The application of PID control in motion control of the spherical amphibious robot

Wang, Zhe; Guo, Shuxiang; Shi, Liwei; Pan, Shaowu; He, Yanlin

doi:10.1109/icma.2014.6885992

Cited by 10 publications

(7 citation statements)

References 17 publications

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“…The performance of the proposed neural PID control with the tuning values of K p , K i and K d can be verified by force control experiments. According to the studies by Huailin 32 and Wang et al, 33 the stability analysis of neural PID control is given in Appendix 1.…”

Section: Force Control Systemmentioning

confidence: 99%

Development of a real-time force-controlled compliant polishing tool system with online tuning neural proportional–integral–derivative controller

Zhou

Zhang

Cheng

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article presents a real-time force-controlled pneumatic compliant polishing tool with self-supplied abrasives making the abrasives added to the contact area between the polishing pad and workpiece, which can lead to good polishing performance. And a force–position decoupling pneumatic servo system for polishing force control is presented to solve the problem of force–position coupling in the traditional polishing process. However, it is difficult to realize satisfactory control performance due to the problems of time variance, compliance, hysteresis and nonlinearity in pneumatic servo system. This article proposes an online tuning neural proportional–integral–derivative controller to improve force control performance. The real-time polishing force control results of pneumatic servo control system are investigated by adopting proposed neural proportional–integral–derivative control strategies with data acquisition card and RTW toolbox in MATLAB/Simulink. The real-time experimental results of polishing force control indicate that the excellent control performance can be achieved by the proposed neural proportional–integral–derivative controller no matter the reference force is constant or varied. Compared with those by traditional proportional–integral–derivative controller, the duration for stabilizing the polishing force is shorter and the error between the output force and the reference is smaller by the proposed neural proportional–integral–derivative controller.

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Section: Force Control Systemmentioning

confidence: 99%

Development of a real-time force-controlled compliant polishing tool system with online tuning neural proportional–integral–derivative controller

Zhou

Zhang

Cheng

et al. 2015

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…In order to eliminate current interference, many outstanding control methods have been adapted for ROVs' control, such as PID control [6,7], adaptive control [8][9][10], back-step control [11,12], and sliding mode control (SMC) [13][14][15][16]. In addition, fuzzy logic control [13,17,18] and neural network control [7,19,20] are often used in combination with other control methods. Among the mentioned control methods, SMC is increasingly used for the trajectory tracking control of ROVs under complex sea conditions because of its robustness to parameter changes and good suppression of external disturbances.…”

Section: Introductionmentioning

confidence: 99%

Double-Loop Sliding Mode Controller with An Ocean Current Observer for the Trajectory Tracking of ROV

Wang

Sun³

et al. 2021

JMSE

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To solve the trajectory tracking problem of insufficient response and the large tracking error of remotely operated vehicles (ROVs) under the interference of large ocean currents, this paper proposes a double-loop sliding mode controller with an ocean current observer. The designed controller consisted of an outer-loop controller (the position controller) and an inner-loop controller (the velocity controller): the outer controller was designed by the position error, and a reference velocity was created for the inner loop to achieve accurate positioning and attitude tracking. The reference control input was treated as a new target to design the inner-loop controller, enabling the ROV to achieve accurate reference velocity tracking. Based on the theoretical idea of active disturbance rejection control, a kinematic equation-based ocean current observer was designed to estimate and compensate for large unknown currents to ensure accurate trajectory tracking performance under large currents. The simulation results proved that the double-loop sliding-mode control scheme with an ocean current observer always showed good tracking performance, demonstrating the excellent control performance and high robustness of the scheme. Compared with the high-complexity control schemes such as neural network-based PID control or fuzzy sliding mode control, it effectively improves the robustness to ocean current disturbances without increasing the computational effort excessively, and is more practical in ROV systems with limited computational power.

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“…The motor-driven structure is light and can realize rapid and simple deployment, but it cannot provide a large load. 26,27 Research on the control system of the underwater Unmanned Aerial Vehicle (UAV) using the motor drive shows that the motor drive can achieve good tracking of the target trajectory. 27,28 The drive and control are among the most important enabling technologies for CPMS because the piston is driven by a motor to control the change of pressure.…”

Section: Introductionmentioning

confidence: 99%

“…26,27 Research on the control system of the underwater Unmanned Aerial Vehicle (UAV) using the motor drive shows that the motor drive can achieve good tracking of the target trajectory. 27,28 The drive and control are among the most important enabling technologies for CPMS because the piston is driven by a motor to control the change of pressure. [29][30][31] At the same time, the pressure compensator not only compensates the change of volume and pressure in real time, but also affects the dynamic adjustment process of the piston.…”

Section: Introductionmentioning

confidence: 99%

Simulation and verification of measurement system for deep-sea pressure and its small fluctuation pressure

Wang

Liu

et al. 2020

Measurement and Control

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Combined pressure measuring system (CPMS), which is mainly used for measuring deep-sea larger pressure and its small fluctuation pressure, is studied. First, the working principle of the CPMS is introduced. Second, the mathematical model of the CPMS is established. Third, the influence of the cross-sectional area of the piston, the equivalent mass of the piston, the diving speed, the cross-sectional diameter of the compensator piston, the air content of the liquid medium, and the small fluctuation pressure on the measurement performance of the CPMS is analyzed using the simulation model. Then, the design principle of the system is summarized. Finally, the test platform is built. The results show that the dynamic pressure is not more than 0.025 bar when the pressure change speed is 0.2 bar/s, the pressure is 2.8 × 10−3 bar under 20 bar, thereby verifying the validity and accuracy of the measurement method and providing theoretical basis and reference for the design and optimization of the measurement system.

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The application of PID control in motion control of the spherical amphibious robot

Cited by 10 publications

References 17 publications

Development of a real-time force-controlled compliant polishing tool system with online tuning neural proportional–integral–derivative controller

Development of a real-time force-controlled compliant polishing tool system with online tuning neural proportional–integral–derivative controller

Double-Loop Sliding Mode Controller with An Ocean Current Observer for the Trajectory Tracking of ROV

Simulation and verification of measurement system for deep-sea pressure and its small fluctuation pressure

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