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

Mao-Long Lv,Shu-Guang Liu,Xiu-Xia Sun,Dong Wang

doi:10.1155/2016/4753241

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.

Highlights

Ultralow altitude airdrop (ULAA) is a crucial ability of a large transport aircraft, which is mainly applied in delivering heavyweight equipment to the precise desired region and critical to the success of military tasks [1, 2]
As for a class of pure-feedback uncertain nonlinear systems with unknown dead-zone inputs and immeasurable states, based on the information of the dead-zone slopes and the unknown inputs coefficients that are treated as a system uncertainty, an adaptive fuzzy output feedback control method is proposed via the backstepping recursive design technique [13]
In the execution of the input nonlinearity of airdrop decline phase of flight path angle that tracks control problem, this paper proposes an adaptive neural network dynamic surface control method, which boasts a first-order lowpass filter introduced in the traditional backstepping control technique to avoid explosion of differential problems

Summary

Introduction

Ultralow altitude airdrop (ULAA) is a crucial ability of a large transport aircraft, which is mainly applied in delivering heavyweight equipment to the precise desired region and critical to the success of military tasks [1, 2]. An adaptive fuzzy robust output feedback control problem is considered in a class of SISO nonlinear systems in a strict-feedback form, which first uses fuzzy logic systems to approximate the unstructured uncertainties and later utilizes the information of bounds of dead-zone slopes and treats the time-varying inputs coefficients as a system uncertainty [12]. As for a class of pure-feedback uncertain nonlinear systems with unknown dead-zone inputs and immeasurable states, based on the information of the dead-zone slopes and the unknown inputs coefficients that are treated as a system uncertainty, an adaptive fuzzy output feedback control method is proposed via the backstepping recursive design technique [13]. Simulation verifies the feasibility and effectiveness of the obtained theoretical results

Problem Statement

Adaptive Flight Controller Design

Stability and Tracking Performance Analysis of the Controller

Simulation Analysis

Tracking Control Analysis with Considering Actuator Input Nonlinearity

Conclusions