Event-Triggered Control Strategies for Nonlinear Systems
Summary
Event-triggered control strategies have emerged as a resource-efficient alternative to time-driven schemes in the regulation of nonlinear dynamical systems. Rather than updating control signals at fixed intervals, actions are initiated only when a state-dependent criterion—often derived from an error measure or Lyapunov function derivative—exceeds a prescribed threshold. This paradigm reduces communication load and computational effort, making it particularly suitable for networked systems with limited bandwidth. Key design challenges lie in ensuring closed-loop stability and robustness in the presence of uncertainties, while simultaneously minimising the frequency of updates. Recent methodological advances have integrated adaptive backstepping to compensate parametric uncertainties, barrier Lyapunov functions to enforce state constraints, and finite-time convergence analyses to guarantee rapid performance. Self-triggered variants further precompute future update instants based on current state estimates, obviating the need for continuous monitoring. Collectively, these approaches afford scalable and safe control architectures for a wide array of applications, including robotic manipulators, multi-agent consensus, sensor networks and autonomous vehicles, highlighting the global significance of event-triggered control in contemporary engineering.
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Event-Triggered Control Strategies for Nonlinear Systems publication trend
The graph below shows the total number of articles in event-triggered control strategies for nonlinear systems across all publications each year (not limited to Nature Index journals).
Technical terms
Event-triggered control: A control paradigm that executes updates only when a state-dependent criterion is met, reducing unnecessary communication and computation.
Self-triggered control: A variant in which future control update times are computed in advance from current state information, eliminating continuous condition monitoring.
Lyapunov function: A scalar function whose decrease along system trajectories is used to certify stability of equilibrium points in dynamical systems.
Nonlinear system: A dynamical system governed by equations in which outputs are not proportional to inputs, often exhibiting complex behaviours such as bifurcations.
Multi-agent system: A networked collection of interacting dynamical subsystems that cooperate under distributed control laws to achieve collective objectives.
References
- Event‐Triggered Adaptive Backstepping Control for Strict‐Feedback Nonlinear Systems with Zero Dynamics. Complexity (2019).
- A Novel Communication Time-Delay Cooperative Control Method with Switching Event-Triggered Strategy. Journal of Intelligent & Robotic Systems (2024).
- Adaptive Self-Triggered Control for Multi-Agent Systems with Actuator Failures and Time-Varying State Constraints. Actuators (2023).
- Time-Varying Transformation-Based Adaptive Tracking Control of Uncertain Robotic Systems With Event-Triggered Mechanism. IEEE Access (2022).
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