Stiffness Modeling and Dynamics Co-Modeling for Space Cable-Driven Linkage Continuous Manipulators

Xu, Hejie; Li, Xinliang; Li, Yanan; Meng, Deshan; Wang, Xueqian

doi:10.3390/math11081874

Cited by 1 publication

(1 citation statement)

References 26 publications

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“…In this regard, the gap created by the lack of interaction between software has to be bridged by developing some sort of interface. In some instances, developers of high-end commercial software have provided a built-in interface or plugins to integrate two software, e.g., SOLIDWORKS-Simscape Multibody, ANSYS-MATLAB, and MSC Adams-MATLAB, the application of which is illustrated by [6]; however, at other instances, such functionalities are not natively available. In this work, we are going to introduce Cavity Laboratory (CAVLAB), which was engendered by integrating Cavity Simulation (CAVSIM) with MATLAB.…”

Section: Motivationmentioning

confidence: 99%

Development of CAVLAB—A Control-Oriented MATLAB Based Simulator for an Underground Coal Gasification Process

Ahmed

Javed²,

Uppal

et al. 2023

Mathematics

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The Cavity Simulation Model (CAVSIM) is a 3D, parameterisable simulator of the Underground Coal Gasification Process (UCG) that serves as a benchmark for UCG prediction. Despite yielding accurate outputs, CAVSIM has some limitations, which chiefly include inadequate graphical capabilities to visualise cavity geometry and gas production, time-ineffectiveness in terms of parametrisation, i.e., it involves editing, compiling multiple files and checking for errors, and lack of tools to synthesise a controller. Therefore, to compensate for these shortcomings, the services of third-party software, such as MATLAB, must be procured. CAVSIM was integrated with MATLAB to utilise its functionalities and toolboxes such as System Identification, Neural Network, and Optimization Toolbox etc. The integration was accomplished by designing C-mex files, and furthermore, the simulation results in both environments exhibit the same behaviour, demonstrating successful integration. Consequently, CAVSIM has also acquired a controllable structure, wherein parametrisation is now a single-click process; this is demonstrated by a case study outlining the implementation of Model Predictive Control (MPC) on a UCG plant. Moreover, the performance metrics, i.e., Mean Average Error (MAE) and Root Mean Square Error (RMSE) of 0.13, 0.23 for syngas heating value, and 0.012, 0.02 for flowrate quantitatively establishes the efficacy of CAVLAB in designing MPC for the UCG system. The novelty of this work lies in making the software package open-source with the aim of streamlining the research of multiple aspects of the UCG process.

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Section: Motivationmentioning

confidence: 99%