Adaptive functional link network control of near-space vehicles with dynamical uncertainties

Abstract

The control law design for a near-space hypersonic vehicle (NHV) is highly challenging due to its inherent nonlinearity, plant uncertainties and sensitivity to disturbances. This paper presents a novel functional link network (FLN) control method for an NHV with dynamical thrust and parameter uncertainties. The approach devises a new partially-feedback-functional-link-network (PFFLN) adaptive law and combines it with the nonlinear generalized predictive control (NGPC) algorithm. The PFFLN is employed for approximating uncertainties in flight. Its weights are online tuned based on Lyapunov stability theorem for the first time. The learning process does not need any offline training phase. Additionally, a robust controller with an adaptive gain is designed to offset the approximation error. Finally, simulation results show a satisfactory performance for the NHV attitude tracking, and also illustrate the controller's robustness.

Adaptive recurrent-functional-link-network control for hypersonic vehicles with atmospheric disturbances

“…The nominal NGPC [9] is an effective NPC law designed in continuous-time domain. It can be applied to the NHV attitude controller design [7]. By (6), (9) and (14), the expressions ofα,β,μ,ṗ K ,q K andṙ K can be written as the affine nonlinear equations as…”

“…In addition, Buschek [5] designed fixedorder μ controllers considering the aeroelastic deformation, and Wilcox [6] presented a robust output feedback controller for capturing aerothermoelastic effects. Except for above researches, the authors of this paper proposed partially-feedback-functional-link-network (PFFLN) adaptive control method [7], …”

Second-Order Sliding Mode Disturbance Observer-Based Adaptive Fuzzy Tracking Control for Near-Space Vehicles with Prescribed Tracking Performance

“…In [33], by introducing the neural networks into an adaptive backstepping controller, an effective attitude controller has been proposed. For the NSV suffering from the dynamical uncertainties, an adaptive functional link network control structure has been constructed in [34]. In [35], a robust attitude controller has been designed for NSVs subjected to time-varying disturbances.…”

Improvement of Transient Stability in a Hybrid Power Multi-System Using a Designed NIDC (Novel Intelligent Damping Controller)

“…The trigonometric function is used in the FLNN, since it can be computed more quickly than the Gaussian, the sine and the cosine functions. Moreover, it also provides better performance when the outer product term is taken into account in the function expansion [15,17]. The input vector X = [X 1 , X 2 ] T is a functional expansion that uses a trigonometric polynomial basis function, and can be written in the enhanced space as ψ = [ψ 1 , ψ 2 , .…”

“…The input variables are trigonometric basis functions and the linearly independency is used for a functional expansion of the FLNN in the extended space for classification. Moreover, FLNN can capture nonlinear input-output relationships effectively by the suitable set of polynomial inputs, since the high-order effects are incorporated in the input variables into higher dimensions of the input space [15][16][17].…”