This paper presents an incremental backstepping sliding-mode (IBS) controller for trajectory control of a tailless aircraft with unknown disturbances and model uncertainties. The proposed controller is based on a nonlinear dynamic model of the tailless aircraft. A stability enhancer (SE) that limits both the rate and amplitude of the virtual control input is proposed. The stability enhancer consists of two layers. When the virtual control input approaches the edge, the first layer SE would be activated to modify the trajectory tracking error; when the virtual control input exceeds the edge, the second layer SE would reduce the control gains to make sure the virtual control input drops within the edge as soon as possible. With the help of SE, the incremental control method could be extended to outer-loop control without considering the dynamics of the inner-loop system. In addition, an adaptive estimator for state derivatives is proposed, together with IBS, allowing the controller to show excellent robustness. Finally, two simulations are presented. The first simulation shows that the system is insensitive to external disturbances and model uncertainties, and the effectiveness of SE is proved in the second simulation.
Using adaptive dynamic programming (ADP), this paper presents a novel attitude-tracking scheme for over-actuated tailless unmanned aerial vehicles (UAVs) that integrates control and control allocation while accounting for nonlinearity and nonaffine control inputs. The proposed method uses the idea of nonlinear dynamic inversion to create an augmented system and converts the optimal tracking problem into an optimal regulation problem using a discounted performance function. Drawing inspiration from incremental control, this method achieves optimal tracking control for the nonaffine system by simply using a critic-only structure. Moreover, the unique design of the performance function ensures robustness against model uncertainties and external disturbances. The ADP method was found to outperform traditional control architectures that separate control and control allocation, achieving the same level of attitude-tracking performance through a more optimized approach. Furthermore, unlike many recent optimal controllers for nonaffine systems, our method does not require any model identifiers and demonstrates robustness. The superiority of the ADP-based approach is verified through two simulated scenarios, and its internal mechanism is further discussed. The theoretical analysis of robustness and stability is also provided.
This paper presents a fault-tolerant attitude control scheme, incorporating reconfiguration control allocation for supersonic tailless aircraft subject to nonlinear characteristics, actuator constraint, uncertainty, and actuator faults. The main idea is to propose an incremental reconfiguration closed-loop control allocation scheme, coupled with a basic backstepping attitude controller, to achieve attitude control. Based on the virtual control input generated by the basic backstepping attitude controller, firstly, the incremental nonlinear control allocation method is adopted to deal with the nonlinear characteristics and actuator constraint. Secondly, a distribution error feedback loop is constructed in the incremental nonlinear control allocation method to enhance the robustness against the uncertainty of the control effectiveness matrix. Thirdly, the control effectiveness matrix is reconstructed by different kinds of fault information to deal with actuator faults, and the proper combination of actuator deflections is generated to achieve accurate command tracking. The stability of the proposed scheme is guaranteed by the Jury stability criterion and the Lyapunov stability analysis. Finally, in comparison with the three existing approaches, the simulation results of two cases are provided to show the effectiveness of the proposed scheme.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.