Designing and application of type-2 fuzzy PID control for overhead crane systems

Sun, Zhe; Ling, Yawen; Xin, Tan; Zhou, Yang

doi:10.1007/s41315-020-00157-w

Cited by 19 publications

(8 citation statements)

References 21 publications

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“…Simulation Group 2: Comparative study The PID control method [26] is chosen for comparison. The incremental PID control law is given as As can be seen from Fig.…”

Section: A Simulation Results and Analysismentioning

confidence: 99%

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Data-Driven Model-Free Adaptive Positioning and Anti-Swing Control for Bridge Cranes

et al. 2023

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In the positioning and anti-swing control of bridge crane, a model-free adaptive control (MFAC) based on data-driven is proposed in order to eliminate the dependence of controller design on the model and the influence of unmodeled dynamics and uncertain disturbances on the controller performance. Only using the input and output data of the bridge crane system, the virtual full format dynamic linearized data model of the bridge crane nonlinear system is obtained through the data-driven modeling method. On the basis of this virtual data model, a model-free adaptive control law and a pseudo-Jacobian matrix estimation algorithm are designed according to the optimization theory under the constraint conditions. The stability of the closed loop system and the convergence of the system error are analyzed and proved by Lipschitz condition and inequality theory. The effectiveness of the control strategy for positioning and anti-swing control of bridge cranes is verified on simulated simulation and experimental platform of bridge crane. The results show that the proposed method is feasible and has good anti-disturbance performance and robustness.

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“…Simulation Group 2: Comparative study The PID control method [26] is chosen for comparison. The incremental PID control law is given as As can be seen from Fig.…”

Section: A Simulation Results and Analysismentioning

confidence: 99%

“…Experiment Group 2: Comparative study In experimental study, the PID parameters of refence [26] are selected as following.…”

Section: B Experimental Results and Analysismentioning

confidence: 99%

Data-Driven Model-Free Adaptive Positioning and Anti-Swing Control for Bridge Cranes

et al. 2023

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“…[14][15][16] It is difficult to obtain the desired control performance with this conventional PID control. 17,18 Hence, it needs to be combined with other control strategies, such as objective optimization algorithm, 19 neural network-based PID controllers, 20 genetic algorithm-based PID controllers, 21 and fuzzy control-based PID controllers. 22,23 Subsequent studies have increasingly focused on PD controllers combined with input shaping, 24,25 which is effective in suppressing the oscillations in mechanical systems such as manipulators 26 and spacecraft.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Response of an Overhead Crane with Anti-Swing Controller in Driving Force and Energy Consumption

Gao,

Gong,

et al. 2024

The International Journal of Acoustics and Vibration

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Cargo sway caused by overhead crane operation not only reduces crane efficiency and safety but also affects the driving force and energy consumption of the operating mechanism. In this paper, a control scheme based on proportional derivative (PD) control and an input shaping technique is proposed to suppress cargo sway. First, the dynamics model of the crane system is established, and the mathematical expressions of the cargo sway, driving force, and energy consumption are derived. The accuracy of the dynamics model is verified through a comparison between the simulations and experiments. Then, a PD-IS controller is designed based on the dynamics model. Finally, the performance of the designed controller is simulated under four typical excitation signals and compared to that of the standard PD controller.

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“…At present, a considerable number of electronic anti-sway control strategies have been applied to the anti-sway control system of bridge cranes to suppress the swing angle generated by the load during crane operation. The main methods include DPID [3] and FPID [4] . However, the controller designed with the PID algorithm has simplified the dynamic model of the bridge crane linearly and has not made good use of the nonlinear characteristics of the crane system, so the control effect is poor.…”

Section: Introductionmentioning

confidence: 99%

Energy Coupling Control of Bridge Crane Based on Adaptive Fuzzy Strategy

Ye³

2023

J. Phys.: Conf. Ser.

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Aiming at the problem that the traditional PID algorithm omits the nonlinear characteristics of the bridge crane system and the control effect is limited, this paper puts forward an energy coupling control strategy based on an adaptive fuzzy strategy. The coupling generalized semaphore for the Lyapunov controller is obtained by solving the dynamic equation of the bridge crane with energy, and the controller parameters are adjusted by using an adaptive fuzzy strategy. The simulation results show that the designed controller has a better anti-sway effect than the traditional PID controller.

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Designing and application of type-2 fuzzy PID control for overhead crane systems

Cited by 19 publications

References 21 publications

Data-Driven Model-Free Adaptive Positioning and Anti-Swing Control for Bridge Cranes

Data-Driven Model-Free Adaptive Positioning and Anti-Swing Control for Bridge Cranes

Dynamic Response of an Overhead Crane with Anti-Swing Controller in Driving Force and Energy Consumption

Energy Coupling Control of Bridge Crane Based on Adaptive Fuzzy Strategy

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