Identification with non-parametric uncertainty

2002 ◽  
Author(s):  
R.C. Younce ◽  
C.E. Rohrs
Keyword(s):  
Parametric Uncertainty ◽  
Non Parametric

On the Taylor series asymptotic tracking control of robots

Robotica ◽  
2018 ◽  
Vol 37 (3) ◽  
pp. 405-427 ◽  
Author(s):  
Seyed Mohammad Ahmadi ◽  
Mohammad Mehdi Fateh
Keyword(s):  
Taylor Series ◽  
Tracking Control ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Parametric Uncertainty ◽  
Series System ◽  
Control Methods ◽  
Asymptotic Tracking ◽  
Modelling Error ◽  
Non Parametric

SUMMARYAchieving the asymptotic tracking control of electrically driven robot manipulators is a challenging problem due to approximation/modelling error arising from parametric and non-parametric uncertainty. Thanks to the specific property of Taylor series systems as they are universal approximators, this research outlines two robust control schemes using an adaptive Taylor series system for robot manipulators, including actuators' dynamics. First, an indirect adaptive controller is designed such as to approximate an uncertain continuous function by using a Taylor series system in the proposed control law. Second, a direct adaptive scheme is established to employ the Taylor series system as a controller. In both controllers, not only a robustifying term is constructed using the estimation of the upper bound of approximation/modelling error, but the closed-loop stability, as well as the asymptotic convergence of joint-space tracking error and its time derivative, is ensured. Due to the design of the Taylor series system in the tracking error space, our technique clearly has an advantage over fuzzy and neural network-based control methods in terms of the small number of tuning parameters and inputs. The proposed methods are simple, model free in decentralized forms, no need for uncertainty bounding functions and perfectly capable of dealing with parametric and non-parametric uncertainty and measurement noise. Finally, simulation results are introduced to confirm the efficiency of the proposed control methods.

Non Holonomic Collision Avoidance under Non-Parametric Uncertainty: A Hilbert Space Approach

2021 ◽  
Author(s):  
Unni Krishnan R Nair ◽  
Anish Gupta ◽  
D. A. Sasi Kiran ◽  
Ajay Shrihari ◽  
Vanshil Shah ◽  
...  
Keyword(s):  
Hilbert Space ◽  
Collision Avoidance ◽  
Parametric Uncertainty ◽  
Space Approach ◽  
Non Parametric

Detection of a Chirp Ionosonde Signal under Conditions of a Priori Non-Parametric Uncertainty

2020 ◽  
Vol 62 (10) ◽  
pp. 685-693
Author(s):  
I.A. Egoshin ◽  
A. A. Kolchev ◽  
A. E. Nedopekin
Keyword(s):  
A Priori ◽  
Parametric Uncertainty ◽  
Non Parametric

Controller Verification Under Non-Parametric Uncertainty

1994 ◽  
Vol 27 (2) ◽  
pp. 315-320 ◽  
Author(s):  
E. Gazi ◽  
W.D. Seider ◽  
L.H. Ungar
Keyword(s):  
Parametric Uncertainty ◽  
Non Parametric

Event-triggered adaptive control of a class of nonlinear systems with non-parametric uncertainty in the presence of actuator failures

2021 ◽  
pp. 014233122110025
Author(s):  
H.R. Ghazisaeedi ◽  
M.S. Tavazoei
Keyword(s):  
Nonlinear Systems ◽  
Control Method ◽  
Parametric Uncertainty ◽  
Control Input ◽  
Actuator Faults ◽  
Adaptive Tracking Control ◽  
Actuator Failures ◽  
Unknown Control ◽  
Event Triggered ◽  
Non Parametric

This paper deals with event-triggered adaptive tracking control of a class of nonlinear systems with non-parametric uncertainty and unknown control input direction, in the presence of actuator faults. The proposed event-triggered control method takes advantage of the radial basis function neural networks to approximate the non-parametric uncertainties. Moreover, this control method benefits from the Nussbaum-type function-based adaptation laws for simultaneously dealing with unknown input direction and actuator faults. Numerical simulation results confirm the efficiency of the proposed control method to confront the above mentioned limitations.

scholarly journals Reactive Navigation Under Non-Parametric Uncertainty Through Hilbert Space Embedding of Probabilistic Velocity Obstacles

2020 ◽  
Vol 5 (2) ◽  
pp. 2690-2697
Author(s):  
SriSai Naga Jyotish Poonganam ◽  
Bharath Gopalakrishnan ◽  
Venkata Seetharama Sai Bhargav Kumar Avula ◽  
Arun Kumar Singh ◽  
K. Madhava Krishna ◽  
...  
Keyword(s):  
Hilbert Space ◽  
Parametric Uncertainty ◽  
Reactive Navigation ◽  
Non Parametric
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