Designing adaptive robust extended Kalman filter based on Lyapunov-based controller for robotics manipulators

Ghiasi, Amir; Ghavifekr, Amir Aminzadeh; Hagh, Yashar Shabbouei; SeyedGholami, H.

doi:10.1109/icmsao.2015.7152248

Cited by 14 publications

(6 citation statements)

References 9 publications

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“…In the EKF, the state or parameter variables are propagated through the non-linear plant model analytically using the first-order Taylor series approximation [43] to compute the Jacobean of the system. In general, the EKF is applied for the simulation of nonlinear systems [44] and [45].…”

Section: ) Extended Kalman Filtermentioning

confidence: 99%

Physics-Based Digital Twins Merging With Machines: Cases of Mobile Log Crane and Rotating Machine

et al. 2022

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Real-world products and physics-based simulations are becoming interconnected. In particular, real-time capable dynamic simulation has made it possible for simulation models to run in parallel and simultaneously with operating machinery. This capability combined with state observer techniques such as Kalman filtering have enabled the synchronization between simulation and the real world. State estimator techniques can be applied to estimate unmeasured quantities, also referred as virtual sensing, or to enhance the quality of measured signals. Although synchronized models could be used in a number of ways, value creation and business model development are currently defining the most practical and beneficial use cases from a business perspective. The research reported here reveals the communication and collaboration methods that lead to economically relevant technology solutions. Two case examples are given that demonstrate the proposed methodology. The work benefited from the broad perspective of researchers from different backgrounds and the joint effort to drive the technology development towards business relevant cases.

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Section: ) Extended Kalman Filtermentioning

confidence: 99%

Physics-Based Digital Twins Merging With Machines: Cases of Mobile Log Crane and Rotating Machine

et al. 2022

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“…Therefore, their control is essential, especially in environments with disturbances that affect their correct operation. In [56], the use of AREKF (Adaptive Robust Extended Kalman Filter), which applies Lyapunov's discontinuous control theory and the EKF, is proposed. The algorithm is used to control a 2-DoF (Degrees of Freedom) manipulator robot, particularly to predict the position and speed of each joint, obtaining a performance superior to that of the EKF alone in the trajectory-tracking task suggested in the study.…”

Section: Applications Of the Kalman Filter In The Robotics Fieldmentioning

confidence: 99%

Kalman Filter: Historical Overview and Review of Its Use in Robotics 60 Years after Its Creation

Urrea

Agramonte

2021

Journal of Sensors

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Due to its widespread application in the robotics field, the Kalman filter has received increased attention from researchers. This work reviews some of the modifications conducted on to this algorithm over the last years. Problems such as the consistency, convergence, and accuracy of the filter are also dealt with. Sixty years after its creation, the Kalman filter is still used in autonomous navigation processes, robot control, and trajectory tracking, among other activities. The filter is not only restricted to robotics but is also present in different fields, such as economics and medicine. In addition, the characteristics of each modification on this filter are analyzed and compared.

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“…SMC is, to some extent, robust to matched disturbances but loses its nominal control performance in the presence of mismatched disturbances [20], [21]. Classical robust control design methods that consider an H 2 norm-bounded condition with approaches, such as the Lyapunov-based control [22], linear matrix inequality (LMI)-based approaches [23], intelligent control [24], [25], and adaptive methods [26] are quite effective in dealing with mismatched disturbances, however, they are restrictive to this type of disturbance. However, it is obvious that not all disturbances satisfy this condition.…”

Section: Introductionmentioning

confidence: 99%

Robust PI-Based Non-Singular Terminal Synergetic Control for Nonlinear Systems via Hybrid Nonlinear Disturbance Observer

2021

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This paper proposes a novel robust proportional integral non-singular terminal synergetic control (PI-NTSC) for a class of affine nonlinear systems. To counteract the effects of the disturbances, a hybrid nonlinear disturbance observer (HNDOB) scheme is proposed to estimate the matched and mismatched disturbances. A novel proportional integral non-singular terminal synergetic control (PI-NTSC) is proposed for a class of affine nth-order systems. The stability of the PI-NTSC approach is proven using the Lyapunov stability theory. Its effectiveness and applicability is evaluated through simulations of a four-bar linkage mechanism and a servo-hydraulic system. The proposed HNDOB-based PI-NTSC is characterized by a finite time convergence rate, simple implementation, better disturbance rejection ability to both matched and mismatched uncertainties, and chattering free dynamics compared to conventional sliding mode control.

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Designing adaptive robust extended Kalman filter based on Lyapunov-based controller for robotics manipulators

Cited by 14 publications

References 9 publications

Physics-Based Digital Twins Merging With Machines: Cases of Mobile Log Crane and Rotating Machine

Physics-Based Digital Twins Merging With Machines: Cases of Mobile Log Crane and Rotating Machine

Kalman Filter: Historical Overview and Review of Its Use in Robotics 60 Years after Its Creation

Robust PI-Based Non-Singular Terminal Synergetic Control for Nonlinear Systems via Hybrid Nonlinear Disturbance Observer

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