Precise and smooth contact force control for a hybrid mobile robot used in polishing

Xie, Fugui; Chong, Zenghui; Liu, Xin-Jun; Zhao, Huichan

doi:10.1016/j.rcim.2023.102573

Cited by 8 publications

(3 citation statements)

References 27 publications

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“…Then, a dynamic model of the polishing system was established, and a PID control algorithm was designed to realize the tracking of the actual torque by the torque sensor. In the literature [11], an integrated polishing contact force control method is proposed, which combines feedforward of the desired force and adaptive variable impedance control. The input step signal is smoothed by a nonlinear tracking differentiator to reduce overshoot.…”

Section: Introductionmentioning

confidence: 99%

“…According to Equation (11), we can know that the polishing force changes as the workpiece curvature changes, so the application of the polishing force is time-varying. Since the polishing force control system is a complex, nonlinear, time-varying system, accurate parameters of the system dynamics model cannot be obtained, and the traditional PID control algorithm makes it difficult to achieve precise control.…”

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confidence: 99%

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Adaptive Fuzzy Sliding Mode Control and Dynamic Modeling of Flap Wheel Polishing Force Control System

Hong,

Zhou,

2024

Applied Sciences

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Polishing force is one of the key process parameters in the polishing process of blisk blades, and its control accuracy will affect the surface quality and processing accuracy of the workpiece. The contact mechanism between the polishing surface and flap wheel was analyzed, and the calculation model of the polishing force and nonlinear dynamic model of the polishing force control system was established. Considering the influence of friction characteristics, parameter perturbation, and nonlinear dead zone on the control accuracy of the polishing force system, an adaptive fuzzy sliding mode controller (AFSMC) was designed. AFSMC uses a fuzzy system to adaptively approximate the nonlinear function terms in the sliding mode control law, adopts an exponential approach law in the switching control part of the sliding mode control (SMC), and designs the adaptive law for adjustable parameters in the fuzzy system based on the Lyapunov Theorem. Simulation and experimental results show that the designed AFSMC has a fast dynamic response, strong anti-interference ability, and high control accuracy, and it can reduce SMC high-frequency chatter. Polishing experiments show that compared with traditional PID, AFSMC can improve the form and position accuracy of the blade by 42% and reduce the surface roughness by 50%.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Adaptive Fuzzy Sliding Mode Control and Dynamic Modeling of Flap Wheel Polishing Force Control System

Hong,

Zhou,

2024

Applied Sciences

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“…Active force control is the use of designed control strategies to actively control force through the feedback of contact force information [32]. In the aspect of force control algorithms, the design of the force controller is the most important, and the common force control algorithms are impedance control [33,34] and hybrid position/force control [35,36].…”

Section: Introductionmentioning

confidence: 99%

Dual PID Adaptive Variable Impedance Constant Force Control for Grinding Robot

Wu,

Guo,

Sun

2023

Applied Sciences

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High-precision and low-overshoot force control are important to guarantee the material removal rate and surface quality of robot grinding. However, traditional force control methods are subjected to positional disturbance, stiffness disturbance, contact process nonlinearity, and force-position coupling, leading to difficulties in robot constant force control. Therefore, how to achieve smooth, stable, and high-precision constant force control is an urgent problem. To address this problem, a dual PID adaptive variable impedance control is established (DPAVIC). Firstly, PD control is used to compensate for the force error, and PID is used to update the damping parameters to compensate for the disturbance. Secondly, a nonlinear tracking differentiator is used to smooth the desired force and reduce the contact force overshoot. Then, the stability, convergence, and effectiveness of the force control algorithm are verified via theoretical analysis, simulations, and experiments. The force tracking error and overshoot of a conventional impedance controller (CIC), adaptive variable impedance control (AVIC), and DPAVIC are analyzed. Finally, the algorithm is used in grinding experiments on a thin-walled workpiece. The force tracking error is controlled within ±0.2 N, and the surface roughness of the workpiece is improved to Ra 0.218 μm.

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Accurate modeling of material removal depth in convolutional process grinding for complex surfaces

Zhou,

Zhao,

et al. 2024

International Journal of Mechanical Sciences

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Precise and smooth contact force control for a hybrid mobile robot used in polishing

Cited by 8 publications

References 27 publications

Adaptive Fuzzy Sliding Mode Control and Dynamic Modeling of Flap Wheel Polishing Force Control System

Adaptive Fuzzy Sliding Mode Control and Dynamic Modeling of Flap Wheel Polishing Force Control System

Dual PID Adaptive Variable Impedance Constant Force Control for Grinding Robot

Accurate modeling of material removal depth in convolutional process grinding for complex surfaces

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