Design of a Predictive RBF Compensation Fuzzy PID Controller for 3D Laser Scanning System

Zhao, Minghui; Xu, Xiaobin; Yang, Hao; Pan, Zhijie

doi:10.3390/app10134662

Cited by 10 publications

(10 citation statements)

References 37 publications

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“…The intelligent optimization algorithm gives new vitality to the PID algorithm. The PID parameters are adjusted online through an intelligent algorithm to make the PID algorithm more adaptable [27][28]. Many intelligent algorithms have been applied in the closedloop control of the motor.…”

Section: Single Neuron Fuzzy Pid Control Strategy Based On Srmmentioning

confidence: 99%

Design of an Embedded Rapier Loom Controller and a Control Strategy Based on SRM

et al. 2022

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Rapier looms are currently important equipment in the weaving process. The control system of the loom determines the performance of the loom, to a large extent. To effectively reduce the production cost and energy consumption and to improve the start-up performance and production efficiency of rapier looms in industrial production, this paper develops an integrated rapier loom control system based on the direct drive of a switched reluctance motor (SRM) spindle and conducts field tests and applications. The contribution and innovation of this paper is to develop a complete set of low-cost control systems, propose an SRM single neuron fuzzy PID speed control strategy based on voltage chopping control and use it for the control of the main shaft drive technology of rapier looms. The integrated rapier loom control system based on the SRM spindle direct drive proposed in this paper reduces the production costs and energy consumption and improves the start-up performance and production efficiency of the rapier loom. This text carries on the systematic plan design to the control system from the hardware system and the software system. First, according to actual needs, starting from the aspect of reducing control costs and combined with the characteristics of embedded systems, such as tailorability, low cost, and strong scalability, this paper proposes a control system hardware structure based on CAN bus communication and a fully embedded STM32. The control system is divided into multiple control modules, such as the main control module, the spindle drive module, and the power transmission coil module. The system conducts a distributed control to the loom through the CAN bus and is equipped with various communication interfaces, such as Ethernet and RS485. Second, combining the characteristics of the SRM with a simple structure, a large starting torque and the operation mode of the loom, the basic control mode of SRM voltage chopping control is determined. To improve the efficiency and start-up performance of the speed control system, the SRM single neuron PID control algorithm is proposed, and a single neuron is used to improve the PID parameters. On this basis, fuzzy control is introduced to adjust the output gain of a single neuron PID control online to improve the system performance and reduce system energy consumption. Finally, the entire set of rapier loom control systems was verified, tested and debugged on site. The results show that each functional circuit works normally, and that the designed control system can meet the speed response demand of the loom at 850 rpm and reduce the production cost and energy consumption. The comparison experiment between the single neuron fuzzy PID algorithm of the motor and the traditional PID control algorithm in the actual loom production process proves that the proposed control algorithm has a better dynamic response performance. The proposed control algorithm effectively improves the starting performance and production efficiency of rapier looms and meets the actual needs of...

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Section: Single Neuron Fuzzy Pid Control Strategy Based On Srmmentioning

confidence: 99%

Design of an Embedded Rapier Loom Controller and a Control Strategy Based on SRM

et al. 2022

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“…However, this technique has been rarely used for accuracy improvement of PID. For example, in [26], a PID is optimized by the use of FLSs and a predictive controller is used to improve the performance. In [27], the MPC is developed for control of eco-driving and it is compared with PID.…”

Section: Literature Reviewmentioning

confidence: 99%

A New General Type-2 Fuzzy Predictive Scheme for PID Tuning

et al. 2021

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The proportional-integral-derivative controller is widely used in various industrial applications. But, in many noisy problems the strong methods are needed to optimize the proportional-integral-derivative parameters. In this paper, a novel method is introduced for adjusting the proportional-integral-derivative parameters through the model predictive control and generalized type-2 fuzzy-logic systems. The rules of suggested fuzzy system are online adjusted and the parameters of proportional-integral-derivative are tuned based on the fuzzy model such that a cost function to be minimized. The designed controller is applied on continuous stirred tank reactor and the performance is compared with other traditional approaches. The main advantages are that the accuracy is improved by online modeling and optimization and a predictive scheme is added to the conventional proportional-integral-derivative controller.

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“…. (40) e transfer function of the inverted pendulum system is discretized by z transformation. e discretized object after z transformation is…”

Section: Simulation Studiesmentioning

confidence: 99%

“…Tuning PID parameters are used to optimize system performance according to actual conditions. As PID parameter tuning technology becomes more and more mature, some interested scholars use PID as a controller to study system stability and tracking issues [39][40][41][42]. In order to adapt PID to more situations, some scholars have launched the control research of fuzzy PID [43,44] and fractional PID [45,46].…”

Section: Introductionmentioning

confidence: 99%

Neural Network Supervision Control Strategy for Inverted Pendulum Tracking Control

Gao

et al. 2021

Discrete Dynamics in Nature and Society

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This paper presents several control methods and realizes the stable tracking for the inverted pendulum system. Based on the advantages of RBF and traditional PID, a novel PID controller based on the RBF neural network supervision control method (PID-RBF) is proposed. This method realizes the adaptive adjustment of the stable tracking signal of the system. Furthermore, an improved PID controller based on RBF neural network supervision control strategy (IPID-RBF) is presented. This control strategy adopts the supervision control method of feed-forward and feedback. The response speed of the system is further improved, and the overshoot of the tracking signal is further reduced. The tracking control simulation of the inverted pendulum system under three different signals is given to illustrate the effectiveness of the proposed method.

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Design of a Predictive RBF Compensation Fuzzy PID Controller for 3D Laser Scanning System

Cited by 10 publications

References 37 publications

Design of an Embedded Rapier Loom Controller and a Control Strategy Based on SRM

Design of an Embedded Rapier Loom Controller and a Control Strategy Based on SRM

A New General Type-2 Fuzzy Predictive Scheme for PID Tuning

Neural Network Supervision Control Strategy for Inverted Pendulum Tracking Control

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