大规模互联系统分散式控制研究现状与趋势OA

Significance Interconnected control systems are widely encountered in modern engineering applications,including energy networks,industrial processes,and multirobot systems.These systems comprise multiple relatively independent subsystems coupled through physical connections,material flows,energy exchanges,or other dynamic interactions,thereby forming an integrated large-scale dynamical system.Unlike conven-tional high-dimensional systems,the main difficulty in using interconnected systems does not arise solely from the increase in system dimensions,but from the strong coupling relationships among subsystems and the resulting challenges in stability analysis and controller design.A fundamen-tal problem in such systems is that the satisfactory stability of individual subsystems does not guarantee the stability and performance of the over-all system.Dynamic interactions among subsystems may modify closed-loop characteristics,reduce stability margins,deteriorate transient re-sponses,and even cause instability under certain operating conditions.With the continuous expansion of engineering system scales and increasing complexity of control objectives,traditional centralized control strategies face considerable limitations in communication requirements,online computational burden,and scalability.The need for global system information and centralized decision-making mechanisms makes such ap-proaches difficult to implement in large-scale systems with limited communication resources and real-time constraints.Decentralized control strat-egies,which have been developed by designing local feedback controllers based only on subsystem-level states or outputs without requiring global state information or information exchange among controllers,provide an effective solution with simple structures,low implementation costs,and favorable scalability.However,due to physical couplings and dynamic interactions,decentralized controllers designed independently for individual subsystems may still experience degraded transient performance,including increased settling time,excessive overshoot,and intensi-fied oscillations.Therefore,improving closed-loop transient performance while maintaining stability under interconnection effects has become an important research challenge in the decentralized control of large-scale interconnected systems. Progress In this article,representative theoretical achievements and technical developments in decentralized control for large-scale intercon-nected systems are systematically reviewed from three perspectives:interconnected system modeling and characterization,coupling effect mitigation,and closed-loop performance analysis.First,centralized,distributed,and decentralized control architectures were compared from the perspective of information structures.This enabled the differences in information requirements,communication mechanisms,com-putational modes,scalability,and typical application scenarios to be clarified.It was found that centralized control relies on global system information and centralized computation,distributed control requires information exchange among neighboring subsystems through com-munication networks,whereas decentralized control mainly relies on local subsystem information without real-time communication among controllers.Next,typical modeling approaches for interconnected systems were summarized.State interconnection,input interconnection,output interconnection,dynamic interconnection,and time-delay interconnection models were reviewed according to their different physi-cal coupling mechanisms.The characteristics,modeling assumptions,and limitations of these interconnection structures were analyzed,to-gether with their influences on stability analysis and controller design.State interconnection models were used to describe the coupling ef-fects caused by subsystem states,whereas input and output interconnection models were adopted to characterize the interactions through control actions and measured variables.Dynamic and time-delay interconnection models were used to describe more complex physical pro-cesses involving internal coupling dynamics,transmission delays,and memory effects.Furthermore,coupling-handling methods under dif-ferent levels of interconnection information availability were reviewed.For systems with completely known interconnections,exact com-pensation,decoupling control,and dynamic compensation approaches were found to directly utilize structural coupling information.For systems with bounded but uncertain interconnections,robust control,sliding-mode control,input-to-state stability analysis,and small-gain techniques were investigated to guarantee stability without requiring accurate coupling models.For systems with unknown parameters,adaptive control,backstepping methods,and dynamic surface control approaches were adopted to estimate uncertain parameters online and reduce the influence of modeling errors.When nonlinear interconnections are completely unknown,neural-network approximation,fuzzy approximation,and observer-based reconstruction methods were explored to approximate unknown dynamics.The applicable conditions,theoretical advantages,and inherent limitations of these approaches were compared,particularly regarding conservatism,computational complexity,and practical implementation difficulties.In terms of closed-loop performance improvement,the review focused on the evolu-tion of decentralized control objectives from asymptotic stability to finite-time control,fixed-time control,prescribed performance control,and prescribed-time control.Different control paradigms were analyzed according to the convergence characteristics,dependence on initial conditions,transient response improvement,and engineering implementation constraints.Additionally,considering the safety requirements of practical systems,state constraints,output constraints,and safety control methods were investigated.The integration of constraint han-dling and safety mechanisms into decentralized control extended the research objective from guaranteeing final stability to ensuring safe op-eration throughout the entire control process. Conclusions and Prospects Although substantial advances have been made in the decentralized control of interconnected systems,several chal-lenges remain.For strongly coupled and heterogeneous systems,unified modeling frameworks and effective analysis methods are required to de-scribe complex interconnection structures while reducing conservatism in stability conditions.The treatment of unknown interconnections re-mains challenging because existing approaches often rely on predefined bounds or structural assumptions,which may limit their applicability in uncertain operating environments.Improving transient performance through rapid convergence mechanisms may introduce large control gains,noise amplification,and actuator saturation problems,leading to difficulties in practical implementation.The integration of intelligent control methods also requires further investigation to ensure stability,interpretability,and reliable performance guarantees rather than relying solely on data-driven optimization.Future research should focus on modeling and analysis of strongly coupled heterogeneous systems,adaptive compensa-tion of unknown interconnections,model-data fusion-based decentralized control,intelligent enhancement with stability guarantees,and resilient control under safety constraints and external disturbances.These developments are expected to move decentralized control theory toward more scalable,reliable,and practical solutions for future large-scale complex engineering systems.