Trajectory tracking control of a coaxial rotor drone: Time-delay estimation-based optimal model-free fuzzy logic approach

Glida, Hossam Eddine; Chelihi, Abdelghani; Abdou, Latifa; Sentouh, Chouki; Perozzi, Gabriele

doi:10.1016/j.isatra.2022.12.015

Cited by 6 publications

(3 citation statements)

References 30 publications

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“…The coaxial HAUV is equipped with two propellers and a swash plant. The control force and torque generated by them can be expressed as follows [17,28,29]:…”

Section: Control Force and Momentmentioning

confidence: 99%

Adaptive Finite-Time Trajectory Tracking Control for Coaxial HAUVs Facing Uncertainties and Unknown Environmental Disturbances

Liao

Xing

et al. 2023

Applied Sciences

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In this paper, the problems of system design, dynamic modeling, and trajectory tracking control of coaxial hybrid aerial underwater vehicles (HAUVs) with time-varying model parameters and composite marine environment disturbances are investigated. It is clear that a stable transition between different media remains a challenge in the practical implementation of amphibious tasks. For HAUVs, accurate dynamic modeling to describe complex dynamic variations during vehicle takeoff from underwater to air is a huge challenge. Meanwhile, due to the rapid changes in model parameters and the external environment, vehicles are likely to fall into the sea during the cross-domain process. An integrated continuous dynamic model considering hydrodynamic changes is established by introducing a linear switching coefficient during the process of trans-medium motion. A nonsingular fast terminal sliding-mode control (NFTSMC) algorithm combined with adaptive technology is used to design the position and attitude of the controller. With no previous knowledge of external interferences and lumped uncertainties of the HAUV, the adaptive NFTSMC (ANFTSMC) algorithm achieves the control objectives; at the same time, the inherent chattering problems of sliding mode control (SMC) are weakened. The finite-time stability of the global system is proven strictly using a series of mathematical derivations based on Lyapunov theory. The effect of the controller applied is analyzed through a series of simulations with representative working conditions. The results show that the proposed ANFTSMC can realize a “seamless” air–water trans-medium process, which proves the superiority and robustness of the proposed control algorithm.

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“…The coaxial HAUV is equipped with two propellers and a swash plant. The control force and torque generated by them can be expressed as follows [17,28,29]:…”

Section: Control Force and Momentmentioning

confidence: 99%

Adaptive Finite-Time Trajectory Tracking Control for Coaxial HAUVs Facing Uncertainties and Unknown Environmental Disturbances

Liao

Xing

et al. 2023

Applied Sciences

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“…Using Newton-Euler formulation, the dynamic model with neglecting the external disturbances can be described as [34]…”

Section: Coaxial Rotor Helicopter Modellingmentioning

confidence: 99%

Optimal Model-Free Finite-Time Control Based on Terminal Sliding Mode for a Coaxial Rotor

Glida,

Sentouh,

Rath

2023

Drones

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This study focuses on addressing the tracking control problem for a coaxial unmanned aerial vehicle (UAV) without any prior knowledge of its dynamic model. To overcome the limitations of model-based control, a model-free approach based on terminal sliding mode control is proposed for achieving precise position and rotation tracking. The terminal sliding mode technique is utilized to approximate the unknown nonlinear model of the system, while the global stability with finite-time convergence of the overall system is guaranteed using the Lyapunov theory. Additionally, the selection of control parameters is addressed by incorporating the accelerated particle swarm optimization (APSO) algorithm. Finally, numerical simulation tests are provided to demonstrate the effectiveness and feasibility of the proposed design approach, which demonstrates the capability of the model-free control approach to achieve accurate tracking control even without prior knowledge of the system’s dynamic model.

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“…As the model of the controlled system becomes increasingly complex, model-based control algorithms become more and more difficult to design and to provide good performance. Thus, model-free control is gradually receiving much attention recently due to its modelindependent characteristics [18,19]. In the recent years, several model-free control methods that only rely on input and output system data have been developed, such as active disturbance rejection control [20,21], dynamiclinearization-based model free adaptive control [22,23], iterative learning control [24,25], etc.…”

Section: Introductionmentioning

confidence: 99%

Model-free fractional-order adaptive prescribed performance control for mechatronic systems with actuator failure

Tian

et al. 2023

Preprint

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In this paper, a model-free fractional-order adaptive prescribed performance controller (MFF-APPC) is designed for mechatronic systems in presence of uncertainties, external disturbances and actuator failure. The MFF-APPC is composed of ultra-local model (ULM)-based time-delay estimation (TDE), Proportional-Differential (PD) controller and fractional-order adaptive prescribed performance compensator (FAPPC). The ULM is utilized to approximate the complex mechatronic system in an extra-short sliding time window and TDE is employed to observe and eliminate the lumped disturbance. Then, PD controller is designed to stabilize the closed-loop system. Correspondingly, the TDE-based PD (TDE-PD) controller is constructed. However, there always exists estimation error under TDE technique and the tracking performance cannot be guaranteed. Hence, the FAPPC is designed and introduced into TDE-PD controller to eliminate the effect of estimation error on control performance and constrain the tracking error with prescribed convergence time and precision. Moreover, an adaptive parameter is designed to approximate the upper bound of estimation error in TDE and thus reduces the unwanted chattering on the switching manifold. Correspondingly, the MFF-APPC is constructed. Furthermore, the stability of closed-loop system under the proposed MFF-APPC is analyzed by using Lyapunov theorem. To validate the proposed method, the numerical simulation on 2-DOF robotic manipulator and co-simulation on virtual prototype of 7-DOF iReHave upper limb exoskeleton are completed. Through the compared simulation results with supervising switching technique based adaptive model-free controller (SST-AMFC) and robust fault tolerant controller (RFTC), the proposed strategy shows better trajectory tracking with prescribed performance.

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Trajectory tracking control of a coaxial rotor drone: Time-delay estimation-based optimal model-free fuzzy logic approach

Cited by 6 publications

References 30 publications

Adaptive Finite-Time Trajectory Tracking Control for Coaxial HAUVs Facing Uncertainties and Unknown Environmental Disturbances

Adaptive Finite-Time Trajectory Tracking Control for Coaxial HAUVs Facing Uncertainties and Unknown Environmental Disturbances

Optimal Model-Free Finite-Time Control Based on Terminal Sliding Mode for a Coaxial Rotor

Model-free fractional-order adaptive prescribed performance control for mechatronic systems with actuator failure

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