Variants of the Sliding Mode Control in Presence of External Disturbance for Quadrotor

Abstract

In this paper, an Improved Integral Power Rate Exponential Reaching Law (IIPRERL) Sliding Mode Control strategy has been presented to cater to the chattering problem and stability issue with the focusing on to achieve minimum steady-state errors in the presence of matched disturbances for a quadrotor. Control strategies have been implemented on quadrotor which is 6 Degree of Freedom (DOF) underactuated model and it is derived via Newton-Euler(NE) equations. The main focus of this article is to design two flight control strategies for a quadrotor. Firstly, a novel IIPRERL-SMC is designed through Improved Integral Sliding Mode Control (II-SMC) via proper gain scheduling by system Eigenvalues. The control objective is to construct a controller such that would force the state trajectories to approach the sliding surface with an exponential policy. Meanwhile, a strong condition for reaching the law of sliding surface via Hurwitz stability has been introduced to the hovering of the quadrotor. Secondly, kinodynamic Rapidly Exploring Random Tree with Fixed Node (RRT*FN) which is an incremental sampling-based optimal algorithm has been implemented for online navigation and flight control of the quadrotor system. Online planning which is based on the offline one, is given on-board radar readings which gradually produces a smooth 3-D trajectory aiming at reaching a predetermined target in an unknown environment. The performance and stability of the quadrotor are completely examined by utilizing Lyapunov stability analysis. Simulations are presented to verify that the proposed scheme is effective with Hurwitz stability for both translational and rotational parts of the quadrotor.

Trajectory tracking based on neural network sliding mode controller

“…where sgn is the signum function given by: (10) Define the RBFNN control law as: (11) the expected weight of RBFNNs can be acquired based on the optimization method as follows: (12) where is the estimated weight of W. from equation ( 4), it can be obtained: (13) among them, M, C, F, and G need to be measured and calculated to obtain their nominal parameter matrices.…”

“…According to equation (13), in order to enhance the adaptive learning capability of the system and improve the robustness, the desired trajectory information is introduced into the neural network and combined with the sliding mode control as follows: (20) in equation (20), assuming that is the new weight corresponding to the neural network, it is easy to know that which is guaranteed to be globally bounded by equation (13).…”

“…In Section 2, a neural network adaptive sliding mode control method is designed for a common n-joint robotic arm, however, it is difficult to decouple the kinematics for a multi-branch, multi-joint, and strongly coupled nonlinear system, such as a parallel robot, so a analysis is needed first, and then an appropriate control law is constructed according to equation (21). Compared with the general tandem robots, six-axis parallel robots are characterized by compact complex structure, high stiffness, high load capacity, no cumulative error, high accuracy, low component wear, and long service life [13]. However, as most of parallel mechanisms are open loop and have many links and joints, calibration is crucial to ensure the motion accuracy.…”

A predictive sliding mode control for quadrotor’s trackingtrajectory subject to wind gusts and uncertainties

“…The integral action added to the sliding manifold has the ability to eliminate the reaching phase and reduce the chattering on the control inputs. Ahmad et al [12] applied an improved integral power rate exponential reaching law (IIPRERL) sliding mode control strategy to deal with the unwanted chattering problem, stability, and the oscillations in the quadrotor responses in the presence of matched disturbances. The simulation results of IIPRERL-SMC have shown no chattering on the control inputs compared to SMC.…”

Robust Output Feedback Control of Single-Link Flexible-Joint Robot Manipulator with Matched Disturbances Using High Gain Observer

“…In this article, robust sliding mode control (SMC) technique is designed in conjunction with a high-gain observer to overcome these challenges. Owing to its outstanding robust nature and computational simplicity, SMC has attained popularity in several scientific applications [ 46 , 47 ]. To deal with bounded external disturbances, perturbations, and uncertainties of nonlinear systems, SMC is one of the most widely used powerful methods.…”