Nonlinear robust sliding mode control of a quadrotor unmanned aerial vehicle based on immersion and invariance method

Abstract

Summary We present an asymptotic tracking controller for an underactuated quadrotor unmanned aerial vehicle using the sliding mode control method and immersion and invariance based adaptive control strategy in this paper. The control system is divided into two loops: the inner‐loop for the attitude control and the outer‐loop for the position. The sliding mode control technology is applied in the inner‐loop to compensate the unmatched nonlinear disturbances, and the immersion and invariance approach is chosen for the outer‐loop to address the parametric uncertainties. The asymptotic tracking of the position and the yaw motion is proven with the Lyapunov based stability analysis and LaSalle's invariance theorem. Real‐time experiment results performed on a hardware‐in‐the‐loop‐simulation testbed are presented to validate the good control performance of the proposed scheme. Copyright © 2014 John Wiley & Sons, Ltd.

High‐order mismatched disturbance rejection control for small‐scale unmanned helicopter via continuous nonsingular terminal sliding‐mode approach

“…It can be noted that the sliding surface dynamics (23) and system dynamics (24) are both subject to the error dynamics of FTDO (11).…”

“…[3][4][5][6] In the past decades, many elegant control methods have been employed for the unmanned helicopters, such as linear quadratic gaussian, 7 H ∞ , 8 feedback-linearization control, 9 backstepping, 10 sliding-mode control (SMC). 11 Above all, the SMC method has drawn much attention for its superior disturbance rejection ability. 12 However, the traditional SMC can only deal with matched disturbances, which means that the disturbances enter system via the same channels as the control inputs.…”

Nonlinear control with integral sliding properties for circular aerial robot trajectory tracking: Real‐time validation

“…Trajectory tracking algorithms based on SMCs have been proposed in the work of Tian et al and by using multiple control layers. However, all of these works have limited the validation of their proposed algorithms to simulations (in most cases), or to constrained experimental setups; see the works of Zhao et al and Liu et al…”

“…Trajectory tracking algorithms based on SMCs have been proposed in the work of Tian et al 27 and by using multiple control layers. However, all of these works have limited the validation of their proposed algorithms to simulations (in most cases), or to constrained experimental setups; see the works of Zhao et al 28 and Liu et al 29 The main scope of this work is the development of an ISM control algorithm to stabilize a quadrotor modeled as a nonlinear MIMO system. The algorithm is composed by two parts, ie, the first one is designed to compensate external perturbations since the beginning, while the second one consists on a supertwisting SMC, which ensures the convergence of a sliding surface to zero in a desired finite time.…”

Model‐assisted extended state observer and dynamic surface control–based trajectory tracking for quadrotors via output‐feedback mechanism

“…(–) For the available research results, the conventional separation between the position (outer loop) and the attitude (inner loop) is commonly taken to tackle the underactuated property that is also known as the hierarchical control strategy, consisting of a 2‐stage architecture with the synergistic combination of different approaches. For example, in the work of Zhao et al, the immersion and invariance approach was chosen for the outer‐loop to address the parametric uncertainties, whereas the sliding‐mode control technology was applied in the inner‐loop to compensate for nonlinear disturbances. A hierarchical controller scheme, consisting of a model predictive controller to track the reference trajectory together with a nonlinear H ∞ controller to stabilize the rotational movements, is developed to solve the path following the problem of quadrotors .…”