Nonfragile Quantitative Prescribed Performance Control of Waverider Vehicles With Actuator Saturation

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