Predefined‐time control of cooperative manipulators

Abstract

A cooperative controller that enforces an exact sliding motion in predefined-time, assuring cooperativeness, and stable manipulation, is proposed in this article. Alternatively, a continuous controller is also proposed, which induces in predefined-time that a hybrid force/position error converges into a predefined-bounded vicinity of the origin. Numerical simulations highlight the effectiveness of the proposed scheme.

Adaptive predefined‐time observer design for generalized strict‐feedback second‐order systems under perturbations

“…Recently, predefined‐time stability (PTS) has emerged as an upgrade of finite‐time stability and fixed‐time stability (FxTS) due to its concise and explicit relationship between the UBST and design parameters, 36 which endows PTS with high practical application value under time‐critical scenarios. Fruitful efforts have been put into controller designs with PTS, such as References 36‐39. However, attempts to incorporate PTS into observing states and perturbations are rare.…”

Observer‐based adaptive control of cooperative multiple manipulators using the Mastroianni operators as uncertainty approximator

“…For example, high speed and accuracy make industrial manipulators widely used in the production processes. With the advancement of technology and the need to increase the quality of products, cooperating robots, including arms, mobile robots, or UAVs, have become the center of attention 1–4 . Performing industrial tasks such as welding, transportation, painting, packaging, and assembly require high maneuverability, so they can not be done by a single robot and require the use of a team of robots.…”

“…With the advancement of technology and the need to increase the quality of products, cooperating robots, including arms, mobile robots, or UAVs, have become the center of attention. [1][2][3][4] Performing industrial tasks such as welding, transportation, painting, packaging, and assembly require high maneuverability, so they can not be done by a single robot and require the use of a team of robots. On the other hand, increasing the number of robots raises the system complexity and challenges their control.…”

“…The motivation of adopting FAT-based approaches for designing the structure is the significant advantages of these approaches compared to both model-based and model-free neuro-fuzzy methods, which make them good candidates for dealing with disturbances and uncertainties. 21 These advantages are as follows: (1) In model-based control methods, change of parameters may affect the system performance significantly. Compared to these approaches, FAT-based methods are not dependent on system modeling.…”

“…Finally, to evaluate the efficiency of the proposed adaptive FAT-based method, it is applied to two 3-degree-of-freedom (DOF) robotic arms carrying a payload. The novelty and merits of the presented method are as follows: (1) To the best of the authors' knowledge, the present article is the first usage of Mastroianni operator in robust adaptive control of cooperative multiple manipulators; (2) The polynomial coefficients are adjusted using the adaptation law achieved in the stability analysis, while in previous related studies, the adaptive form of the Mastroianni Operator is not used; (3) The introduced controller is regressor-free. So, the problems of the usual adaptive methods do not appear in the proposed controller; (4) One of the advantages of the developed strategy is that there is no need to measurement of joint velocity, and joint position is the only measured state;…”