Development of intelligent learning motion control systems

Ph.DDOCTOR OF PHILOSOPH

Design and Control of Electrical Motor Drives

Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito

Modeling and Contour Control of Multi-Axis Linear Driven Machine Tools

In modern manufacturing industries, many applications require precision motion control of multi-agent systems, like multi-joint robot arms and multi-axis machine tools. Cutter (end effector) should stay as close as possible to the reference trajectory to ensure the quality of the final products. In conventional computer numerical control (CNC), the control unit of each axis is independently designed to achieve the best individual tracking performance. However, this becomes less effective when dealing with multi-axis contour following tasks because of the lack of coordination among axes. This dissertation studies the control of multi-axis machine tools with focus on reducing the contour error. The proposed research explicitly addresses the minimization of contour error and treats the multi-axis machine tool as a multi-input-multi-output (MIMO) system instead of several decoupled single-input-single-output (SISO) systems. New control schemes are developed to achieve superior contour following performance even in the presence of disturbances. This study also extends the applications of the proposed control system from plane contours to regular contours in R3. The effectiveness of the developed control systems is experimentally verified on a micro milling machine

Recent Advances in Robust Control

Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics

Adaptive control system of slotless DC linear motor

Slotless DC linear motors (SDCLM) offer several benefits over traditional linear motors, including higher efficiency, smoother operation, and higher power density. These advantages make them a popular choice for a wide range of applications in various industries. One of the main benefits of a slotless DC linear motor is the absence of slot harmonics, which can cause vibration and noise in traditional slotted motors. This makes slotless motors ideal for applications that require precise and smooth motion, such as in medical equipment, robotics, and semiconductor manufacturing. However, one of the challenges of a Slotless DC linear motor is the presence of force ripple, which can limit the motor's performance, precision, and accuracy. Force ripple is caused by the mutual attraction of the translator's magnets and iron cores. It is independent of the motor current and is determined only by the relative position of the motor coils regarding the magnets. To overcome these challenges, motor redesign, magnetic field optimisation and the use of an adaptive control system. This research program focused on and investigated the above possible methods (i.e., motor redesign, magnetic field optimisation field and use of advanced control algorithms such as Sliding Mode Control SMC) to tackle the current challenges and improve the relevant industrial application performance and precision. The inquiry encompasses the analysis, design, and control of the SDCLM by proper modelling, building, and experimental validation of the modelled findings, applying both static and dynamic methodologies. Electrical, mechanical, and magnetic analyses were performed on the SDCLM design. The performance of the SDCLM was investigated using a finite element method (FEM), and the motor parameters were improved. Investigation and analysis are performed about additional difficulties such as force ripple and normal force, where the results indicated that the flux density in the airgap and the thrust force were different between the actual time and the simulation by 7.14% and 8.07%, respectively. Moreover, sliding mode control is designed to achieve desired system performance, such as reducing the power ripple of a slotless DC linear motor. where the proposed control shows experiments that it has stability despite disturbances and uncertainties. To improve the control method and reduce the steady-state error caused by the force ripple, the Bees algorithm has been used to tune the parameters of the controller. Finally, the outcomes indicate that the control method employing the disturbance observer and Bees algorithm has enhanced the performance of both position and speed, while concurrently reducing the force ripple. A comparison between simulation and experiment shows that there is a difference in the tracking performance, where the difference was around 13.6%. This error could have arisen from the omission of certain errors that cannot be accounted for within the simulation. These errors may stem from issues with the position sensor or discrepancies in the manual system design process

Bilateral Control with Task Learning and Adaptation to Environment

The Motion Copying System permits to save an operator task in terms of position and force references for the action reproduction whenever the operator isn't available or to train new users. This thesis analyzes the MCS design and limitations, the Bilateral Control System on which the MCS is based, and proposes a model to adapt the saved task to new environmental conditions

Robust fractional-order fast terminal sliding mode control with fixed-time reaching law for high-performance nanopositioning

Open Access via the Wiley Agreement ACKNOWLEDGEMENTS This work is supported by the China Scholarship Council under Grant No. 201908410107 and by the National Natural Science Foundation of China under Grant No. 51505133. The authors also thank the anonymous reviewers for their insightful and constructive comments.Peer reviewedPublisher PD