Barrier Lyapunov functions-based dynamic surface control with tracking error constraints for ammunition manipulator electro-hydraulic system

Nie, Songlin; Qian, Linfang; Chen, Longmiao; Tian, Lingfei; Zou, Quan

doi:10.1016/j.dt.2020.04.010

Cited by 17 publications

(5 citation statements)

References 26 publications

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“…In the part of the information collection, the temperature, position, pressure and other information are obtained through sensors, and then the collected information is transmitted to the part of the information processing. Usually, PLC (Programmable Logic Controller) [8] is used in this part, and the PLC transmits the processed data to the actuator, and controls the action of the manipulator through the hydraulic system [9]. Its overall design scheme is shown in Figure 2.…”

Section: The Overall Design Of the Control System Of The Manipulatormentioning

confidence: 99%

“…For displacement deviation and displacement deviation change rate , the Gaussian membership function is selected, and the function expression is shown in equation ( 8): (8) c and δ are both parameters to determine the shape of the function In fuzzy control, the basic domain of input variables is the variation range of the input variables of the control system. The universes of displacement deviation , displacement deviation change rate , proportional coefficient , integral coefficient , and differential coefficient are respectively defined, as shown in equation ( 9): (9) To better fuzzy control the system, the quantization factor is usually used to convert the value in the basic domain into the coefficient in the fuzzy domain, assuming that the basic domain is , and the fuzzy domain is , the calculation of the quantization factor is shown in equation ( 10):…”

Section: Design Of Fuzzy Controller Of the Electronic Drive Control S...mentioning

confidence: 99%

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Design of Electronic Drive Control System of the Hydraulic Joints of the Manipulator

2022

IJOMAM

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To further improve the control system of the manipulator, the manipulator of the jumbo is taken as the research object. According to the working process of the jumbo and the structure of the manipulator, the electronic drive control system of the hydraulic joints of the jumbo manipulator is designed. Firstly, the overall scheme of the electronic drive control system of the hydraulic joints of the jumbo manipulator is designed, which includes three parts: information collection, information processing, and actuators. Secondly, through the selection of fuzzy subsets and membership functions, the determination of variable domains, quantization factors and proportional factors, and the establishment of fuzzy control rules, fuzzy Proportion Integration Differentiation (PID) controller is designed, and the overall design and software and hardware system of the electronic drive control system of the hydraulic joints of the jumbo manipulator are studied. Finally, the fuzzy controller is designed and simulated through Matrix Laboratory (MATLAB) software. The results show that the rising time of the fuzzy PID controller is about 0.3 seconds, while the rising time of the conventional PID control is about 1 second. Compared with the conventional PID control, the overshoot of the fuzzy PID controller is smaller and can be fast and stable. When disturbed by the 10,000N external load, the fuzzy PID controller responds faster. The maximum peak range is about 1.13, the adjustment time is about 3 seconds. However, the maximum peak range of the conventional PID controller is about 1. 15. The adjustment time is about 3.8 seconds, indicating that compared with the conventional PID controller, the fuzzy PID controller has good dynamic performance, stability, fast response speed, strong tamper-resistance ability and better control effect. The results are conducive to improving the working efficiency of the jumbo manipulator, and providing certain research experience for the research of automatic jumbo.

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Section: The Overall Design Of the Control System Of The Manipulatormentioning

confidence: 99%

Section: Design Of Fuzzy Controller Of the Electronic Drive Control S...mentioning

confidence: 99%

Design of Electronic Drive Control System of the Hydraulic Joints of the Manipulator

2022

IJOMAM

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“…Electro-hydraulic servo system (EHSS) has the advantages of high power density, fast response speed, and high control accuracy, which is widely used in aerospace, weapons and equipment, civil industry, and other fields, such as pitch system 1 , mechanical arm 2 , excavator 3 and so on. However, several factors affect the control accuracy of EHSS.…”

Section: Introductionmentioning

confidence: 99%

Research on the characteristics of electro-hydraulic position servo system of RBF neural network under fuzzy rules

Li,

2024

Sci Rep

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A radial basis function neural network PID controller under fuzzy rules (FUZZY-RBF-PID) was designed for the electro-hydraulic position servo system under the influence of uncertain factors such as load mutation, and load stiffness change. Firstly, the mathematical model of the system is established, and the frequency domain and time domain analysis of the system are carried out. Secondly, based on the analysis results, a radial basis function (RBF) neural network PID controller is designed, and fuzzy rules are innovatively used to adjust the learning rate of PID parameters in the RBF neural network learning algorithm in real time. Thirdly, the simulation results show that under the action of the FUZZY-RBF-PID controller, the unit step response of the system has high steady-state accuracy, fast response speed, and under the condition of large load stiffness, the system can recover to the steady-state value faster after being disturbed. At the same time, when the input signal is the sinusoidal signal of 10 HZ, the system under the action of the FUZZY-RBF-PID controller has no obvious phase lag phenomenon, and the tracking error is minimal. The proposed method can effectively improve the comprehensive performance of the electro-hydraulic position servo system under the influence of uncertain factors.

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“…Further research is conducted to enhance disturbance elimination performance around ARC (Na et al, 2020), where the disturbance is bounded and the bound should be known. However, most ARC algorithms are designed by means of the backstepping scheme, which brings about ''differential explosion'' (Nie et al, 2021). Although the dynamic surface control technique (Zhang and Shi, 2022) is introduced to avoid this issue, extra complexity of the filter cannot be ignored.…”

Section: Introductionmentioning

confidence: 99%

Practical adaptive robust tracking control of the dual-valve parallel electro-hydraulic servo system with reduced-order model

Hu,

Zhang,

Fang

et al. 2023

Transactions of the Institute of Measurement and Control

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To meet the increasing demand for trajectory tracking accuracy and high-efficiency requirements in modern mobile machinery, this paper proposes a practical adaptive robust control method based on the dual-valve parallel electro-hydraulic servo system. Existing tracking control strategies for such servo systems rely on a backstepping method and assume that full states are known, which is stringent in practice. To cope with the problem, we reduce the mathematical model order of the studied system using singular perturbation theory in this paper, and only the position feedback is required for the control implementation. Then, to achieve high accuracy tracking control, a direct adaptive robust control scheme combing with a dynamic flow allocation layer is adopted to synthesize the controller. With this method, parameter uncertainties and load disturbance are rejected, and valve characteristics are considered in the dynamic flow allocation layer to solve the flow redundancy problem, respectively. Convergence of the simplified system tracking results is proved theoretically. Extensive co-simulations and experimental tests are carried out to illustrate the effectiveness of the proposed strategy, both tracking precision and flow distribution can be achieved efficiently by simple parameter adjustments in the field.

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Barrier Lyapunov functions-based dynamic surface control with tracking error constraints for ammunition manipulator electro-hydraulic system

Cited by 17 publications

References 26 publications

Design of Electronic Drive Control System of the Hydraulic Joints of the Manipulator

Design of Electronic Drive Control System of the Hydraulic Joints of the Manipulator

Research on the characteristics of electro-hydraulic position servo system of RBF neural network under fuzzy rules

Practical adaptive robust tracking control of the dual-valve parallel electro-hydraulic servo system with reduced-order model

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