Tracking control using optimal discrete-time <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e192" altimg="si194.svg"><mml:msub><mml:mrow><mml:mi>H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:math> for mechanical systems: Applied to Robotics

Osuna-Ibarra, Linda Patricia; Caballero-Barragán, H.; Loukianov, Alexander G.; Bayro–Corrochano, Eduardo

doi:10.1016/j.robot.2019.07.005

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…Additional controllers were reviewed such as the H-inf controller 25 which is used as an optimal control theory that achieves stabilization with a perfectly adequate performance by reducing the gain parameter, that is the result of minimizing the closed loop system. The non-linear system is linearized by figuring the system’s jacobian matrices.…”

Section: Related Workmentioning

confidence: 99%

Fuzzy predictive Stanley lateral controller with adaptive prediction horizon

Abdelmoniem

Ali

Taher

et al. 2023

Measurement and Control

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The challenge of trajectory tracking of autonomous vehicles (AVs) is a critical aspect that must be effectively addressed. Recent studies are concerned with maintaining the yaw stability to guarantee the customers’ comfort throughout the journey. Most of the geometrical controllers solve this task by dividing it into consecutive point stabilization problems, limiting the controllers’ ability to handle sudden trajectory changes. One research presented a predictive Stanley lateral controller that uses a discrete prediction model to mimic human behavior by anticipating the vehicle’s future states. That controller is limited in its use, as the parameters must be manually tuned for every change in the maneuver or vehicle velocity. This article presents a novel approach for trajectory tracking in autonomous vehicles, by introducing a fuzzy supervisory controller that automatically adapts to changes in the vehicle’s velocity and maneuver by estimating the prediction horizon’s length and providing different weights for each controller. The proposed method overcomes the limitations of traditional controllers that require manual tuning of parameters, making it ready for real-world experiments. This is the main contribution of the research in this paper. The suggested technique demonstrated an advantage over the Basic Stanley controller and the manually tuned predictive Stanley controller in terms of the total lateral error and the model predictive control (MPC) in terms of computational time. The performance is determined by performing various simulations on V-Rep and hardware-in-the-loop (HIL) experiments on an E-CAR golf bus. A broad selection of velocities is used to validate the behavior of the vehicle while working on different maneuvers (double lane change, hook road, S road, and curved road).

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Section: Related Workmentioning

confidence: 99%

Fuzzy predictive Stanley lateral controller with adaptive prediction horizon

Abdelmoniem

Ali

Taher

et al. 2023

Measurement and Control

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“…This limitation will be relaxed in this section. In this regard, the Lipschitz continuous condition Σeq ≤ σ with a known Lipschitz constant σ is considered [4,8]. This condition may often exist in many real-life systems [2].…”

Section: Disturbance Observer-based Finite-time Tracking Control Designmentioning

confidence: 99%

“…The problem of position tracking in uncertain robotic manipulators is a well-known topic over the last years, especially in the presence of external disturbances [1][2][3][4][5][6][7]. Many tracking approaches provide asymptotic or exponential convergence (convergence of tracking errors in an infinite time).…”

Section: Introductionmentioning

confidence: 99%

Non-linear Finite-Time Tracking Control of Uncertain Robotic Manipulators Using Time-Varying Disturbance Observer-Based Sliding Mode Method

Razmjooei

Shafiei

Palli

et al. 2022

J Intell Robot Syst

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In this paper, a time-varying chattering-free disturbance observer-based position tracking control law of serial robotic manipulators is presented to track a reference signal in a finite time. The key idea is to employ a positive-increasing function associated with the control/observer objectives to improve the control performance. First, the model of an uncertain robotic manipulator is presented as the case study of the proposed strategy. Then, the time-varying form of the robotic manipulator model is obtained to provide finite-time boundedness using the first-order sliding mode method. Moreover, without any knowledge about the upper bounds of the uncertainties, a reduced-order observer is presented to estimate the uncertainties in a finite time. Subsequently, a disturbance observer-based finite-time position tracking control law is designed. The time-varying gains are provided to converge the position tracking error to a neighborhood of zero in a finite time. Finally, comparative simulations are presented to show the effectiveness of the proposed scheme compared to other existing strategies.

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Research on composite anti-disturbance adaptive constraint control strategy for quadruped robot

Gong,

Yang,

Yuan

et al. 2024

Transactions of the Institute of Measurement and Control

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To achieve the stable walking of a quadruped robot, a composite anti-disturbance adaptive constraint control strategy is proposed based on the analysis of the dynamic model. First, the leg control adopts a trajectory tracking constraint control algorithm based on a time-varying tangent-type barrier Lyapunov function, which ensures high-precision control with joint trajectory tracking errors consistently constrained within a time-varying boundary. To further enhance the robustness of the system, an adaptive algorithm is used to compensate for external disturbances and system uncertainties. Second, the body posture control of the quadruped robot adopts the Virtual Model Control algorithm, which achieves stable adjustments of the body posture and soft contact between the foot end and the ground. This further improves its disturbance rejection capability. Finally, a comparative study of control algorithms is being conducted using MATLAB/Simulink. The results show that under this control strategy, the quadruped robot’s motion exhibits good robustness and flexibility.

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Tracking control using optimal discrete-time H∞ for mechanical systems: Applied to Robotics

Cited by 4 publications

References 13 publications

Fuzzy predictive Stanley lateral controller with adaptive prediction horizon

Fuzzy predictive Stanley lateral controller with adaptive prediction horizon

Non-linear Finite-Time Tracking Control of Uncertain Robotic Manipulators Using Time-Varying Disturbance Observer-Based Sliding Mode Method

Research on composite anti-disturbance adaptive constraint control strategy for quadruped robot

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