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The purpose of this paper is to design a new compliant motion/force control strategy for robotic manipulators with environmental constraints in the sense of fixed-time stability.

This paper investigates a novel compliant motion/force control strategy for robotic manipulators with environmental constraints. By using the Lyapunov theory and fixed-time stability theory, a non-singular terminal sliding mode manifold is first established. Then, the compliant motion/force controller is designed, and relevant conditions are given for guaranteeing that the robotic manipulator can track the prescribed constrained trajectory while exerting a desired force to the environment in fixed-time. An illustrative example is presented to show the effectiveness of our proposed control strategy.

Based on fixed-time stability theory, the desired compliant motion/force controller for robotic manipulators with environmental constraints is developed.

Compared with most existing literature, the proposed fixed-time compliant motion/force control strategy can provide the upper bound of the settling time independent of the initial conditions in designing procedure and is more practical for the real-world applications.

This paper aims to present a fully actuated aerial manipulator (AM) with a robust motion/force hybrid controller for conducting contact-typed inspection tasks in industrial plants.

An AM is designed based on a hexarotor with tilted rotors and a rigidly attached end effector. By tilting the rotors, the position and attitude of the AM can be controlled independently, and the AM can actively exert forces on industrial facilities through the rigidly attached end effector. A motion/force hybrid controller is proposed to perform contact-typed inspection tasks. The contact-typed inspection task is divided into the approach phase and the contact phase. In the approach phase, the AM automatically approaches the contact surface. In the contact phase, a motion/force hybrid controller is used for contact-typed inspection. Finally, a disturbance observer (DOB) is used to estimate external disturbances and used as feedforward compensation.

The proposed AM can slowly approach the contact surface without significant impact in the contact phase. It can realize constant force control in the direction normal to the contact surface in the contact phase, whereas the motion of the remaining directions can be controlled by the operator. The use of the DOB ensures the robustness of the AM in the presence of external wind disturbances.

A fully actuated AM system with a robust motion/force hybrid controller is proposed. The effectiveness of the proposed AM system for conducting contact-typed industrial inspection tasks is validated by practical experiments.

This paper aims to describe how a novel biomimetic chewing robot was designed, including its motion, force, control and mechanical designs, and shows some initial experiments about motion tracking.

According to the biomechanics, the authors modeled the muscles of mastication in six linkages and the temporomandibular joint in higher kinematic pairs of point contact. As a result, the chewing robot was represented in a redundantly actuated parallel mechanism. With reference to literature data on the biological system, the authors specified the motion and force requirements for the robot via inverse kinematics and force analysis. A prototype of the robot was built, which has a position control system and is driven by six linear actuators. Experiments were conducted to show the capability of the robot in reproducing the human chewing motion.

A chewing robot was successfully modeled and developed, which is able to simulate the motion of human mastication in a biologically faithful way.

The chewing robot as a scientific instrument can be used to test dental materials and evaluate food textural properties of chewing.

Two higher kinematic pairs of point contact are proposed to simulate the two temporomandibular joints. The mechanism of the novel chewing robot is the first of this kind, which has two higher kinematic pairs of point contact and is a redundantly actuated spatial parallel mechanism.

The purpose of this paper is to improve the flexibility and tracking errors of the controllers-based neural networks (NNs) for mobile manipulator robot (MMR) in the presence of time-varying uncertainties.

The conventional backstepping force/motion control is developed by the wavelet fuzzy CMAC neural networks (WFCNNs) (for mobile-manipulator robot). The proposed WFCNNs are applied in the tracking-position-backstepping controller to deal with the uncertain dynamics of the controlled system. In addition, an adaptive robust compensator is proposed to eliminate the inevitable approximation errors, uncertain disturbances, and relax the requirement for prior knowledge of the controlled system. Besides, the position tracking controller, an adaptive robust constraint-force is also considered. The online-learning algorithms of the control parameters (WFCNNs, robust term and constraint-force controller) are obtained by using the Lyapunov stability theorem.

The design of the proposed method is determined by the Lyapunov theorem such that the stability and robustness of the control-system are guaranteed.

The WFCNNs are more the generalized networks that can overcome the constant out-weight problem of the conventional fuzzy cerebellar model articulation controller (FCMAC), or can converge faster, give smaller approximation errors and size of networks in comparison with FNNs/NNs. In addition, an intelligent-control system by inheriting the advantage of the conventional backstepping-control-system is proposed to achieve the high-position tracking for the MMR control system in the presence of uncertainties variation.

In aircraft wing–fuselage assembly, the distributed multi-point support layout of positioners causes fuselage to deform under gravity load, leading to assembly difficulty and assembly stress. This paper aims to propose a hybrid force position control method to balance aerodynamic shape accuracy and deformation of assembly area, thereby correcting assembly deformation and reducing assembly stress.

Force and position control axes of positioners are selected based on screw theory and ellipsoid method. The position-control axes follow the posture trajectory to align the fuselage posture. To exert force on the fuselage and correct the deformations, the force-control axes follow the contact force derived by using orthogonal experiments and partial least squares regression (PLSR). Finite element simulation and one-dimension deformation correction experiment are conducted to verify the validity of this method.

Simulation results indicate that hybrid force position control method can correct assembly deformation and improve the wing–fuselage assembly quality significantly. Experiment on specimen verifies the effect of this method indirectly.

The proposed method gives a solution to solve the deformation problem during aircraft wing-fuselage assembly, thereby reducing assembly stress and improving assembly quality.

The purpose of this paper is to present the radial basis function (RBF) networks‐based adaptive robust control for an omni‐directional wheeled mobile manipulator in the presence of uncertainties and disturbances.

First, a dynamic model is obtained based on the practical omni‐directional wheeled mobile manipulator system. Second, the RBF neural network is used to identify the unstructured system dynamics directly due to its ability to approximate a nonlinear continuous function to arbitrary accuracy. Using the learning ability of neural networks, RBFNARC can co‐ordinately control the omni‐directional mobile platform and the mounted manipulator with different dynamics efficiently. The implementation of the control algorithm is dependent on the sliding mode control.

Based on the Lyapunov stability theory, the stability of the whole control system, the boundedness of the neural networks weight estimation errors, and the uniformly ultimate boundedness of the tracking error are all strictly guaranteed.

In this paper, an adaptive robust control scheme using neural networks combined with sliding mode control is proposed for crawler‐type mobile manipulators in the presence of uncertainties and disturbances. RBF neural networks approximate the system dynamics directly and overcome the structured uncertainty by learning. Based on the Lyapunov stability theory, the stability of the whole control system, the boundedness of the neural networks weight estimation errors, and the uniformly ultimate boundedness of the tracking error are all strictly guaranteed.

This study attempts to control the movement of industrial robots with virtual and real-time variable time delay. The improved variable wave method was used for analyzing position tracking performance and stability of the system.

This study consists of both theoretical and real-time operations. Teleoperation systems that provide information about point or environment that people cannot reach and are one of the important robotic works that include the human–machine interaction technology were used to obtain the necessary data. Robots, as the simulated virtual environment to achieve real behaviors, were found to be important for the identification of damage that may occur during the tests performed by real robots and then in terms of prevention of errors identified in algorithm development stages.

The position and speed controls of the real–virtual–real robots consist of the teleoperation system. Also, in this study, the virtual environment was created; variable time delay motion control with teleoperation was performed and applied in the simulation and real-time environment; and the performance results were analyzed.

The teleoperation system created in the laboratory consists of a six-degree-of-freedom (dof) master robot, six-dof industrial robot and six-dof virtual robot. A visual interface is designed to provide visual feedback of the virtual robot’s movements to the user.

The purpose of this paper is to propose an adaptive control for a redundant robot manipulator interacting physically with the environment, especially with the existence of humans, on its body.

The redundant properties of the robot manipulator are used and a reference velocity variable is introduced to unify the operation-space tracking control and the null-space impedance control under one common framework. Neural networks are constructed to deal with unstructured and unmodeled dynamic nonlinearities. Lyapunov function is used during the course of control design and simulation studies are carried out to further illustrate the effectiveness of the proposed strategies.

Satisfying tracking performance in the operation-space and compliance behavior in the null-space of the redundant robot manipulator are ensured simultaneously.

The design procedure of redundant robot manipulators control can be greatly simplified, and the framework of multi-priority control can be transformed into a joint-space velocity tracking problem via the introducing of a reference velocity variable.

The purpose of this paper is to improve control performance and safety of a real two-wheeled inverted pendulum (TWIP) robot by dealing with model uncertainty and motion restriction simultaneously, which can be extended to other TWIP robotic systems.

The inequality of lumped model uncertainty boundary is derived from original TWIP dynamics. Several motion restriction conditions are derived considering zero dynamics, centripedal force, ground friction condition, posture stability, control torque limitation and so on. Sliding-mode control (SMC) and model predictive control (MPC) are separately adopted to design controllers for longitudinal and rotational motion, while taking model uncertainty into account. The reference value of the moving velocity and acceleration, delivered to the designed controller, should be restricted in a specified range, limited by motion restrictions, to keep safe.

The cancelation of model uncertainty commonly existing in real system can improve control performance. The motion commands play an important role in maintaining safety and reliability of TWIP, which can be ensured by the proposed motion restriction to avoid potential movement failure, such as slipping, lateral tipping over because of turning and large fluctuation of body.

An inequation of lumped model uncertainty boundary incorporating comprehensive errors and uncertainties of system is derived and elaborately calculated to determine the switching coefficients of SMC. The motion restrictions for TWIP robot moving in 3D are derived and used to impose constraints on reference trajectory to avoid possible instability or failure of movement.

Whereas a combination of unique historical conditions and a specific set of public policies in the United States enabled labor to significantly increase its relative power during the quarter century following World War II, this halcyon period for labor was followed by a period of over two decades during which labor's relative status and power declined. This paper explores this reversal of fortunes.

Although the current plight of labor has been extensively studied within the discipline of economics, these studies have typically focused upon specific aspects of labor's declining status. In this study, labor's plight is examined within the larger context of the institutions and dynamics of capitalism as a socio‐economic system. Within this broadened context, an exploration is made of whether the sustained period of progress for American labor set in motion the creation of forces that eventually led to reversal.

Labor's relative successes in the quarter century following World War II encouraged behavior that enabled the interests of capital to politically legitimate policies that, combined with trends in international trade and technology, served to decrease the relative power and welfare of labor.

Further research is needed to determine whether there are other instances of a dynamic whereby labor's successes set in motion forces that lead to reversal.

This study emphasizes the importance of a broaden institutional focus for grasping important economic changes in society.