A new intelligent controller based on integral sliding mode control and extended state observer for nonlinear MIMO drone quadrotor
Unmanned aerial vehicles (UAVs) control faces major challenges such as dynamic complexity, unknown external disturbances, parametric uncertainties, time-varying states and delays. The literature proposes different techniques to address these challenges, but little attention has been paid to the desi...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2024-01-01
|
| Series: | International Journal of Intelligent Networks |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666603024000058 |
| _version_ | 1797317048853856256 |
|---|---|
| author | Moussa Abdillah El Mehdi Mellouli Touria Haidi |
| author_facet | Moussa Abdillah El Mehdi Mellouli Touria Haidi |
| author_sort | Moussa Abdillah |
| collection | DOAJ |
| description | Unmanned aerial vehicles (UAVs) control faces major challenges such as dynamic complexity, unknown external disturbances, parametric uncertainties, time-varying states and delays. The literature proposes different techniques to address these challenges, but little attention has been paid to the design of a hybrid controller combining the advantages of these techniques to improve system performance. This research therefore aims to investigate the design of such a hybrid controller. In this paper, we present a novel intelligent controller based on Integral Sliding Mode Control (ISMC) and Extended State Observer (ESO) for a nonlinear Multiple Input Multiple Output (MIMO) drone quadrotor. First, the kinematic and dynamic models of our quadrotor drone are presented. Second, the ESO is used to estimate external disturbances and model uncertainties. Third, to overcome the problem of the reaching phase and the steady-state error, a new nonlinear ISMC is designed. The additive term of the ISMC structure has also overcome the problem of external disturbances and modelling errors, as well as observational errors. Fourth, an Adaptive Neural Network (ANN) switching control law is developed to surmount the chattering phenomenon. In addition, the stability of the control system is verified using Lyapunov stability theory. Finally, the effectiveness and superiority of the proposed control method are proved by simulation results. The results show that the proposed approach can handle external disturbances and eliminate chatter, leading to smooth control laws and lower power consumption, which is excellent from an energy efficiency perspective. |
| first_indexed | 2024-03-08T03:29:14Z |
| format | Article |
| id | doaj.art-4c592199d5e24b4baa81acfc7cb850ed |
| institution | Directory Open Access Journal |
| issn | 2666-6030 |
| language | English |
| last_indexed | 2024-03-08T03:29:14Z |
| publishDate | 2024-01-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | International Journal of Intelligent Networks |
| spelling | doaj.art-4c592199d5e24b4baa81acfc7cb850ed2024-02-11T05:12:28ZengKeAi Communications Co., Ltd.International Journal of Intelligent Networks2666-60302024-01-0154962A new intelligent controller based on integral sliding mode control and extended state observer for nonlinear MIMO drone quadrotorMoussa Abdillah0El Mehdi Mellouli1Touria Haidi2Laboratory of Engineering, Systems and Applications, Sidi Mohammed Ben Abdellah University- National School of Applied Sciences, Fes, Morocco; Corresponding author.Laboratory of Engineering, Systems and Applications, Sidi Mohammed Ben Abdellah University- National School of Applied Sciences, Fes, MoroccoLaboratory LAGES, Ecole Hassania Des Travaux Publics (EHTP), Casablanca, MoroccoUnmanned aerial vehicles (UAVs) control faces major challenges such as dynamic complexity, unknown external disturbances, parametric uncertainties, time-varying states and delays. The literature proposes different techniques to address these challenges, but little attention has been paid to the design of a hybrid controller combining the advantages of these techniques to improve system performance. This research therefore aims to investigate the design of such a hybrid controller. In this paper, we present a novel intelligent controller based on Integral Sliding Mode Control (ISMC) and Extended State Observer (ESO) for a nonlinear Multiple Input Multiple Output (MIMO) drone quadrotor. First, the kinematic and dynamic models of our quadrotor drone are presented. Second, the ESO is used to estimate external disturbances and model uncertainties. Third, to overcome the problem of the reaching phase and the steady-state error, a new nonlinear ISMC is designed. The additive term of the ISMC structure has also overcome the problem of external disturbances and modelling errors, as well as observational errors. Fourth, an Adaptive Neural Network (ANN) switching control law is developed to surmount the chattering phenomenon. In addition, the stability of the control system is verified using Lyapunov stability theory. Finally, the effectiveness and superiority of the proposed control method are proved by simulation results. The results show that the proposed approach can handle external disturbances and eliminate chatter, leading to smooth control laws and lower power consumption, which is excellent from an energy efficiency perspective.http://www.sciencedirect.com/science/article/pii/S2666603024000058Integral sliding mode controlExtended state observerNonlinear MIMO quadrotor droneAdaptive neural networksLyapunov stability theoryEnergy efficiency |
| spellingShingle | Moussa Abdillah El Mehdi Mellouli Touria Haidi A new intelligent controller based on integral sliding mode control and extended state observer for nonlinear MIMO drone quadrotor International Journal of Intelligent Networks Integral sliding mode control Extended state observer Nonlinear MIMO quadrotor drone Adaptive neural networks Lyapunov stability theory Energy efficiency |
| title | A new intelligent controller based on integral sliding mode control and extended state observer for nonlinear MIMO drone quadrotor |
| title_full | A new intelligent controller based on integral sliding mode control and extended state observer for nonlinear MIMO drone quadrotor |
| title_fullStr | A new intelligent controller based on integral sliding mode control and extended state observer for nonlinear MIMO drone quadrotor |
| title_full_unstemmed | A new intelligent controller based on integral sliding mode control and extended state observer for nonlinear MIMO drone quadrotor |
| title_short | A new intelligent controller based on integral sliding mode control and extended state observer for nonlinear MIMO drone quadrotor |
| title_sort | new intelligent controller based on integral sliding mode control and extended state observer for nonlinear mimo drone quadrotor |
| topic | Integral sliding mode control Extended state observer Nonlinear MIMO quadrotor drone Adaptive neural networks Lyapunov stability theory Energy efficiency |
| url | http://www.sciencedirect.com/science/article/pii/S2666603024000058 |
| work_keys_str_mv | AT moussaabdillah anewintelligentcontrollerbasedonintegralslidingmodecontrolandextendedstateobserverfornonlinearmimodronequadrotor AT elmehdimellouli anewintelligentcontrollerbasedonintegralslidingmodecontrolandextendedstateobserverfornonlinearmimodronequadrotor AT touriahaidi anewintelligentcontrollerbasedonintegralslidingmodecontrolandextendedstateobserverfornonlinearmimodronequadrotor AT moussaabdillah newintelligentcontrollerbasedonintegralslidingmodecontrolandextendedstateobserverfornonlinearmimodronequadrotor AT elmehdimellouli newintelligentcontrollerbasedonintegralslidingmodecontrolandextendedstateobserverfornonlinearmimodronequadrotor AT touriahaidi newintelligentcontrollerbasedonintegralslidingmodecontrolandextendedstateobserverfornonlinearmimodronequadrotor |