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Introduction
Published in Jun Ma, Xiaocong Li, Kok Kiong Tan, Advanced Optimization for Motion Control Systems, 2020
Jun Ma, Xiaocong Li, Kok Kiong Tan
Motion control is a sub-field of automation entering an era of rapid changes and technological advances. It encompasses the systems related to moving parts of machines in a controlled manner. The motion control system is widely used in various fields in order to develop automated systems, such as precision engineering, micromanufacturing, biotechnology, and nanotechnology (Tan, Lee, and Huang 2007). The main components involved in a motion control system include the motion controller, the motor drive, the motor, the encoder, as well as other mechanical components. Each of these plays a unique role in achieving precision motion control. The motion controller is the brain of the system controlling the motion path, the servo loop closure, and the sequence execution. The controller sends a low-power command signal to the motor drive in digital or analog form. The motor drive amplifies the signal, produces the torque and sets the load into motion. Finally, the feedback sensors record the performance and send information to the controller.
Introduction to High-Performance Motion Control of Mechatronic Systems
Published in Takashi Yamaguchi, Mitsuo Chee, Khiang Pang Chee, Advances in High-Performance Motion Control of Mechatronic Systems, 2017
Mechatronics is present mainly in systems with dynamical motion, and is an integrated methodology for motion control including the choice of sensors, actuators, processers, and machines to control the dynamics and motion. Mechatronics exists in a wide variety of products which include home and office appliances such as air conditioners, office automation equipment such as printers, precision devices, e.g., wrist watches and digital cameras, etc., and entertainment devices such as electronic musical instruments. On a larger scale, mechatronics also appears in cars, airplanes, machine tools, and robots, etc. On the other hand, motion control is an advanced technology applied to mechatronic systems for achieving desired motions such as fast movement, precise positioning or tracking, profile control, and force control for the above-mentioned products.
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Published in Richard Zurawski, Industrial Communication Technology Handbook, 2017
Scott Hibbard, Peter Lutz, Ronald M. Larsen
Sercos offers short data update times and low communication jitter for any kind of automation applications, including—but not limited to—high-performance multiaxis machine control systems. Like most digital buses, Sercos greatly reduces connectivity problems in control systems. It can connect up to 254 slave devices (drives, I/O, ancillary devices) to a control using one fiber-optic cable ring (Sercos I/II) or up to 511 on a single Ethernet cable (Sercos III), compared to a traditional analog servo system with eight axes of motion that may require over 100 wires between the drive and the control. This reduces system cost, eliminates many types of noise problems, and helps machine designers get motion control systems up and running quickly.
Adaptive sliding mode control with information concentration estimator for a robot arm
Published in International Journal of Systems Science, 2020
Xiaofei Zhang, Hongbin Ma, Man Luo, Xiaomeng Liu
The motion control of robot (manipulator) is divided into two stages: trajectory (path) planning in the task space and tracking control in the joint space. The performance improvement of trajectory (path) planning involves kinematics and even obstacle-avoiding. Considering that trajectory planner eventually provides a tracking controller with a desired trajectory in joint space. In this paper, we mainly consider the tracking control problem in joint space. Most industrial manipulators have six degrees of freedom. Figure 1 is a modular, multi-jointed and self-developed robot arm which is independently manufactured by our laboratory. The cooperative robot is implemented by six joints ( to ), respectively. If there is no barrier, the end of robots can achieve any position and pose in space theoretically. In industrial high-performance applications, robots are generally required to achieve millimetre level positioning precision. The motion control is a key factor affecting the positioning accuracy of robot end actuator. Those joints ( to ) all have servo motor and decelerator. In this paper, the joint is discussed.The electrical equations and dynamic equations of the joint of a modular, multi-jointed and self-developed robot arm are introduced.
Identification of a class of precision motion systems with uncertain hysteretic nonlinearities
Published in International Journal of Control, 2023
Khaled F. Aljanaideh, Mohammad Al Janaideh, Micky Rakotondrabe, Mohammad Al Saaideh, Abdallah M. Almomani, Muath A. Bani Hani, Deepa Kundur
PI-based models have been used recently in many motion control and precision engineering applications, and these include: (i) control of a class of nano-robotic systems with piezoelectric stick-slip actuators (Al Janaideh et al., 2019), (ii) feedoforward control of piezoceramic stack actuators, magnetostrictive actuators, and Shape-memory alloy actuators (Al Janaideh et al., 2011), (iii) closed-loop control systems for piezoelectric cantilever beams (Al Janaideh et al., 2018), (iv) modelling strain-stress hysteresis characteristics of cable-driven robots (O. Aljanaideh et al., 2017), (v) modelling and control of pneumatic artificial muscles with hysteresis nonlinearities (Y. Zhang et al., 2021), and (vi) closed-loop control of shape memory alloys actuators (Shakiba et al., 2021).
Combining lean and agile manufacturing competitive advantages through Industry 4.0 technologies: an integrative approach
Published in Production Planning & Control, 2023
Bingjie Ding, Xavier Ferràs Hernández, Núria Agell Jané
Industrial communication systems have become an increasingly essential part of factory automation, motion control, and network control systems. They require information about the real-time performance and behaviour of the manufacturing plant. As a result, future manufacturing systems will need to make better use of plant data, transform it into knowledge and make smart automated decisions. Table 7 summarizes the main findings of the studies that prove Industry 4.0 technologies enhance flexibility in data collection and conversion.