Decentralized Adaptive Control for Nonlinear Large-Scale Systems

Decentralized adaptive control addresses the coordination of numerous interconnected subsystems whose dynamics are nonlinear and subject to uncertain disturbances and faults. By endowing each subsystem with a local controller that adapts its parameters online, global stability and performance can be achieved without the need for a centralised coordinator or extensive communication links. This approach exploits Lyapunov-based design and nonlinear approximation techniques—such as neural networks or fuzzy logic—to estimate unknown functions and disturbances in real time. Key challenges include coping with time delays, actuator failures and measurement corruption, while guaranteeing robustness, finite-time convergence and avoidance of excessive complexity. Practical implementations span power grids, robotic swarms, large-scale chemical processes and networked transportation systems, where scalability, fault tolerance and minimal information exchange are essential.

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Recent studies have introduced a semi-global finite-time control strategy for high-order large-scale nonlinear systems. By constructing a composite Lyapunov function with both quadratic and higher-order terms and employing homogeneous domination methods, the proposed decentralised state-feedback law ensures that every subsystem attains stability within a finite settling time. Extensions to output tracking demonstrate versatility, and numerical as well as practical examples validate the approach’s effectiveness under unknown disturbances.

Advances in event-triggered adaptive control have addressed interconnected nonlinear delay systems suffering actuator faults. A decentralised scheme combines a K-filter observer with hyperbolic tangent functions and neural network approximators to compensate for unknown interconnection and delay effects. Dynamic surface control is incorporated to prevent complexity explosion, while adaptive triggering rules guarantee that all closed-loop signals remain semi-globally uniformly ultimately bounded and Zeno phenomena are avoided. Simulation results illustrate robust fault tolerance and reduced communication load.

Fuzzy-based dynamic surface control has emerged as an efficient means to tackle uncertain nonlinear subsystems with unknown actuator faults. Leveraging fuzzy logic systems to approximate uncertain functions and applying a layer-by-layer backstepping procedure, the adaptive controller maintains all signals within prescribed bounds and ensures tracking errors converge to an arbitrarily small neighbourhood. The dynamic surface design significantly reduces computational burden, making the method suitable for real-time implementation in resource-limited platforms.

Decentralized Adaptive Control for Nonlinear Large-Scale Systems publication trend

The graph below shows the total number of articles in decentralized adaptive control for nonlinear large-scale systems across all publications each year (not limited to Nature Index journals).

Technical terms

Decentralized adaptive control: A control architecture in which local controllers adjust their parameters online to achieve global objectives without central coordination.

Nonlinear large-scale systems: Complex assemblies of interconnected subsystems governed by nonlinear dynamics and subject to uncertainties.

Event-triggered control: A strategy that updates control actions only when predefined conditions are met, reducing unnecessary communications.

Dynamic surface control: A backstepping-based design that introduces first-order filters to avoid the explosion of algebraic complexity in adaptive laws.

Finite-time stability: A property whereby system states converge to desired values within a finite time interval under the designed controller.

References

1. Fuzzy-Based Adaptive Dynamic Surface Control for a Type of Uncertain Nonlinear System with Unknown Actuator Faults. Mathematics (2022).
2. A Semi-Global Finite-Time Decentralized Control Method for High-Order Large-Scale Nonlinear Systems. Actuators (2024).
3. Decentralized Output-Feedback Adaptive Event-Triggered Control for Interconnected Nonlinear Delay Systems with Actuator Failures. Actuators (2024).