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Friction Stir Welding-Based Additive Manufacturing Techniques
Published in Sandeep Rathee, Manu Srivastava, Sachin Maheshwari, T. K. Kundra, Arshad Noor Siddiquee, Friction Based Additive Manufacturing Technologies, 2018
Sandeep Rathee, Manu Srivastava, Sachin Maheshwari, T. K. Kundra, Arshad Noor Siddiquee
In the steady state, at constant levels of rotational and traverse rate, a change in plunge depth by even a fraction of a millimeter may change the axial force by several thousand Newtons. A variation in plunge depth during the transient state may, however, result in an exceptionally high change in axial force, even three to five times greater than an equal change in the steady state. Because of this typical nature of axial force, robotic FSW/P systems must always be operated under force-controlled mode, as robotic systems are constrained by being compliant and possessing limited load capacity. Incidentally, FSAM along a complex 3D path must be performed by a robotic system, and a sound joining needs accurate position control, whereas the system is of the force-control type. Under such conditions, the axes and arms of the robotic system may undergo deflections, causing undesirable force and positional variations and making robotic FSW/P process control a challenge. In force-controlled systems, a force sensor continuously senses the force at the tool and supplies feedback to the machine's controller. When the force deviates from a preset value, the change is sensed and feedback is sent to the controller, which adjusts the position of the tool to keep the force constant. Generally, force-control mode provides greater flexibility in accommodating part material, part geometry, and tool path, as all these changes are manifested through a change in force.
Control and Manipulation
Published in Marina Indri, Roberto Oboe, Mechatronics and Robotics, 2020
Bruno Siciliano, Luigi Villani
Force control techniques are employed also in medical robotics, haptic systems, telerobotics, humanoid robotics, and micro and nano robotics. An interesting field of application is related to human-centered robotics, where control plays a key role in achieving adaptability, reaction capability, and safety. Robots and biomechatronic systems based on the novel variable impedance actuators, with physically adjustable compliance and damping, capable of reacting softly when touching the environment, necessitate the design of specific control laws [39]. The combined use of exteroceptive sensing (visual, depth, proximity, force, and tactile sensing) for reactive control in the presence of uncertainty represents another challenging research direction [28].
Control of Robots and Manipulators
Published in William S. Levine, Control System Applications, 2018
Mark W. Spong, Joris De Schutter, Herman Bruyninckx, John Ting-Yung Wen
Control. The aim of the force control system is to make the actual contact forces, as measured by the sensor, equal to the desired contact forces, given by the task specification. This is called low- level or setpoint control, which is the main topic of this chapter. However, by interpreting the velocities actually executed by the robot, as well as the measured contact forces, much can be learned about the actual geometry of the constraints. This is the key for more high-level or adaptive control.
Comparative study of force control methods for bipedal walking using a force-sensitive hydraulic humanoid
Published in Advanced Robotics, 2020
Kazuya Murotani, Ko Yamamoto, Taiki Ishigaki, Yoshihiko Nakamura
Force control is the basic technology for the current robotics, in particular, for human–robot physical interaction. In the last decades, various types of force-controllable actuators have been developed, including series-elastic actuators [1], torque-sensing actuators [2,3], and hydraulic actuators [4]. Direct drive motors [5] are often used in quadruped robots [6]. Those actuators have been employed in humanoid robots [7–11] in the recent studies, changing the design of a humanoid. Until 2000s, the standard actuator of a humanoid was the combination of an electrical motor and a high reduction-ratio gear such as harmonic drive. This type of actuator is suitable for the joint position control. Many researchers focused on re-planning of the referential motion, and not much attention was paid to the fact that a humanoid requires the contact force control. A lot of studies [12–16] employed compliance or admittance control of the foot and realized walking motions on uneven terrains. The admittance control is regarded as re-planning of the reference motion based on the force sensor measurement, and its disadvantage is the time delay of the sensor feedback. Force-controllable actuators are now changing the control of a humanoid. The passivity-based control [17,18] and the inverse dynamics control [3,19–21] have shown successful results. On the other hand, a difficulty in the inverse dynamics control was also reported.
A continuous terminal sliding mode algorithm for robot manipulators: an application to force control
Published in International Journal of Control, 2022
Lauro F. Vázquez-Alberto, Marco A. Arteaga
Force control of robot manipulators has several possible applications, from industrial ones to surgical operations or haptics. For that reason, it has been a very active area of research in the recent years to comply with different applications under many circumstances. Some authors have built especial end-effectors to improve performance, like Wei and Xu (2022), who introduce the concept design of an end-effector based on a constant force mechanism for robotic polishing. The property of the constant force ensures more accurate contact without using a complex controller. But in fact most researchers have chosen a wide variety of control techniques to achieve this goal, including Proportional Integral (PI) or Proportional Integral Derivative (PID) controllers, although these are usually complemented with more sophisticated algorithms. For instance, Perrusquia et al. (2019) propose a model-free PID admittance controller by using reinforcement learning to obtain a desired force, which is the minimum one required by the robot to be close to its reference, so that impedance/admittance properties are maintained. Gutiérrez-Giles and Arteaga (2020) employ Generalised Proportional Integral (GPI) observers to estimate both forces and velocities to deal with uncertainties on the contact surface. Xu et al. (2021) introduce an active force control method consisting of force/position PI/PD controllers to eliminate grinding marks and traces, and a passive force control method including a PID to reduce the over- and under-cutting phenomenon in robotic machining systems. Then, a Kalman filter information fusion methodology is adopted to combine the active and passive force control methods. Maldonado-Fregoso et al. (2021) design a generalised and saturating adaptive stiffness control scheme in task-space to regulate the interaction or contact between the end-effector of a robot manipulator and the environment modelled as a vector of bounded spring-like forces. The proposed control approach has a PD structure with static model-based compensation of gravitational and interaction forces. Abbas et al. (2021) propose an adaptive motion-force control scheme for a networked ultrasound robotic manipulator to perform a transversal abdomen scan. An adaptive backstepping position controller is designed to ensure the stability of the ultrasound robot in the presence of parametric uncertainties and external disturbances. A PID force controller is proposed to maintain a constant interaction force during the scan process. H. Zhang et al. (2021) develop a hybrid force/position anti-disturbance control strategy based on a fuzzy PID control to improve the quality of grinding aviation blades, where a speed gain loop and a dual fuzzy PID control are introduced to enhance the anti-disturbance ability of the control system. Also, Yun et al. (2022) introduce an improved position controller based on a conventional fuzzy PID control strategy to realise hybrid force/bit control based on the position control by combining constraint estimation method and impedance force control.