An Adaptive Dynamic Surface Controller for Ultralow Altitude Airdrop Flight Path Angle with Actuator Input Nonlinearity

Abstract

In the process of ultralow altitude airdrop, many factors such as actuator input dead-zone, backlash, uncertain external atmospheric disturbance, and model unknown nonlinearity affect the precision of trajectory tracking. In response, a robust adaptive neural network dynamic surface controller is developed. As a result, the aircraft longitudinal dynamics with actuator input nonlinearity is derived; the unknown nonlinear model functions are approximated by means of the RBF neural network. Also, an adaption strategy is used to achieve robustness against model uncertainties. Finally, it has been proved that all the signals in the closed-loop system are bounded and the tracking error converges to a small residual set asymptotically. Simulation results demonstrate the perfect tracking performance and strong robustness of the proposed method, which is not only applicable to the actuator with input dead-zone but also suitable for the backlash nonlinearity. At the same time, it can effectively overcome the effects of dead-zone and the atmospheric disturbance on the system and ensure the fast track of the desired flight path angle instruction, which overthrows the assumption that system functions must be known.

Fuzzy Adaptive DSC Design for an Extended Class of MIMO Pure‐Feedback Non‐Affine Nonlinear Systems in the Presence of Input Constraints

“…In the past several decades, approximation-based adaptive control of nonlinear systems has been attracting much attention, and many significant results have been achieved [1][2][3][4][5][6][7][8][9][10][11]. Among them, the fuzzy logic systems (FLSs) and neural networks (NNs) have been successfully employed to approximate the unknown nonlinear functions.…”

Approximation‐Based Robust Adaptive Backstepping Prescribed Performance Control for a Huger Class of Nonlinear Systems

“…Many researchers have utilized fuzzy logic systems or neural networks (NNs) for this purpose [4][5][6][7][8][9][10]. When combined with the backstepping methodology, approximationbased adaptive approaches can achieve global stability for many classes of nonlinear systems [11][12][13][14][15]. However, as the traditional backstepping controller repeatedly differentiates the virtual controllers at each step, its complexity drastically increases as the order of systems increases.…”

Adaptive NN Control for Multisteering Plane Aircraft with Dead Zone or Backlash Input Nonlinearity

“…In [5], an adaptive fuzzy robust output-feedback control problem is considered for a class of single-input and single-output nonlinear strictfeedback system with unstructured uncertainties, unknown dead zone, and the dynamics uncertainties. Moreover, fuzzy logic systems are also applied to identify the unknown nonlinear functions, and a state filter observer is designed to estimate the unmeasured states in [6,7]. In recent years, multisteering surface control technology for aircraft with dead zone or backlash input nonlinearity has been gradually developed [8,9] and draws more and more attention from the aviation academics [10][11][12][13].…”