Tension distribution algorithm based on graphics with high computational efficiency and robust optimization for two-redundant cable-driven parallel robots

Gao, Haibo; Sun, Guangming; Liu, Zhen; Sun, Cong; Li, Nan; Ding, Lixin; Yu, Haitao; Deng, Zongquan

doi:10.1016/j.mechmachtheory.2022.104739

Cited by 11 publications

(3 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on this mechanical characteristic of CDPRs, there are many factors, including geometric parameters [13], modular configurations [14], and tensions of cables [15], which can affect system performances. Gao et al [16] proposed a novel tension distribution algorithm for cable-driven parallel robots, and the algorithm can calculate the tension feasible region and efficiently optimize the tension distribution. Based on driving force transmission indexes and geometrical constraints, Zhang et al [17] constituted multi-objective functions to effectively optimize the singularity, power, interference, and motion range of the parallel mechanism for hip rehabilitation.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimal Design of a Cable-Driven Parallel Robot Based on an Adaptive Adjustment Inertia Weight Particle Swarm Optimization Algorithm

Zeng

et al. 2023

Journal of Mechanical Design

View full text Add to dashboard Cite

Cable-driven parallel robots (CDPRs) have been widely used in engineering fields because of their significant advantages including high load-bearing capacity, large workspace, and low inertia. However, the impact of convergence speed and solution accuracy of optimization approaches on optimal performances can become a key issue when it comes to the optimal design of CDPR applied to large storage space. An adaptive adjustment inertia weight particle swarm optimization (AAIWPSO) algorithm is proposed for the multi-objective optimal design of CDPR. The kinematic and static models of CDPR are established based on the principle of virtual work. Subsequently, two performance indices including workspace and dexterity are derived. A multi-objective optimization model is established based on performance indices. The AAIWPSO algorithm introduces an adaptive adjustment inertia weight to improve the convergence efficiency and accuracy of traditional particle swarm optimization (PSO) algorithm. Numerical examples demonstrate that final convergence values of the objective function by the AAIWPSO algorithm can almost be 14%~20% and 19%~40% higher than those by the PSO algorithm and genetic algorithm (GA) for the optimal design of CDPR with different configurations and masses of end-effectors, respectively.

show abstract

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimal Design of a Cable-Driven Parallel Robot Based on an Adaptive Adjustment Inertia Weight Particle Swarm Optimization Algorithm

Zeng

et al. 2023

Journal of Mechanical Design

View full text Add to dashboard Cite

show abstract

“…In this paper, a CDPR prototype for 3D printing tasks is designed and constructed. Leveraging various advantages of CDPR, this type of CDPR can be reconfigured in a wide range of scenarios to accomplish additive manufacturing of building materials in large-scale spaces in the future [12]. Although CDPRs have received more attention in recent years due to their various advantages, research on CDPRs still needs to be conducted to overcome various problems associated with their structural properties.…”

Section: Introductionmentioning

confidence: 99%

“…However, due to the complexity of most tension distribution algorithms, most algorithms entail substantial computational costs, which results in the compromised real-time performance of feedback control. Currently, several algorithms, such as [12] and [13], can reduce the computational complexity of cable tension distributions to guarantee real-time performance. Moreover, some methods have been proposed to guarantee real-time performance.…”

Section: Introductionmentioning

confidence: 99%

Research on workspace visual-based continuous switching sliding mode control for cable-driven parallel robots

Qian,

Zhao,

Qian

et al. 2023

Robotica

View full text Add to dashboard Cite

Achieving the high-precision control of cable-driven parallel robots (CDPRs) is complex because of their structural properties. In this paper, a quintessential redundant CDPR is designed as the research subject, and a continuous switching sliding mode controller based on workspace vision is implemented to enhance the accuracy and stability of trajectory tracking. In addition, a virtual prototype of the CDPR with uncertainties is created in the simulation analysis software ADAMS, and co-simulation is performed with the control system designed in Simulink to validate the effectiveness of the proposed control strategy. Furthermore, a CDPR platform is established for trajectory tracking experiments using the visual-based position feedback method. The trajectory tracking performance with the three control schemes is then evaluated. The experimental results show that the continuous switching sliding mode control algorithm can significantly decrease trajectory tracking errors and exhibit superior trajectory tracking performance compared to the other control strategies.

show abstract

Hybrid Joint-space Control Strategies Analysis for One-redundant Cable Suspended Parallel Robots

Qin

Liu

Gao

2023

Lecture Notes in Mechanical Engineering

View full text Add to dashboard Cite

Tension distribution algorithm based on graphics with high computational efficiency and robust optimization for two-redundant cable-driven parallel robots

Cited by 11 publications

References 25 publications

Multi-Objective Optimal Design of a Cable-Driven Parallel Robot Based on an Adaptive Adjustment Inertia Weight Particle Swarm Optimization Algorithm

Multi-Objective Optimal Design of a Cable-Driven Parallel Robot Based on an Adaptive Adjustment Inertia Weight Particle Swarm Optimization Algorithm

Research on workspace visual-based continuous switching sliding mode control for cable-driven parallel robots

Hybrid Joint-space Control Strategies Analysis for One-redundant Cable Suspended Parallel Robots

Contact Info

Product

Resources

About