本文旨在系统综述英国应用性系统思维(Applied Systems Thinking)的研究历程与前沿进展,该领域以系统科学为基础,以系统思想为核心,形成了一系列系统方法论,旨在解决复杂性问题。自20世纪50年代起,随着系统科学理论的兴起与发展,系统思...本文旨在系统综述英国应用性系统思维(Applied Systems Thinking)的研究历程与前沿进展,该领域以系统科学为基础,以系统思想为核心,形成了一系列系统方法论,旨在解决复杂性问题。自20世纪50年代起,随着系统科学理论的兴起与发展,系统思维逐渐形成并被跨学科应用于管理科学等多个领域。彼得·切克兰德(Peter Checkland)等一批英国学者,通过结合社会理论与管理实践,创立了旨在指导组织管理与复杂问题解决的系统方法论,即应用性系统思维。本文采用历史时间、内容结构及理论基础与争论的三维框架,全面梳理了英国应用性系统思维从诞生至今的演变过程,将其概括为硬系统思维、软系统思维及批判性系统思维三类主要类型,并呈现了该领域中的相关理论基础与争论。进一步地,本文对未来系统思维发展进行展望,主张可以从系统科学哲学角度提炼系统思想与方法论原则,并认为未来应用性系统思维的理论创新需深化哲学基础研究,并且需要从系统科学的最新发展成果中吸收有价值的概念或思想,以丰富系统思维的内涵。展开更多
This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mi...This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.展开更多
文摘本文旨在系统综述英国应用性系统思维(Applied Systems Thinking)的研究历程与前沿进展,该领域以系统科学为基础,以系统思想为核心,形成了一系列系统方法论,旨在解决复杂性问题。自20世纪50年代起,随着系统科学理论的兴起与发展,系统思维逐渐形成并被跨学科应用于管理科学等多个领域。彼得·切克兰德(Peter Checkland)等一批英国学者,通过结合社会理论与管理实践,创立了旨在指导组织管理与复杂问题解决的系统方法论,即应用性系统思维。本文采用历史时间、内容结构及理论基础与争论的三维框架,全面梳理了英国应用性系统思维从诞生至今的演变过程,将其概括为硬系统思维、软系统思维及批判性系统思维三类主要类型,并呈现了该领域中的相关理论基础与争论。进一步地,本文对未来系统思维发展进行展望,主张可以从系统科学哲学角度提炼系统思想与方法论原则,并认为未来应用性系统思维的理论创新需深化哲学基础研究,并且需要从系统科学的最新发展成果中吸收有价值的概念或思想,以丰富系统思维的内涵。
基金supported by the National Natural Science Foundation of China(No.12372045)the National Key Research and the Development Program of China(Nos.2023YFC2205900,2023YFC2205901)。
文摘This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.
