As to control systems, transient performance is as important as steady‐state performance. For some special dynamic systems, transient performance is a more prior index in comparison with the steady‐state one. Prescribed performance control (PPC) has been proved to be a powerful tool that guarantees control system outputs/errors with desired transient performance as well as steady‐state performance. The purpose of this paper is to give a comprehensive review on the latest developments of PPC theories and applications. The existing performance functions are classified into five different categories, and their features are comprehensively compared, providing a useful guidance for further applications. Then, the latest developments of PPC's applications in all kinds of control systems are recalled. Specially, the faced challenges and theoretical defects of PPC are discussed, which is expected to point out the further research direction for PPC.

The existing prescribed performance control (PPC) strategies exhibit the fragility and nonguarantee of the prescribed performance when they are applied to dynamic systems with actuator saturation, and moreover, all of them are unable to quantitatively design prescribed performance. This article aims at remedying those deficiencies by proposing a new nonfragile PPC method for waverider vehicles (WVs) such that the quantitative prescribed performance can be guaranteed for tracking errors in the presence of actuator saturation. First, readjusting performance functions are developed to achieve quantitative prescribed performance and prevent the fragile problem. Then, low-complexity fuzzy neural control protocols are presented for velocity subsystem and altitude subsystem of WVs, while there is no need of recursive back-stepping design. Furthermore, auxiliary systems are designed to generate effective compensations on control constraints, which contributes to the guarantee of the desired prescribed performance, being proved via Lyapunov synthese. Finally, compared simulation results are given to validate the superiority.

Optimal performance is extremely important for hypersonic flight control. Different from the most existing methodologies which only consider basic control performance including stability, robustness and transient performance, this article deals with the design of nearly optimal tracking controllers for hypersonic flight vehicles (HFVs). Firstly, main controllers are developed for the velocity subsystem and the altitude subsystem of HFVs via concise fuzzy approximations. Then, optimal controllers are nearly implemented utilizing single-network adaptive critic design. Moreover, the stability of closed-loop systems and the convergence of optimal controllers are theoretically proved. Finally, compared simulation results are given to verify the superiority. The special contribution is the application of low-complex control structure owing to the critic-only network and advanced learning laws developed for fuzzy approximations, which is expected to guarantee satisfied real-time performance.

This article addresses a finite-time prescribed performance controller within the concise fuzzy-neural framework with application to a waverider aircraft. First, new finite-time performance functions are developed to construct a constraint funnel, which accomplishes that tracking errors converge to their steady-state values in a given time (i.e., finite-time convergence), being expected to guarantee tracking errors with small overshoots. Then, the equivalent transformation approach is introduced to unify unknown dynamics such that the control complexity is reduced. Moreover, to further reduce computational costs, a single-learning-parameter-based regulation scheme is developed for fuzzy-neural approximation. Finally, the proposed method is applied to a waverider aircraft to test its effectiveness and superiority.