Prescribed-Time and Prescribed-Performance Control for Nonlinear Dynamical Systems

The evolution of safety-critical autonomous systems, including agile drones and surgical robots, has fundamentally increased the demands for control design. It is no longer sufficient for a controller to be stable eventually; engineers now demand absolute, mathematically guaranteed performance from the very first moment of operation. They need to answer critical questions a priori: Will the tracking error settle within 2 seconds? Can we guarantee zero overshoot? Traditional asymptotic or even finite-time control theory often leaves these precise transient specifications as post-analysis hopes rather than pre-design guarantees. This gap between design objective and verifiable outcome is the critical challenge that Prescribed-Time (PT) and Prescribed-Performance Control (PPC) frameworks are engineered to solve. By embedding the desired performance specifications, such as convergence time, maximum overshoot, steady-state bounds, directly into the control law's structure, these paradigms transform performance from a hopeful outcome into a contractual design constraint, offering guaranteed control over dynamic behavior.This Research Topic aims to advance and consolidate the paradigm shift from predictive to prescribed control design. The primary goal is to gather innovative research that directly addresses the challenge of translating strict, user-defined performance specifications, including convergence time, overshoot limits, steady-state bounds, into mathematically rigorous control frameworks. We specifically seek contributions that solve key open problems, such as extending PT/PPC to more complex system structures (e.g., pure-feedback, switched, or large-scale networks), creating new time-varying scaling and barrier function techniques, and successfully merging these frameworks with adaptive, robust, or event-triggered control schemes. Ultimately, the collection will highlight methods that move beyond simulation-based validation to provide verifiable, a priori performance certificates, embodying the principle that a controller should not merely function, but function exactly as mandated at the design stage.We welcome high-quality original research, review articles, and methodological perspectives. Contributions are solicited on themes including, but not limited to:- Novel prescribed-time stabilization and tracking control architectures.- Adaptive prescribed-performance control for uncertain nonlinear systems.- Integration with fault-tolerant control, event-triggered control, and networked control systems.- Applications in robotics (manipulator, UAV), space systems, automotive systems, power electronics, and process control.- Control under state/input constraints using barrier Lyapunov functions within PT/PPC frameworks.- Theoretical extensions to stochastic systems, multi-agent systems, and singularly perturbed systems.- Experimental validations and comparative studies demonstrating the practical superiority of PT/PPC designs. Topic editors: Quanmin Zhu, Mehdi Golestani, Guangtai Tian Source: https://www.frontiersin.org/research-topics/77869/prescribed-time-and-prescribed-performance-control-for-nonlinear-dynamical-systems