Adaptive Recursive Sliding Mode Control (ARSMC)-Based UAV Control for Future Smart Cities

被引:4
作者
Abbas, Nadir [1 ]
Abbas, Zeshan [2 ]
Liu, Xiaodong [1 ]
机构
[1] Dalian Univ Technol, Sch Elect Informat & Elect Engn, Dalian 116620, Peoples R China
[2] Shenzhen Polytech, Inst Intelligent Mfg Technol, Shenzhen 518055, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 11期
关键词
smart cities; unmanned aerial vehicle; nonlinear dynamic inversion; recursive sliding mode control; adaptation laws; MIMO; OPTIMIZATION; DESIGN;
D O I
10.3390/app13116790
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The rapid expansion of the Internet and communication technologies is leading to significant changes in both society and the economy. This development is driving the evolution of smart cities, which utilize cutting-edge technologies and data analysis to optimize efficiency and reduce waste in their infrastructure and services. As the number of mobile devices and embedded computers grows, new technologies, such as fifth-generation (5G) cellular broadband networks and the Internet of Things (IoT), are emerging to extend wireless network connectivity. These cities are often referred to as unmanned aerial vehicles (UAVs), highlighting their innovative approach to utilizing technology. To address the challenges posed by continuously varying perturbations, such as unknown states, gyroscopic disturbance torque, and parametric uncertainties, an adaptive recursive sliding mode control (ARSMC) has been developed. The high computational cost and high-order nonlinear behavior of UAVs make them difficult to control. The controller design is divided into two steps. First, a confined stability analysis is performed using controllability and observability to estimate the system's stability calculation. Second, a Lyapunov-based controller design analysis is systematically tackled using a recursive design procedure. The strategy design aims to enhance robustness through Lyapunov stability-based mathematical analysis in the presence of considered perturbations. The ARSMC introduces new variables that depend on state variables, controlling parameters, and stabilizing functions to minimize unwanted signals and compensate for nonlinearities in the system. The paper's significant contribution is to improve the controlled output's rise time and stability time while ensuring efficient robustness.
引用
收藏
页数:19
相关论文
共 40 条
  • [1] Abbas N, 2022, CONTROL ENG APPL INF, V24, P13
  • [2] Real-time robust generalized dynamic inversion based optimization control for coupled twin rotor MIMO system
    Abbas, Nadir
    Pan, Xuejun
    Raheem, Abdur
    Shakoor, Rabia
    Arfeen, Zeeshan Ahmad
    Rashid, Muhammad
    Umer, Farhana
    Safdar, Nouman
    Liu, Xiaodong
    [J]. SCIENTIFIC REPORTS, 2022, 12 (01)
  • [3] Ahmad U., 2013, Intell. Control Autom, V4, P27843
  • [4] Nonlinear model identification and adaptive model predictive control using neural networks
    Akpan, Vincent A.
    Hassapis, George D.
    [J]. ISA TRANSACTIONS, 2011, 50 (02) : 177 - 194
  • [5] Biswas P, 2014, 2014 INTERNATIONAL CONFERENCE ON CONTROL, INSTRUMENTATION, ENERGY & COMMUNICATION (CIEC), P56, DOI 10.1109/CIEC.2014.6959049
  • [6] Bouffard P, 2012, IEEE INT CONF ROBOT, P279, DOI 10.1109/ICRA.2012.6225035
  • [7] Brogan W.L., 1991, MODERN CONTROL THEOR
  • [8] Bifurcation scenarios for pilot induced oscillations
    Bucolo, Maide
    Buscarino, Arturo
    Fortuna, Luigi
    Gagliano, Salvina
    [J]. AEROSPACE SCIENCE AND TECHNOLOGY, 2020, 106
  • [9] Evaluation of algorithms for linear and nonlinear PID control for Twin Rotor MIMO System
    Cajo, Ricardo
    Agila, Wilton
    [J]. 2015 ASIA-PACIFIC CONFERENCE ON COMPUTER-AIDED SYSTEM ENGINEERING - APCASE 2015, 2015, : 214 - 219
  • [10] Chaudhary Seema, 2019, 2019 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA). Proceedings, P746, DOI 10.1109/ICECA.2019.8821923