An Improved Single Neuron Adaptive PID Controller System Based on Additional Error of an Inversed-Control Signal

An adaptive PID controller based on single neuron is proposed. The properties, control algorithm, parameters tuning, the control law and the application condition of the controller are studied in the paper. To satisfy the properties of the requirements of the control system in an electromotor group, such as a broad dynamic changing range, a fast response, a little overshoot and time-variable parameter, a new-type self-optimizing PID controller based on artificial neural networks is proposed and studied. It is verified that the controller has few adjustable parameters and excellent robust performance. The results of simulation and experiment prove that the controller is superior to the traditional PID controller.

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Design of quad-rotor PID controller based on improved single neuron

2018 Chinese Control And Decision Conference (CCDC) ◽

10.1109/ccdc.2018.8407198 ◽

2018 ◽

Author(s):

Lu Yanjun ◽

Li Chenjie ◽

Zhang Xiaodong

Keyword(s):

Pid Controller ◽

Single Neuron

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BLDC Motor Control System Based on Quadratic Single Neuron Adaptive PID Algorithm

International Journal of Advanced Pervasive and Ubiquitous Computing ◽

10.4018/ijapuc.2014010102 ◽

2014 ◽

Vol 6 (1) ◽

pp. 12-25

Author(s):

Xiaoyuan Wang ◽

Tao Fu ◽

Xiaoguang Wang

Keyword(s):

Pid Controller ◽

Single Neuron ◽

High Efficiency ◽

Control Method ◽

Current Control ◽

Operating Conditions ◽

Regulation System ◽

Bldc Motor ◽

Motor Speed ◽

Pid Algorithm

Brushless DC (BLDC) motors are widely used for many industrial applications because of their high efficiency, high torque and low volume. In view of the problem that the current control method of speed regulation system of BLDC motor has poor control effect caused by fixed parameters of PID controller, an adaptive PID algorithm with quadratic single neuron (QSN) was designed. Quadratic performance index was introduced in adjustment of weight coefficients; expected optimization effect was gotten by calculating control law. QSN adaptive PID controller can change its parameters online when operating conditions are changed, it can also change its control characteristic automatically. Matlab simulations and experiment results showed that the proposed approach has less overshoot, faster response, stronger ability of anti-disturbance, the results also showed more effectiveness and efficiency than the conventional PID model in motor speed control.

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Optimisation of Energy Use in Bioethanol Production Using a Control Algorithm

Processes ◽

10.3390/pr9020282 ◽

2021 ◽

Vol 9 (2) ◽

pp. 282

Author(s):

Jarosław Knaga ◽

Stanisław Lis ◽

Sławomir Kurpaska ◽

Piotr Łyszczarz ◽

Marcin Tomasik

Keyword(s):

Energy Consumption ◽

Pid Controller ◽

Control Algorithm ◽

Control Signal ◽

Control Algorithms ◽

Signal Quality ◽

Control Signals ◽

And Control ◽

Rectification Process

In this work, the possibility of limiting energy consumption in the manufacturing process of bioethanol to obtain biofuel was analysed. For this purpose, a control algorithm has been optimised while retaining the good quality of the control signals. New in this study is the correlation of the control algorithm not only with the signal’s quality, but also with the energy consumption in such an energy-intensive process as rectification. The rectification process in a periodic production system has been researched. The process was modelled on a test station with the distillation mixture capacity of 25 dm3. For the optimization, the following control algorithms have been applied: relay, PID and PID after modification to I-PD. The simulation was carried out on a transfer function model of the plant that has been verified on a real object, a rectification column. The simulations of energy consumption and control signal’s quality have been carried out in the Matlab®-Simulink environment after implementing the model of the research subject and control algorithms. In the simulation process, an interference signal with an amplitude of 3% and frequency of 2 mHz was used. The executed analyses of the control signal quality and the influence of the control algorithm on the energy consumption has shown some essential mutual relationships. The lowest energy consumption in the rectification process can be achieved using the I-PD controller—however, the signal quality deteriorates. The energy savings are slightly lower while using the PID controller, but the control signal quality improves significantly. From a practical point of view, in the considered problem the best control solution is the classic PID controller—the obtained energy effect was only slightly lower while retaining the good quality of the control signals.

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