Multi‐manipulators coordination for bilateral teleoperation system using fixed‐time control approach

Abstract

Summary In this paper, the fixed‐time synchronization control problem for bilateral teleoperation system composed of a single master manipulator and multiple cooperative slave manipulators with system uncertainties and external disturbances is addressed. The multiple cooperative slave manipulators have the capability to perform some complex tasks that are difficult or even impossible to be executed by a single slave manipulator. In order to control the multiple slave manipulators handling a common object with faster speed and higher accuracy, a new adaptive neural networks (NNs)–based fixed‐time control scheme is proposed. First, under the assumptions that the slave manipulators are rigidly grasping a nondeformable object, an integrated dynamic model composed of multiple slave manipulators and an object is derived. The object's grasping forces are concealed in the derived dynamics and can be controlled independent of the motion space. Then, a new nonsingular integral terminal sliding mode providing fixed‐time convergence of the velocity and position errors is designed with high‐degree terms and lower‐degree terms. By setting proper initial value of the integral function, the system settling time will be reduced greatly. Moreover, the corresponding adaptive NN‐based fixed‐time control approach is proposed by employing the strong approximation of the NNs. It is proved that the closed‐loop teleoperation system is semiglobally fixed‐time stable and the synchronization errors between the local manipulator and the object will converge to zero in fixed time for any initial condition of the master and the slaves. Finally, simulation and experiment are both performed to verify the effectiveness of the proposed method.

Adaptive Tracking Control for a Class of Uncertain Nonlinear Multi-Agent Systems With Input Quantization Based on Neural Approach

“…An example verifies the effectiveness of the presented protocol in the simulation part. In our future research, we may further consider some control issues such as finite-time control [44] and [51], observerbased output feedback control [52] and reliable control design for actuator faults [46].…”

“…More recently, synchronization control is addressed for bilateral teleoperation MASs. A fixed-time control strategy is developed in [44], which ensures semiglobally fixedtime stability of the closed-loop system and the convergence of synchronization errors. Adaptive synchronization control is also addressed in [45] for flexible telerobotics systems.…”

Neuro‐adaptive fixed‐time trajectory tracking control for human‐in‐the‐loop teleoperation with mixed communication delays

“…Substituting the proposed NAFT control algorithm (12)- (14) into the HIL teleoperation system (5) yields the following closedloop system:…”

Adaptive fuzzy finite‐time consensus tracking for multiple Euler‐Lagrange systems with unknown control directions

“…The consensus problem plays a significant role for distributed control of multiple ELSs. [4][5][6][7][8][9] Since the ELSs usually work in complex environment, the unknown parameters and disturbances can not be ignored, so how to overcome the influence brought by uncertain dynamics and disturbances such that the desired consensus can be guaranteed is a great challenge, and many control schemes have been proposed to achieve this objective. [10][11][12] He et al 11 considered the iterative learning control of ELS with distributed disturbances, and 12 studied the adaptive fuzzy control of multiple ELSs with constraint using impedance learning.…”

“…In recent years, the multiple Euler‐Lagrange systems (ELSs) have been received extensive attention because various practical systems can be described by them, such as the multiple robot manipulators, 1,2 multiple spacecraft systems, 3 and so on. The consensus problem plays a significant role for distributed control of multiple ELSs 4‐9 . Since the ELSs usually work in complex environment, the unknown parameters and disturbances can not be ignored, so how to overcome the influence brought by uncertain dynamics and disturbances such that the desired consensus can be guaranteed is a great challenge, and many control schemes have been proposed to achieve this objective 10‐12 .…”