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Research Progress and Performance Optimization Paths of Robot Adaptive Control Technology: A Review

Author(s)

Xiaoman Chi

Affiliation(s)

TaiShan University, Taian, Shandong, China

Abstract

As robot technology continues to expand into complex and dynamic scenarios, adaptive control technology has become a key means to address uncertainties such as system parameter settings and external disturbances. This paper systematically reviews the research progress in this field. Breakthroughs have been achieved in algorithm theory, including nonlinear system control, constraint optimization, and integration with intelligent algorithms. In terms of scenario applications, differentiated solutions for mobile, special-purpose, and industrial robots have been established. In the aspect of cooperative control, the dynamic coordination technology for multi-robot systems has been advanced. The current technical bottlenecks are summarized as follows: the trade-off between algorithm convergence and robustness, the mismatch between dynamic modeling and actual working conditions, the difficulty in optimizing control resources under multi-constraint conditions, and the insufficient cross-domain integration. To address these bottlenecks, optimization paths based on intelligent algorithm fusion, data-model hybrid modeling, multi-objective optimization, and modular architecture reconstruction are proposed. This study can provide theoretical references for the scenario-based implementation and performance improvement of robot adaptive control technology, and promote its large-scale application in complex environments.

Keywords

Robot Adaptive Control; Performance Optimization; Intelligent Algorithm Fusion; Dynamic Modeling; Multi-Robot Cooperation

References

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