Adaptive Attitude Control for Foldable Quadrotors

Patnaik, Karishma; Zhang, Wenlong

doi:10.1109/lcsys.2023.3234045

Cited by 8 publications

(2 citation statements)

References 19 publications

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“…Two adaptive control laws were designed for the attitude stabilization of a quadrotor in order to deal with the problem of parametric uncertainty and external disturbance [18]. A robust adaptive control strategy was developed for tracking the attitude of foldable quadrotors, which were modeled as switched systems [19].…”

Section: Introductionmentioning

confidence: 99%

Deep Deterministic Policy Gradient (DDPG) Agent-Based Sliding Mode Control for Quadrotor Attitudes

Hu,

Yang,

Liu

2024

Drones

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A novel reinforcement deep learning deterministic policy gradient agent-based sliding mode control (DDPG-SMC) approach is proposed to suppress the chattering phenomenon in attitude control for quadrotors, in the presence of external disturbances. First, the attitude dynamics model of the quadrotor under study is derived, and the attitude control problem is described using formulas. Second, a sliding mode controller, including its sliding mode surface and reaching law, is chosen for the nonlinear dynamic system. The stability of the designed SMC system is validated through the Lyapunov stability theorem. Third, a reinforcement learning (RL) agent based on deep deterministic policy gradient (DDPG) is trained to adaptively adjust the switching control gain. During the training process, the input signals for the agent are the actual and desired attitude angles, while the output action is the time-varying control gain. Finally, the trained agent mentioned above is utilized in the SMC as a parameter regulator to facilitate the adaptive adjustment of the switching control gain associated with the reaching law. The simulation results validate the robustness and effectiveness of the proposed DDPG-SMC method.

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Section: Introductionmentioning

confidence: 99%

Deep Deterministic Policy Gradient (DDPG) Agent-Based Sliding Mode Control for Quadrotor Attitudes

Hu,

Yang,

Liu

2024

Drones

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“…In an effort to overcome the limitations of linear control methods, nonlinear control techniques have been widely shown to achieve an increased level of reliability in quadrotor flight under various uncertain and adversarial operating conditions. Common nonlinear control design approaches include feedback linearization [8], [9], backstepping [10], [11], [12], adaptive control [13], [14] and robust control [15], [16], [17]. Advantages to feedback linearization include mathematical simplicity and easy implementation; however, they often incur reduced robustness to disturbances and sensitivity to model uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Modified RISE-based Quadrotor Trajectory Tracking with Actuator Uncertainty Compensation

Kidambi¹,

Tiwari²,

Ijoga³

et al. 2023

Preprint

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This paper presents an adaptive robust nonlinear control method, which achieves reliable trajectory tracking control for a quadrotor unmanned aerial vehicle in the presence of gyroscopic effects, rotor dynamics, and external disturbances. Through novel mathematical manipulation in the error system development, the quadrotor dynamics are expressed in a control-oriented form, which explicitly incorporates the uncertainty in the gyroscopic term and control actuation term. An adaptive robust nonlinear control law is then designed to stabilize both the position and attitude loops of the quadrotor system. A rigorous Lyapunov-based analysis is utilized to prove asymptotic trajectory tracking, where the region of convergence can be made arbitrarily large through judicious control gain selection. Moreover, the stability analysis formally addresses gyroscopic effects and actuator uncertainty. To illustrate the performance of the control law, comparative numerical simulation results are provided, which demonstrate the improved closed-loop performance achieved under varying levels of parametric uncertainty and disturbance magnitudes.

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