2020
DOI: 10.1109/access.2020.2977687
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Abstract: In this paper, we consider iterative learning control for trajectory tacking of robotic manipulator with uncertainty. An improved quadratic-criterion-based iterative learning control approach (Q-ILC) is proposed to obtain better trajectory tracking performance for the robotic manipulator. Besides of the position error information, which has been used in existing Q-ILC methods for robotic control, the velocity error information is also taken into consideration such that a new norm-optimal objective function is … Show more

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Cited by 12 publications
(4 citation statements)
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“…A further challenge is to ensure these controllers are continuous, to avoid chattering or exciting high-frequency dynamics that are not typically modeled [31], [32]. To handle parametric uncertainty, a variety of adaptive and sliding-mode control approaches have been proposed that prove both convergence and bounds on trajectory tracking error by simultaneously controlling a robot and estimating its uncertain parameters; such techniques were originally introduced in the 1980s and continue to be developed through the past decade [33]- [36].…”
Section: B Controlmentioning
confidence: 99%
See 1 more Smart Citation
“…A further challenge is to ensure these controllers are continuous, to avoid chattering or exciting high-frequency dynamics that are not typically modeled [31], [32]. To handle parametric uncertainty, a variety of adaptive and sliding-mode control approaches have been proposed that prove both convergence and bounds on trajectory tracking error by simultaneously controlling a robot and estimating its uncertain parameters; such techniques were originally introduced in the 1980s and continue to be developed through the past decade [33]- [36].…”
Section: B Controlmentioning
confidence: 99%
“…III-D is used to conservatively bound the truncation error. By using this property and the fact that all operations involving polynomial zonotopes are either exact or overapproximative, the polynomial zonotope forward kinematics can be computed similarly to the classical formulation (36) and proven to be overapproximative:…”
Section: B Reachable Set Constructionmentioning
confidence: 99%
“…This technique gives necessary and sufficient conditions to the design of robust quadratic filters. In Zhu et al (2020), the unscented Kalman filter (UKF) technique is employed for simultaneous estimation for uncertain parameters and system states. Adaptive control approaches have also been considered due to high efficiency in systems with parametric uncertainty.…”
Section: Introductionmentioning
confidence: 99%
“…For example, in the work of Luo et al (2020), a P-type and PI-type iterative learning control update law has been proposed for a nonlinear fractional order multi-agent system, which solves the problem of consensus tracking with fixed and iterative variable communication graphs. An improved iterative learning control method (Q-ILC) based on quadratic criterion has been developed in the work of Zhu et al (2020), which solves the trajectory tracking control problem of robot manipulators with uncertainties. Obviously, iterative learning control strategies have numerous practical applications in many fields such as power systems and mechanical systems.…”
Section: Introductionmentioning
confidence: 99%