Synergetic Synthesis of Nonlinear Laws of Throttle Control of a Pneumatic Drive

被引:1
作者
Obukhova, Elena [1 ]
Veselov, Gennady E. [2 ]
Obukhov, Pavel [1 ]
Beskopylny, Alexey [3 ]
Stel'makh, Sergey A. [4 ]
Shcherban, Evgenii M. [4 ]
机构
[1] Don State Tech Univ, Fac Automat Mechatron & Control, Dept Automat Ind Proc, Gagarin 1, Rostov Na Donu 344003, Russia
[2] Southern Fed Univ, Inst Comp Technol & Informat Secur, Chekhov 2, Taganrog 347922, Russia
[3] Don State Tech Univ, Fac Roads & Transport Syst, Dept Transport Syst, Gagarin 1, Rostov Na Donu 344003, Russia
[4] Don State Tech Univ, Bases & Fdn, Dept Engn Geol, Gagarin 1, Rostov Na Donu 344003, Russia
来源
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 04期
关键词
synergistic synthesis; nonlinear law; automatic control; pneumatic system; throttle control; mathematical model; TRACKING CONTROL; ROBUST-CONTROL; NETWORK; SUBJECT; SYSTEMS; DESIGN;
D O I
10.3390/app12041797
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Currently, a significant trend in control in robotic systems is developing and improving linear and nonlinear control algorithms to improve the overall quality of production with high accuracy and adaptability. The present study considers a synergistic synthesis of throttle control of a pneumatic distributor valve and backpressure control for piston rod positioning. The article presents the synthesis of control laws for the position of a pneumatic cylinder piston using the method of analytical design of aggregated regulators (ADAR) of synergetic control theory (STC), which allows operation with nonlinear mathematical models, eliminating the loss of information about the object during linearization. A comparative calculation of the energy efficiency of backpressure control and throttle control methods was carried out, while the numerical value of the total airflow with throttle control is 0.0569 m(3) forward slash s and, with backpressure control, it is 0.0337 m(3) forward slash s. Using a P controller in a linear model gives a transient oscillatory process damped in 2-2.5 s. When using a PID controller, the process has an overshoot equal to 11.5%, while the synergistic controller allows you to smoothly move the drive stem to a given position without overshoot. The parametric uncertainty analysis of the considered mathematical model is carried out. The model's main parameters are identified, which change the actual functioning of the system under study. The inconsistency of applying classical control laws based on typical controllers to parametrically indeterminate mathematical models is shown.
引用
收藏
页数:23
相关论文
共 42 条
  • [1] Power Management for Connected EVs Using a Fuzzy Logic Controller and Artificial Neural Network
    Angundjaja, Clint Yoannes
    Wang, Yu
    Jiang, Wenying
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (01):
  • [2] Joint Waveform and Guidance Control Optimization by Statistical Linearisation for Target Rendezvous
    Benavoli, Alessio
    Balleri, Alessio
    Farina, Alfonso
    [J]. 2021 IEEE RADAR CONFERENCE (RADARCONF21): RADAR ON THE MOVE, 2021,
  • [3] Beskopylny Alexey, 2022, Robotics, Machinery and Engineering Technology for Precision Agriculture: Proceedings of XIV International Scientific Conference "INTERAGROMASH 2021". Smart Innovation, Systems and Technologies (247), P13, DOI 10.1007/978-981-16-3844-2_2
  • [4] Beskopylny Alexey, 2022, Robotics, Machinery and Engineering Technology for Precision Agriculture: Proceedings of XIV International Scientific Conference "INTERAGROMASH 2021". Smart Innovation, Systems and Technologies (247), P1, DOI 10.1007/978-981-16-3844-2_1
  • [5] Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
    Beskopylny, Alexey
    Lyapin, Alexandr
    Anysz, Hubert
    Meskhi, Besarion
    Veremeenko, Andrey
    Mozgovoy, Andrey
    [J]. MATERIALS, 2020, 13 (11)
  • [6] Boldareva K. I., 2021, 2021 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), P642, DOI 10.1109/ICIEAM51226.2021.9446292
  • [7] Design and Analysis of an Active Disturbance Rejection Robust Adaptive Control System for Electromechanical Actuator
    Chen, Qinan
    Chen, Hui
    Zhu, Deming
    Li, Linjie
    [J]. ACTUATORS, 2021, 10 (12)
  • [8] Fault-Tolerant Active Disturbance Rejection Control of Plant Protection of Unmanned Aerial Vehicles Based on a Spatio-Temporal RBF Neural Network
    Hua, Lianghao
    Zhang, Jianfeng
    Li, Dejie
    Xi, Xiaobo
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (09):
  • [9] Design of Position Control Method for Pump-Controlled Hydraulic Presses via Adaptive Integral Robust Control
    Huang, Zhipeng
    Xu, Yuepeng
    Ren, Wang
    Fu, Chengwei
    Cao, Ruikang
    Kong, Xiangdong
    Li, Wenfeng
    [J]. PROCESSES, 2022, 10 (01)
  • [10] Khinikadze Tengiz, 2022, XIV International Scientific Conference "INTERAGROMASH 2021": Precision Agriculture and Agricultural Machinery Industry. Lecture Notes in Networks and Systems (246), P192, DOI 10.1007/978-3-030-81619-3_21