Precision manufacturing is a development that has been gathering momentum over the last century and accelerating over the last 25 years in terms of research, development, and application to product innovation. The driving force in this development arises from requirements for much higher performance of products, higher reliability, longer life, lower cost, and miniaturization. This development is widely known as precision engineering and, today, it is generally defined as manufacturing to tolerances which are better than one part in 105. Applications are abound and can be found in various semiconductor processes (e.g., lithography, wafer probing, inspection), Coordinate Measuring Machines (CMMs) and precision metrology systems (e.g., Scanning Probe Microscopy (SPM)), and robot/machine tools to carry out micro-assembly (e.g., MEMS) and delicate short wavelength laser processes. As an enabling technology for precision engineering, precision instrumentation and measurement, geometrical calibration and compensation, and motion control are directly important issues to be addressed in the overall system design and realization. This book is focused on these aspects of precision engineering. It is a compilation of the major results and publications from a major project which develop a state-of-the-art high-speed, ultra-precision robotic system. A comprehensive and thorough treatment of the subject matter is provided in a manner that is amenable to a broad base of readers, ranging from the academics to the practitioners, by providing detailed experimental verifications of the developed materials.

The precision and productivity requirements for modern manufacturing process drive precision systems to their physical limitations, such as the limitation of sensor resolution, actuator saturation, and traversing speed. Incorporating these restrictions, constrained optimization has been an active research area that can explicitly handle the physical constraints. This dissertation covers three important topics in productivity and precision improvements through constrained optimization: sub-count sensor estimation, constraint violation avoidance, and cycle-time minimization. To solve sensor quantization and measurement synchronization problem, a model-based encoder-triggered estimation method was developed addressing state continuity. By enforcing smooth estimation in important physical states such as position and velocity, this method avoids abrupt estimation change when encoder trigger occurs. Furthermore, because continuous-time open-loop model is used to predict inter-trigger behavior, the developed sub-count estimator can be applied to asynchronous systems with untimely measurement updates. By applying this sub-count estimation method, the precision system can improve tracking performance when only quantized and untimely sensor measurement is available. When improving tracking performance, the precision system is often pushed to its limitation. This often causes the precision system to violate system constraints (such as control signal saturation and excessive acceleration), which results in unexpected vibration and sacrifices the tracking performance. To avoid such kind of constraint violation, the system model can be used to predict the dynamic behavior of the plant given a known trajectory and plant model. A model predictive control based optimal feed-forward tracking method is proposed to be integrable with any feedback controller. Besides tracking performance, cycle time is also an important index for modern precision motion control. The shorter the cycle time is, the more productive the machine can be. Therefore, to reduce cycle time for precision machines, a minimal time contour tracking problem is formulated to explicitly constrained receding horizon control where the trajectory (feed) profile is determined for the specified contour under system dynamics, contour error, axial velocity, signal saturation, and monotonic feed constraints. Because minimal-time operations typically drive the system near its constraint boundary, it is vital to reject measurement noise and compensate for modeling error in real-time. To accommodate the high sampling rate controllers in precision systems, an efficient real-time quadratic programming solver is proposed with robust warm start strategy in order to handle active constraints.

Precision manufacturing is a development that has been gathering momentum over the last century and accelerating over the last 25 years in terms of research, development, and application to product innovation. The driving force in this development arises from requirements for much higher performance of products, higher reliability, longer life, lower cost, and miniaturization. This development is widely known as precision engineering and, today, it is generally defined as manufacturing to tolerances which are better than one part in 105. Applications are abound and can be found in various semiconductor processes (e.g., lithography, wafer probing, inspection), Coordinate Measuring Machines (CMMs) and precision metrology systems (e.g., Scanning Probe Microscopy (SPM)), and robot/machine tools to carry out micro-assembly (e.g., MEMS) and delicate short wavelength laser processes. As an enabling technology for precision engineering, precision instrumentation and measurement, geometrical calibration and compensation, and motion control are directly important issues to be addressed in the overall system design and realization. This book is focused on these aspects of precision engineering. It is a compilation of the major results and publications from a major project which develop a state-of-the-art high-speed, ultra-precision robotic system. A comprehensive and thorough treatment of the subject matter is provided in a manner that is amenable to a broad base of readers, ranging from the academics to the practitioners, by providing detailed experimental verifications of the developed materials.

Precision motion control is strongly required in many fields, such as precision engineering, micromanufacturing, biotechnology, and nanotechnology. Although great achievements have been made in control engineering, it is still challenging to fulfill the desired performance for precision motion control systems. Substantial works have been presented to reveal an increasing trend to apply optimization approaches in precision engineering to obtain the control system parameters. In this book, we present a result of several years of work in the area of advanced optimization for motion control systems. The book is organized into two parts: Part I focuses on the model-based approaches, and Part II presents the data-based approaches. To illustrate the practical appeal of the proposed optimization techniques, theoretical results are verified with practical examples in each chapter. Industrial problems explored in the book are formulated systematically with necessary analysis of the control system synthesis. By virtue of the design and implementation nature, this book can be used as a reference for engineers, researchers, and students who want to utilize control theories to solve the practical control problems. As the methodologies have extensive applicability in many control engineering problems, the research results in the field of optimization can be applied to full-fledged industrial processes, filling in the gap between research and application to achieve a technology frontier increment.

Precision Motion Systems: Modeling, Control, and Applications presents basic dynamics and the control knowledge needed for the daily challenges of researchers and professionals working in the field. The book explains accurate dynamics and control algorithms, along with experimental validation of precision systems in industrial, medical, airborne and spaceborne applications. By using the proposed experimental designs, readers will be able to make further developments and validations. Presents accurate dynamics and control algorithms in industrial, medical, airborne and spaceborne applications Explains basic dynamics and control knowledge, such as Laplace transformations and stability analysis Teaches how to design, develop and control typical precision systems

Modeling and Control of Precision Actuators explores new technologies that can ultimately be applied in a myriad of industries. It covers dynamical analysis of precise actuators and strategies of design for various control applications. The book addresses four main schemes: modeling and control of precise actuators; nonlinear control of precise actuators, including sliding mode control and neural network feedback control; fault detection and fault-tolerant control; and advanced air bearing control. It covers application issues in the modeling and control of precise actuators, providing several interesting case studies for more application-oriented readers. Introduces the driving forces behind precise actuators Describes nonlinear dynamics of precise actuators and their mathematical forms, including hysteresis, creep, friction, and force ripples Presents the control strategies for precise actuators based on Preisach model as well as creep dynamics Develops relay feedback techniques for identifying nonlinearities such as friction and force ripples Discusses a MPC approach based on piecewise affine models which emulate the frictional effects in the precise actuator Covers the concepts of air bearing stages with the corresponding control method Provides a set of schemes suitable for fault detection and accommodation control of mechanical systems Emphasizing design theory and control strategies, the book includes simulation and practical examples for each chapter; covers precise actuators such as piezo motors, coil motors, air bearing motors, and linear motors; discusses integration among different technologies; and includes three case studies in real projects. The book concludes by linking design methods and their applications, emphasizing the key issues involved and how to implement the precision motion control tasks in a practical system. It provides a concise and comprehensive source of the state-of-the-art developments and results for modeling and control of precise actuators.