Dynamic Model and Intelligent Optimal Controller of Flexible Link Manipulator System with Payload Uncertainty

Alandoli, Esmail Ali; Lee, T. S.; Lin, You-Wei; Vijayakumar, V.

doi:10.1007/s13369-021-05436-7

Cited by 15 publications

(6 citation statements)

References 38 publications

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“…The relevant symbols of the manipulator are shown in Nomenclature. According to the theory and formulas of structural dynamics, mean normal stress ratio to shear stress can be calculated, as shown in Equation (1). Therefore, σ ave τ s .…”

Section: Dynamic Modeling Of Micro-deformable Manipulatormentioning

confidence: 99%

“…We considered the plane motion single-rod micro-deformable manipulator as the research object (Figure 1); its cross-section was circular, and its radius, R, was 0.01 m. The relevant symbols of the manipulator are shown in Nomenclature. According to the theory and formulas of structural dynamics, mean normal stress ratio to shear stress can be calculated, as shown in Equation (1). Therefore, ave s σ τ  .…”

Section: Dynamic Modeling Of Micro-deformable Manipulatormentioning

confidence: 99%

“…With the rapid development of modern manipulators, the traditional rigid manipulators with large mass and margin cannot satisfy fast response and accurate positioning requirements. However, micro-deformable manipulators have lighter weight, lower energy consumption, and less inertia than traditional manipulators; moreover, they have high precision, high efficiency, high speed, high flexibility, high adaptability, and intelligence [ 1 ]. Their application range is wider than that of rigid manipulators.…”

Section: Introductionmentioning

confidence: 99%

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The Boundary Proportion Differential Control Method of Micro-Deformable Manipulator with Compensator Based on Partial Differential Equation Dynamic Model

et al. 2021

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It is challenging to accurately judge the actual end position of the manipulator—regarded as a rigid body—due to the influence of micro-deformation. Its precise and efficient control is a crucial problem. To solve the problem, the Hamilton principle was used to establish the partial differential equation (PDE) dynamic model of the manipulator system based on the infinite dimension of the working environment interference and the manipulator space. Hence, it resolves the common overflow instability problem in the micro-deformable manipulator system modeling. Furthermore, an infinite-dimensional radial basis function neural network compensator suitable for the dynamic model was proposed to compensate for boundary and uncertain external interference. Based on this compensation method, a distributed boundary proportional differential control method was designed to improve control accuracy and speed. The effectiveness of the proposed model and method was verified by theoretical analysis, numerical simulation, and experimental verification. The results show that the proposed method can effectively improve the response speed while ensuring accuracy.

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Section: Dynamic Modeling Of Micro-deformable Manipulatormentioning

confidence: 99%

Section: Dynamic Modeling Of Micro-deformable Manipulatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Boundary Proportion Differential Control Method of Micro-Deformable Manipulator with Compensator Based on Partial Differential Equation Dynamic Model

et al. 2021

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“…As a basic part of the flexible manipulator, the joint servo motor has been used to suppress vibration of the flexible manipulator during motion. Lots of literatures improved the trajectory tracking accuracy and decreased vibration level of flexible manipulator by adjusting the joint driving torque (Alandoli et al, 2021; Zhao et al, 2021). The existing vibration control techniques based on the joint servo motor can be broadly classified into two categories, namely, feedback control and feed-forward control (Dong et al, 2019; Habibi et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Hybrid control of piezoelectric flexible manipulator based on Volterra filtered-xLMS algorithm

Yang

Zhang

2021

Journal of Vibration and Control

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To suppress the nonlinear vibration of the flexible manipulator during motion, this article presents a hybrid control strategy based on a servo motor and a piezoelectric actuator. The dynamic model of the piezoelectric flexible manipulator is established first. To realize the trajectory tracking, a proportional derivative control method is used to schedule the control torque. Because the Volterra filter can approximate the nonlinear system model, a Volterra filtered-xLMS algorithm based on a second-order Volterra filter structure is proposed, by which the active nonlinear vibration control of flexible link is realized. Simulation results show that the proposed Volterra filtered-xLMS algorithm can not only make use of the advantages of the classical filtered-xLMS algorithm but also solve the problem of effective modeling of nonlinear secondary path. The proposed hybrid control strategy based on Volterra filtered-xLMS algorithm and proportional derivative control algorithm can improve the position accuracy of joint and effectively suppress the vibration response of the nonlinear flexible link. A piezoelectric flexible manipulator with PZT (lead zirconate titanate) sensor and actuator is designed to demonstrate the validity and efficiency of the proposed method by experiments. Experiment results demonstrate that the attenuation time of vibration response is reduced from 5 s to 1.5 s, the vibration response at the first-order frequency is reduced by 60%, and the proposed methodology has an important advantage in application of active vibration control of piezoelectric flexible manipulator.

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“…However, mathematical modelling is difficult and requires long calculations especially for nonlinear systems; critical and deep discussion of mathematical modelling methods is given in reference 7 . A numerical modelling method was used to obtain SimMechanics models of robots using Simulink and Simscape toolboxes from CAD assemblies [8][9][10] . SimMechanics models are easily obtained and can be simulated and controlled, so they are preferable.…”

Section: Introductionmentioning

confidence: 99%

2-DOF robot modelling by SimMechanics and PD-FL integrated controller for position control and trajectory tracking

2021

Self Cite

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Background Due to the high demand of robots to perform several industrial tasks, such as welding, machining, pick and place, position control in robotics has attracted high attention recently. Controllers’ improvement is also continuous specifically in terms of design simplicity and performance accuracy. This research plans to obtain the SimMechanics model of a two-degree of freedom (DOF) robot and to propose an integrated controller of a proportional–derivative (PD) controller and a fuzzy logic (FL) controller. Methodology The SimMechanics model of the 2-DOF robot is obtained using MATLAB SimMechanics toolbox from a CAD assembly design of the 2-DOF robot. Then, the proposed PD-FL integrated controller is designed and simulated in MATLAB Simulink. The PD controller is widely used for its simplicity, but it doesn’t have a satisfactory performance in difficult tasks. Furthermore, the FL controller is also easy for design and implementation even by non-experts in control theory, but it has the disadvantage of long computational time for multi-input systems due to the increased fuzzy rules. Results The FL controller is integrated with the PD controller for enhanced performance of the 2-DOF robot. The PD-FL integrated controller is developed and tested to control the 2-DOF robot for point-to-point position control and also tip trajectory tracking (TTT) such as triangular TTT and rhombic TTT. Conclusion The PD-FL integrated controller demonstrates enhanced performance compared to the conventional PD controller in both point-to-point position control and TTT. Furthermore, the PD-FL integrated controller has the advantage of less fuzzy rules which helps to overcome the computational time issue of the FL controller.

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Dynamic Model and Intelligent Optimal Controller of Flexible Link Manipulator System with Payload Uncertainty

Cited by 15 publications

References 38 publications

The Boundary Proportion Differential Control Method of Micro-Deformable Manipulator with Compensator Based on Partial Differential Equation Dynamic Model

The Boundary Proportion Differential Control Method of Micro-Deformable Manipulator with Compensator Based on Partial Differential Equation Dynamic Model

Hybrid control of piezoelectric flexible manipulator based on Volterra filtered-xLMS algorithm

2-DOF robot modelling by SimMechanics and PD-FL integrated controller for position control and trajectory tracking

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