></p><p><strong><em>Kata kunci - </em></strong><em>transformator, rugi – rugi tembaga, temperatur, sistem kontrol, dial thermometer<strong>.</strong></em></p><p><strong><em> </em></strong></p><p><em>Abstract <strong>- </strong></em><strong>A transformer is an electrical device that is vital in the generation and transmission of electrical energy because the transformer can raise (stepping up) or lower (stepping down) the voltage. In the process of raising and lowering the voltage is usually often caused heat loss of copper in iron core and coil so that the overload condition will cause excessive warming and can affect the performance of the transformer. Therefore, a temperature control system on the transformer can control the temperature inside the transformer while working under overload conditions, so the transformer is not burned. Dial thermometer is used as a device that controls the temperature of the transformer in the temperature control system. In order to obtain an optimal control system, the temperature setting on the dial thermometer adjusted to the maximum transformer temperature can work. So that when a certain temperature dial thermometer can provide a signal to sound the alarm and activate the fan control so that the fan can work down the transformer temperature.</strong></p><p><strong> </strong></p><p><strong><em>Keywords -  </em></strong><em>transformator, loss of copper, themperature, control system, dial thermometer<strong></strong></em></p>

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