Dynamic Modeling, Trajectory Optimization, and Linear Control of Cable-Driven Parallel Robots for Automated Panelized Building Retrofits †

שמור ב:
מידע ביבליוגרפי
הוצא לאור ב:Buildings vol. 15, no. 9 (2025), p. 1517
מחבר ראשי: Liu, Yifang
מחברים אחרים: Maldonado, Bryan P
יצא לאור:
MDPI AG
נושאים:
גישה מקוונת:Citation/Abstract
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MARC

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045 2 |b d20250101  |b d20251231 
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100 1 |a Liu, Yifang 
245 1 |a Dynamic Modeling, Trajectory Optimization, and Linear Control of Cable-Driven Parallel Robots for Automated Panelized Building Retrofits † 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a The construction industry faces a growing need for automation to reduce costs, improve accuracy and productivity, and address labor shortages. One area that stands to benefit significantly from automation is panelized prefabricated building envelope retrofits, which can improve a building’s energy efficiency in heating and cooling interior spaces. In this paper, we propose using cable-driven parallel robots (CDPRs), which can effectively lift and handle large objects, to install these panels. However, implementing CDPRs presents significant challenges because of their nonlinear dynamics, complex trajectory planning, and precise control requirements. To tackle these challenges, this work focuses on a new application of established control and trajectory optimization theories in a CDPR simulation of a building envelope retrofit under real-world conditions. We first model the dynamics of CDPRs, highlighting the critical role of damping in system behavior. Building on this dynamic model, we formulate a trajectory optimization problem to generate feasible and efficient motion plans for the robot under operational and environmental constraints. Given the high precision required in the construction industry, accurately tracking the optimized trajectory is essential. However, challenges such as partial observability and external vibrations complicate this task. To address these issues, a Linear Quadratic Gaussian control framework is applied, enabling the robot to track the optimized trajectories with precision. Simulation results show that the proposed controller enables precise end effector positioning with errors under 4 mm, even in the presence of external wind disturbances. Through comprehensive simulations, our approach allows for an in-depth exploration of the system’s nonlinear dynamics, trajectory optimization, and control strategies under controlled yet highly realistic conditions. The results demonstrate the feasibility of CDPRs for automating panel installation and provide insights into their practical deployment. 
653 |a Accuracy 
653 |a Green buildings 
653 |a Building envelopes 
653 |a End effectors 
653 |a Energy efficiency 
653 |a Optimization 
653 |a Linear control 
653 |a Robots 
653 |a Nonlinear systems 
653 |a Automation 
653 |a Dynamic models 
653 |a Linear quadratic Gaussian control 
653 |a Energy consumption 
653 |a Robot learning 
653 |a Construction industry 
653 |a Construction 
653 |a Vibrations 
653 |a Prefabricated buildings 
653 |a Trajectory optimization 
653 |a Robot dynamics 
653 |a Planning 
653 |a Sensors 
653 |a Damping 
653 |a Design 
653 |a Retrofitting 
653 |a Feasibility 
653 |a Dynamical systems 
653 |a Nonlinear dynamics 
653 |a Trajectory planning 
653 |a Robot control 
700 1 |a Maldonado, Bryan P 
773 0 |t Buildings  |g vol. 15, no. 9 (2025), p. 1517 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3203189258/abstract/embedded/J7RWLIQ9I3C9JK51?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3203189258/fulltextwithgraphics/embedded/J7RWLIQ9I3C9JK51?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3203189258/fulltextPDF/embedded/J7RWLIQ9I3C9JK51?source=fedsrch