Nonlinear adaptive trajectory tracking control for a stratospheric airship with parametric uncertainty

Abstract

A nonlinear adaptive trajectory tracking control strategy is proposed for a fully actuated stratospheric airship subject to uncertain mass and inertia parameters. Based on the stratospheric airship trajectory tracking model, a non-certainty equivalence adaptive control approach is adopted to estimate the uncertain parameters since its excellently attractive property of the immersion and invariance manifold condition.The key idea involves a new filter construction for the regressor terms in the airship dynamics that enables the establishment of a stabilizing mechanism within the adaption process for uncertain parameters. It is proved that trajectory tracking errors asymptotically converge to zero within the Lyapunov framework. Numerical simulations are presented to demonstrate the performance of the proposed controller.

Neuroadaptive output-feedback trajectory tracking control for a stratospheric airship with prescribed performance

“…where B u (•) is a continuously bounded function on a compact set on a compact set (24) y u ∈ R 22 It should be noted that the first equation in 7 can be rewritten as ν = R T (ψ)η; thus, the function f u (ν) can be restated as a continuous function f u (ζ ), where ζ = [η T ,η T ] T . Since the nonlinear f u (ζ ) is indefinite, we use the RBF NNs to model the nonlinear functions f u (ζ ) as (13)…”

“…In Ref. (22), a non-certainty equivalence adaptive trajectory tracking control structure was formulated for a fully actuated airship subject to parametric uncertainties. By adopting a time-varying tan-type barrier Lyapunov function, Zheng et al (37,38,40) presented outputconstrained control schemes that could effectively implement error-constrained trajectory tracking or path-following, and constructed radial basis function (RBF) NNs to approximate the uncertain dynamics and disturbances of an airship.…”

Trajectory Tracking Control for a Stratospheric Airship Subject to Constraints and Unknown Disturbances

“…To generate the desired attitude ξ d (t), a Frenet frame [41] of the desired trajectory p d (t) at arbitrary time t is defined as follows: (21) where e t , e b and e n represent the tangent vector, the binormal vector and the normal vector, respectively. Then, the desired reference frame can be established by {e t , sgn(e b3 )e n , sgn(e b3 )e b }, and the rotation matrix from the desired reference frame to ERF can be written as R e d = e t , sgn(e b3 )e n , sgn(e b3 )e b where e b3 is the third element of e b [4], [11]. Since the objective of attitude tracking is to render the BRF coinciding the desired reference frame, comparing R e d = r ij (i = j = 1, 2, 3) with R e b results in the desired attitude ξ…”

“…Similar to the balloon [3], stratospheric airship gains the lift force through the use of a buoyant gas rather than aerodynamic force, which makes the airship possess longer endurance than the conventional aircraft. Unlike the balloon, the stratospheric airship is capable of cruising along the predetermined path, also known as trajectory tracking [4], [5], to accomplish relatively complicated missions, such as typhoon tracking and maritime rescue. However, the tracking control is quite difficult since stratospheric airship is a complex, highly nonlinear and…”

“…In [30], a novel type-2 fuzzy approach was proposed to cope with the parameter uncertainty. In [4], the author proposed a non-certainty equivalence adaptive control to estimate the uncertain parameters, and asymptotic convergence of errors was guaranteed. A radial basis function neural network was applied to compensate for the unknown wind field in [31].…”