Spiking PID Control Applied in the Van de Vusse Reaction

(1) Carlos Antonio Márquez-Vera Mail (Universidad Veracruzana, Mexico)
(2) Zaineb Yakoub Mail (National Engineering School of Gabès, Tunisia)
(3) * Marco Antonio Márquez Vera Mail (Polytechnic University of Pachuca, Mexico)
(4) Alfian Ma'arif Mail (Universitas Ahmad Dahlan, Indonesia)
*corresponding author


Artificial neural networks (ANN) can approximate signals and give interesting results in pattern recognition; some works use neural networks for control applications. However, biological neurons do not generate similar signals to the obtained by ANN.  The spiking neurons are an interesting topic since they simulate the real behavior depicted by biological neurons. This paper employed a spiking neuron to compute a PID control, which is further applied to the Van de Vusse reaction. This reaction, as the inverse pendulum, is a benchmark used to work with systems that has inverse response producing the output to undershoot. One problem is how to code information that the neuron can interpret and decode the peak generated by the neuron to interpret the neuron's behavior. In this work, a spiking neuron is used to compute a PID control by coding in time the peaks generated by the neuron. The neuron has as synaptic weights the PID gains, and the peak observed in the axon is the coded control signal. The neuron adaptation tries to obtain the necessary weights to generate the peak instant necessary to control the chemical reaction. The simulation results show the possibility of using this kind of neuron for control issues and the possibility of using a spiking neural network to overcome the undershoot obtained due to the inverse response of the chemical reaction.


Spiking Neuron; PID Control; Chemical Reaction; Van de Vusse Reaction; Artificial Neural Networks




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International Journal of Robotics and Control Systems
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