Passivity-based coupling control for underactuated three-dimensional overhead cranes

Zhang, Shengzeng; Zhu, Haiyue; He, Xiongxiong; Feng, Yuanjing; Pang, Chee Khiang

doi:10.1016/j.isatra.2021.07.040

Cited by 22 publications

(12 citation statements)

References 47 publications

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“…The same strategy has been employed by [216] with the difference that the torque applied to the winch (F l in (3)) has been also taken into account for position tracking of the load. PBC has also been developed for the 3D operating space with initial control saturation avoidance [304]. This method has been extended in [299] without partial feedback linearization to improve the robustness.…”

Section: Passivity-based Controlmentioning

confidence: 99%

Modeling and control of overhead cranes: A tutorial overview and perspectives

Mojallizadeh

Brogliato

Prieur

2023

Annual Reviews in Control

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Section: Passivity-based Controlmentioning

confidence: 99%

Modeling and control of overhead cranes: A tutorial overview and perspectives

Mojallizadeh

Brogliato

Prieur

2023

Annual Reviews in Control

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“…An extended Kalman filter is used for the estimation of payload angles and angular velocity. In [45] modified tracking error variables and Lyapunov stability analysis are used to define a feedback controller that finally stabilizes a 4-DOF overhead crane. The global stability proof makes use of LaSalle's invariance principle.…”

Section: State-of-the-art In the Control Of Underactuated Robotic Cranesmentioning

confidence: 99%

Nonlinear optimal control for the 4-DOF underactuated robotic tower crane

Rigatos

Abbaszadeh

Pomares

2022

Auton. Intell. Syst.

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Tower cranes find wide use in construction works, in ports and in several loading and unloading procedures met in industry. A nonlinear optimal control approach is proposed for the dynamic model of the 4-DOF underactuated tower crane. The dynamic model of the robotic crane undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the system a stabilizing optimal (H-infinity) feedback controller is designed. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed control approach is advantageous because: (i) unlike the popular computed torque method for robotic manipulators, the new control approach is characterized by optimality and is also applicable when the number of control inputs is not equal to the robot’s number of DOFs, (ii) it achieves fast and accurate tracking of reference setpoints under minimal energy consumption by the robot’s actuators, (iii) unlike the popular Nonlinear Model Predictive Control method, the article’s nonlinear optimal control scheme is of proven global stability and convergence to the optimum.

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“…In contrast to the open-loop methods, the closed-loop feedback control methods are more robust and more resistant to the unexpected disturbance and therefore are more popular in the research field. Sliding mode control (Nguyen et al, 2022;Zhang et al, 2020Zhang et al, , 2021, fuzzy control (Miao et al, 2022;Smoczek, 2014;Tolochko and Bazhutin, 2020), observerbased control (Lu et al, 2017;Ouyang et al, 2018;Wu et al, 2020;Zhang et al, 2019), passivity-based nonlinear control (Toriumi and Angelico, 2021;Zhang et al, 2022), energy shaping-based control (Chen and Sun, 2020;Sun and Fang, 2012;Wu and He, 2017), and so on are designed and applied on trajectory tracking and anti-swing suppression for crane systems. Some intelligent algorithms such as a neural network-based control method (Abe, 2011;Nemcik et al, 2021;Yang et al, 2020), radial basis function network (RBFN) (Tuan et al, 2018), and genetic algorithm (GA) (Qian et al, 2016) are also included in the theoretical research and practical engineering.…”

Section: Introductionmentioning

confidence: 99%

Synchronous slew/translation positioning and swing suppression control for 4-DOF tower crane system

Huang

Zhao

2023

Transactions of the Institute of Measurement and Control

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This paper introduces a method to navigate the tower crane movement and suppress the payload swing synchronously. Special error signals are introduced, which bring the coupling of dynamics among various states of the crane and enable the control to meet the synchronous operation in practice. The special angle-dependent energy functions are designed as the candidate sub-Lyapunov functions for decoupling the states. The controller is then stepwise designed with the help of the dynamics model. The stability of the control is proven in the Lyapunov sense. Extensive simulations and experiments have been carried out to demonstrate the effectiveness of the proposed nonlinear coupling control. A popular control approach in the literature is chosen to compare with the current work. It is found that the proposed control is quite effective in suppressing the payload swing while tracking the pre-determined path at the same time.

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Passivity-based coupling control for underactuated three-dimensional overhead cranes

Cited by 22 publications

References 47 publications

Modeling and control of overhead cranes: A tutorial overview and perspectives

Modeling and control of overhead cranes: A tutorial overview and perspectives

Nonlinear optimal control for the 4-DOF underactuated robotic tower crane

Synchronous slew/translation positioning and swing suppression control for 4-DOF tower crane system

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