Adaptive model predictive control with extended state observer for <scp>multi‐UAV</scp> formation flight

Zhang, Boyang; Sun, Xiaodong; Deng, Xiongfeng

doi:10.1002/acs.3145

Cited by 26 publications

(12 citation statements)

References 39 publications

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“…MPC trajectory tracking performance evaluation index.Figure15 and Fig.16show that MPC, MPC with KF, and MPC with AKF have similar linear tracking performances.From Fig.15, we know MPC with AKF's trajectory is closer to the reference trajectory during first curving tacking. The tracking performance of MPC with AKF is a litter better than that of MPC and MPC with KF.From Fig.15and Fig.16, we know that after obstacle avoidance, compared to the MPC, MPC with KF and MPC with AKF's trajectories are even more deviated.…”

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confidence: 82%

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MPC Based Trajectory Tracking for An Automonous Deep-Sea Tracked Mining Vehicle

Chen

Qin

2021

ASP trans. Internet things

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Model predictive control (MPC) has been successfully used in trajectory tracking for autonomous vehicles based on certain kinematic model under low external disturbance conditions, but when there are model uncertainties and external disturbances, autonomous vehicles will fail to follow the pre-set trajectory. This paper studies trajectory tracking control based on MPC for an autonomous deep-sea tracked mining vehicle in polymetallic nodule mines with model uncertainty and external disturbances. A MPC algorithm is designed for trajectory tracking. To address model uncertainties caused by vehicle body subsidence and track slippage, a drive wheel speed correction controller is designed by experimental data fitting, and Kalman filtering (KF) and adaptive Kalman filtering (AKF) are introduced to improve tracking performance by rejecting external disturbances especially during curve tracking. To handle dead zones and obstacles during actual operation, an obstacle avoidance strategy is proposed that uses the tri-circular arc obstacle avoidance trajectory with an equal curvature for path re-planning. Finally, Simulink&Recurdyn co-simulations validate the performance of the proposed MPC controller through a comparison with nonlinear MPC(NMPC).

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confidence: 82%

“…To address model uncertainties in AUV trajectory tracking, an adaptive model predictive controller was designed in [15] with an extended system observer. Compared to traditional MPC, the proposed method improved trajectory tracking accuracy under the premise of stable algorithm convergence.…”

Section: Introductionmentioning

confidence: 99%

MPC Based Trajectory Tracking for An Automonous Deep-Sea Tracked Mining Vehicle

Chen

Qin

2021

ASP trans. Internet things

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“…Zhang et al proposed an adaptive model predictive control with extended state observers to deal with multiple unmanned aerial vehicle formation flight in presence of external disturbances and system uncertainties (Zhang et al, 2020). Shi et al proposed an active anti-disturbance control strategy based on generalized extended state observer for a quadrotor.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrated design of fault-tolerant control for flight control systems using observer and fuzzy logic

Unal

2021

AEAT

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Purpose Fault detection, isolation and reconfiguration of the flight control system is an important problem to obtain healthy flight. This paper aims to propose an integrated approach for aircraft fault-tolerant control. Design/methodology/approach The integrated structure includes a Kalman filter to obtain without noise, a full order observer for sensor fault detection, a GOS (generalized observer scheme) for sensor fault isolation and a fuzzy controller to reconfigure of the healthy sensor. This combination is simulated using the state space model of a lateral flight control system in case of disturbance and under sensor fault scenario. Findings Using a dedicated observer scheme, the detection and time of sensor fault are correct, but the sensor fault isolation is evaluated incorrectly while the faulty sensor is isolated correctly using GOS. The simulation results show that the suggested approach works affectively for sensor faults with disturbance. Originality/value This paper proposes an integrated approach for aircraft fault-tolerant control. Under this framework, three units are designed, one is Kalman filter for filtering and the other is GOS for sensor fault isolation and another is fuzzy logic for reconfiguration. An integrated approach is sensitive to faults that have disturbances. The simulation results show the proposed integrated approach can be used for any linear system.

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“…More recently, Zhang et al 23 proposed a parameter estimation strategy by utilizing the recursive least squares (RLS) algorithm, which was employed in the construction of homothetic tube MPC. Additionally, Zhang et al 24 developed an adaptive MPC methodology with extended state observers (ESO) to apply to flight control. By introducing the gradient descent methodology, Zhu et al 25 proposed an adaptive MPC algorithm for discrete-time linear systems with parametric uncertainties.…”

Section: Introductionmentioning

confidence: 99%

An adaptive model predictive control strategy for a class of discrete‐time linear systems with parametric uncertainty

Gou

Ding

et al. 2021

Adaptive Control & Signal

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In this study, an adaptive model predictive control (MPC) strategy is proposed for a class of discrete-time linear systems with parametric uncertainty. In the presented adaptive MPC, an updating law is firstly designed to update the estimated parameters online. By utilizing the estimated parameters, a standard MPC optimization problem for unconstrained systems is established. Then, to deal with constrained systems, the min-max MPC technique is developed under the set-based approach for the estimated parameters. Furthermore, it is shown theoretically that the recursive feasibility and closed-loop stability can be rigorously proved, respectively. Finally, numerical simulations and comparative analysis are presented to illustrate the superiority of the proposed algorithms in control performance.

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Adaptive model predictive control with extended state observer for multi‐UAV formation flight

Cited by 26 publications

References 39 publications

MPC Based Trajectory Tracking for An Automonous Deep-Sea Tracked Mining Vehicle

MPC Based Trajectory Tracking for An Automonous Deep-Sea Tracked Mining Vehicle

Integrated design of fault-tolerant control for flight control systems using observer and fuzzy logic

An adaptive model predictive control strategy for a class of discrete‐time linear systems with parametric uncertainty

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