Fuzzy-PID controller for motion control of CFETR multi-functional maintenance platform

Li, Dongyi; Lü, Kun; Cheng, Yong; Zhao, Wenlong; Yang, Song; Zhang, Yu; Li, Junwei; Wu, Huapeng

doi:10.1016/j.net.2021.01.025

Cited by 10 publications

(5 citation statements)

References 10 publications

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“…Combing eqs. (5)(6)(7)(8), the general state space model of asymmetric hydraulic cylinder is obtained.…”

Section: Du Of Bcr Nonlinear Model Establishmentmentioning

confidence: 99%

Hybrid Nonlinear Model Predictive Motion Control of a Heavy-duty Bionic Caterpillar-like Robot

Li,

Lu,

Cheng

et al. 2024

J Bionic Eng

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This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot (BCR) for the maintenance of the China Fusion Engineering Test Reactor (CFETR). Initially, a comprehensive nonlinear mathematical model for the BCR system is formulated using a physics-based approach. The nonlinear components of the model are compensated through nonlinear feedback linearization. Subsequently, a fuzzy-based regulator is employed to enhance the receding horizon optimization process for achieving optimal results. A Deep Neural Network (DNN) is trained to address disturbances. Consequently, a novel hybrid controller incorporating Nonlinear Model Predictive Control (NMPC), the Fuzzy Regulator (FR), and Deep Neural Network Feedforward (DNNF), named NMPC-FRDNNF is developed. Finally, the efficacy of the control system is validated through simulations and experiments. The results indicate that the Root Mean Square Error (RMSE) of the controller with FR and DNNF decreases by 33.2 and 48.9%, respectively, compared to the controller without these enhancements. This research provides a theoretical foundation and practical insights for ensuring the future highly stable, safe, and efficient maintenance of blankets.

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“…Combing eqs. (5)(6)(7)(8), the general state space model of asymmetric hydraulic cylinder is obtained.…”

Section: Du Of Bcr Nonlinear Model Establishmentmentioning

confidence: 99%

Hybrid Nonlinear Model Predictive Motion Control of a Heavy-duty Bionic Caterpillar-like Robot

Li,

Lu,

Cheng

et al. 2024

J Bionic Eng

Self Cite

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“…Select binary numbers “000” to “111” to represent decimal numbers 0, 1, 2, 3, 4, 5, 6, and 7, where these 8 numbers represent eight rules in the fuzzy subset: NB (negative major), NM (negative middle), NS (negative minor), NZ (negative zero), PZ (positive zero), PS (positive minor), PM (positive middle), PB (positive major) [ 33 ]. Therefore, there are 441 genes on one chromosome, including Kp.…”

Section: Design Of Temperature Control System Based On Ga-fuzzy Optim...mentioning

confidence: 99%

Design of vacuum annealing furnace temperature control system based on GA-Fuzzy-PID algorithm

Meng,

Gao,

Ruan

et al. 2023

PLoS ONE

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As is well known, the metal annealing process has the characteristics of heat concentration and rapid heating. Traditional vacuum annealing furnaces use PID control method, which has problems such as high temperature fluctuation, large overshoot, and long response time during the heating and heating process. Based on this situation, some domestic scholars have adopted fuzzy PID control algorithm in the temperature control of vacuum annealing furnaces. Due to the fact that fuzzy rules are formulated through a large amount of on-site temperature data and experience summary, there is a certain degree of subjectivity, which cannot ensure that each rule is optimal. In response to this drawback, the author combined the technical parameters of vacuum annealing furnace equipment, The fuzzy PID temperature control of the vacuum annealing furnace is optimized using genetic algorithm. Through simulation and comparative analysis, it is concluded that the design of the fuzzy PID vacuum annealing furnace temperature control system based on GA optimization is superior to fuzzy PID and traditional PID control in terms of temperature accuracy, rise time, and overshoot control. Finally, it was verified through offline experiments that the fuzzy PID temperature control system based on GA optimization meets the annealing temperature requirements of metal workpieces and can be applied to the temperature control system of vacuum annealing furnaces.

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“…By the substitution of Eqs. ( 23)-( 24), ( 27)- (28), and (30)-(32) into Eq. (33), the above equation is simplified as follows optimization type:…”

Section: Cost Function Of Mpc-ccc Algorithm and Its Optimization Typementioning

confidence: 99%

“…With linearizing flow with load equation near the balance point of the valve spool [28], the following equation is obtained: where…”

Section: Brmr Modelingmentioning

confidence: 99%

Synchronization control of blanket remote maintenance robot based on MPC-CCC algorithm

Lü

Cheng

et al. 2023

Robotica

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This paper studies the synchronization control of the blanket remote maintenance robot (BRMR) of the China fusion engineering test reactor (CFETR). First, the general state space mathematical model of BRMR was established by using a physical-based method. Second, based on the receding horizon optimization of model predictive control (MPC) and cross-coupling error reduction in cross-coupling control (CCC), the innovative MPC-CCC controller was proposed to realize the single-system and multisystem error convergence and high accuracy transportation of blanket through the high accuracy synchronization control of BRMR. Third, to verify the control effectiveness of the MPC-CCC controller, two types of simulations and experiments were implied compared with the original proportional-integral (PI) controller in Mover. Results showed that simulation and experiments were highly consistent. It is found that the use of an MPC-CCC controller can result in up to a 70% reduction in displacement error and up to a 59% reduction in synchronization error compared to the PI controller. And the accuracy of the MPC-CCC controller satisfies the real requirement of the maintenance process of the blanket. This work provides the theoretical basis and practical experience for the highly stable, safe, and efficient maintenance of blankets in the future.

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Fuzzy-PID controller for motion control of CFETR multi-functional maintenance platform

Cited by 10 publications

References 10 publications

Hybrid Nonlinear Model Predictive Motion Control of a Heavy-duty Bionic Caterpillar-like Robot

Hybrid Nonlinear Model Predictive Motion Control of a Heavy-duty Bionic Caterpillar-like Robot

Design of vacuum annealing furnace temperature control system based on GA-Fuzzy-PID algorithm

Synchronization control of blanket remote maintenance robot based on MPC-CCC algorithm

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