Experimental study on a nonlinear observer application for a very flexible parallel robot

Ansarieshlaghi, Fatemeh; Eberhard, Peter

doi:10.1007/s40435-018-0467-2

Cited by 9 publications

(3 citation statements)

References 21 publications

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“…Figure 14 shows the flexible parallel manipulator representing the virtual plant and the related underactuated manipulator with one passive joint

γ = [β]

used as model in the parametric estimation. This plant is similar to the so‐called Lambda Manipulator used in Reference 44, but with an additional degree‐of‐freedom related to the rotation of the third body (first node is on the base). Another similar manipulator was experimentally studied for control purposes in Reference 45.…”

Section: Methodology Validationmentioning

confidence: 99%

A non‐inherent parametric estimation for dynamical equivalence of flexible manipulators

Bastos

2022

Optim Control Appl Methods

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This study aims to develop a methodology for parametric estimation of flexible manipulators considering an equivalent underactuated manipulator with passive joints, which should allow better possibilities to control flexible systems when addressing challenging problems to reach a satisfactory tracking motion. Theoretically, this is achieved by a minimum number of internal dynamics variables needed for representing almost all dynamics of the system. The parametric estimation approach is based on the optimal control theory considering a robust, stable method. This methodology requires only measured/computed data that are system output. Validation occurs through a virtual plant of the flexible manipulator observing a numerical perspective. The systems studied have serial and parallel kinematics and are mounted on carts for more diverse applications and general possibilities of the methodology.

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“…Figure 14 shows the flexible parallel manipulator representing the virtual plant and the related underactuated manipulator with one passive joint

γ = [β]

Section: Methodology Validationmentioning

confidence: 99%

A non‐inherent parametric estimation for dynamical equivalence of flexible manipulators

Bastos

2022

Optim Control Appl Methods

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“…The general control algorithm needs a lot of model prior information to design the control scheme, while the controller does not need too much system model and parameter information. Therefore, neural network control can be widely used to solve the control problem of uncertain models [11].  Since some single control methods are powerless to the nonlinear system, the nonlinear function in the neural network algorithm is used to realize the nonlinear mapping function [12][13].…”

Section: Methodology 21 the Neural Networkmentioning

confidence: 99%

Analysis of Mechanical Arm Control Methods Under Non-Linear Differential Equation

2020

IJOMAM

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“…They are only found in the chemical and petrochemical industry under the name advanced process control (APC), where their implementation on a programmable logic controller (PLC) is manual and costly, and the production capacity so large that a fast return of invest can be expected [7, 8]. However, in academics, model‐based control has emerged as a state‐of‐the‐art approach and offers potential to implement lighter, more dynamic structures by considering structural flexibility in control [9].…”

Section: State Of the Artmentioning

confidence: 99%

An improved development process of production plants using digital twins with extended dynamic behaviour in virtual commissioning and control – Simulation@Operations

Pfeifer,

Scheid,

Kneifl

et al. 2023

Proc Appl Math and Mech

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The challenges in automation system development are driven by short development cycles and individualization along with resource‐constraints. State of the art solutions do not provide the necessary digital tools to apply model‐based methods in automation engineering to achieve higher performing systems. To overcome these issues this paper presents a novel approach to address some of the current challenges in automation systems development using digital twins with extended dynamic behaviour. The study underscores how dynamic models can be imported through standardised interfaces into virtual commissioning (VC) tools, improving the development process by effectively utilising domain‐specific expertise. The paper highlights how these digital twins enhance not only the VC process but can also be applied to model‐based control methods. Initial experiments showcase the utility of digital twins in calculating dynamic acceleration limits during trajectory planning of CNC control and enhancing feed‐forward control. Further, the importance of parameter identification in achieving accurate system models is stressed. The initial results are promising, and future work aims to combine these methods in an industrial application involving a newly developed, individual lightweight robot, demonstrating the potential for enhanced design, accelerated development, and resource efficiency in automation systems.

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Experimental study on a nonlinear observer application for a very flexible parallel robot

Cited by 9 publications

References 21 publications

A non‐inherent parametric estimation for dynamical equivalence of flexible manipulators

A non‐inherent parametric estimation for dynamical equivalence of flexible manipulators

Analysis of Mechanical Arm Control Methods Under Non-Linear Differential Equation

An improved development process of production plants using digital twins with extended dynamic behaviour in virtual commissioning and control – Simulation@Operations

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