Learning for Advanced Motion Control

Iterative Learning Control (ILC) can achieve perfect tracking performance for mechatronic systems. The aim of this paper is to present an ILC design tutorial for industrial mechatronic systems. First, a preliminary analysis reveals the potential performance improvement of ILC prior to its actual implementation. Second, a frequency domain approach is presented, where fast learning is achieved through noncausal model inversion, and safe and robust learning is achieved by employing a contraction mapping theorem in conjunction with nonparametric frequency response functions. The approach is demonstrated on a desktop printer. Finally, a detailed analysis of industrial motion systems leads to several shortcomings that obstruct the widespread implementation of ILC algorithms. An overview of recently developed algorithms, including extensions using machine learning algorithms, is outlined that are aimed to facilitate broad industrial deployment.Comment: 8 pages, 15 figures, IEEE 16th International Workshop on Advanced Motion Control, 202

Design of a five-axis ultra-precision micro-milling machine—UltraMill. Part 2: Integrated dynamic modelling, design optimisation and analysis

Using computer models to predict the dynamic performance of ultra-precision machine tools can help manufacturers to substantially reduce the lead time and cost of developing new machines. However, the use of electronic drives on such machines is becoming widespread, the machine dynamic performance depending not only on the mechanical structure and components but also on the control system and electronic drives. Bench-top ultra-precision machine tools are highly desirable for the micro-manufacturing of high-accuracy micro-mechanical components. However, the development is still at the nascent stage and hence lacks standardised guidelines. Part 2 of this two-part paper proposes an integrated approach, which permits analysis and optimisation of the entire machine dynamic performance at the early design stage. Based on the proposed approach, the modelling and simulation process of a novel five-axis bench-top ultra-precision micro-milling machine tool—UltraMill—is presented. The modelling and simulation cover the dynamics of the machine structure, the moving components, the control system and the machining process and are used to predict the entire machine performance of two typical configurations

A holistic integrated dynamic design and modelling approach applied to the development of ultraprecision micro-milling machines

Ultraprecision machines with small footprints or micro-machines are highly desirable for micro-manufacturing high-precision micro-mechanical components. However, the development of the machines is still at the nascent stage by working on an individual machine basis and hence lacks generic scientific approach and design guidelines. Using computer models to predict the dynamic performance of ultraprecision machine tools can help manufacturers substantially reduce the lead time and cost of developing new machines. Furthermore, the machine dynamic performance depends not only upon the mechanical structure and components but also the control system and electronic drives. This paper proposed a holistic integrated dynamic design and modelling approach, which supports analysis and optimization of the overall machine dynamic performance at the early design stage. Based on the proposed approach the modelling and simulation process on a novel 5-axis bench-top ultraprecision micro-milling machine tool – UltraMill – is presented. The modelling and simulation cover the dynamics of the machine structure, moving components, control system and the machining process, and are used to predict the overall machine performance of two typical configurations. Preliminary machining trials have been carried out and provided the evidence of the approach being helpful to assure the machine performing right at the first setup

On Advanced Mobility Concepts for Intelligent Planetary Surface Exploration

Surface exploration by wheeled rovers on Earth's Moon (the two Lunokhods) and Mars (Nasa's Sojourner and the two MERs) have been followed since many years already very suc-cessfully, specifically concerning operations over long time. However, despite of this success, the explored surface area was very small, having in mind a total driving distance of about 8 km (Spirit) and 21 km (Opportunity) over 6 years of operation. Moreover, ESA will send its ExoMars rover in 2018 to Mars, and NASA its MSL rover probably this year. However, all these rovers are lacking sufficient on-board intelligence in order to overcome longer dis-tances, driving much faster and deciding autonomously on path planning for the best trajec-tory to follow. In order to increase the scientific output of a rover mission it seems very nec-essary to explore much larger surface areas reliably in much less time. This is the main driver for a robotics institute to combine mechatronics functionalities to develop an intelligent mo-bile wheeled rover with four or six wheels, and having specific kinematics and locomotion suspension depending on the operational terrain of the rover to operate. DLR's Robotics and Mechatronics Center has a long tradition in developing advanced components in the field of light-weight motion actuation, intelligent and soft manipulation and skilled hands and tools, perception and cognition, and in increasing the autonomy of any kind of mechatronic systems. The whole design is supported and is based upon detailed modeling, optimization, and simula-tion tasks. We have developed efficient software tools to simulate the rover driveability per-formance on various terrain characteristics such as soft sandy and hard rocky terrains as well as on inclined planes, where wheel and grouser geometry plays a dominant role. Moreover, rover optimization is performed to support the best engineering intuitions, that will optimize structural and geometric parameters, compare various kinematics suspension concepts, and make use of realistic cost functions like mass and consumed energy minimization, static sta-bility, and more. For self-localization and safe navigation through unknown terrain we make use of fast 3D stereo algorithms that were successfully used e.g. in unmanned air vehicle ap-plications and on terrestrial mobile systems. The advanced rover design approach is applica-ble for lunar as well as Martian surface exploration purposes. A first mobility concept ap-proach for a lunar vehicle will be presented

Towards an Integrated Conceptual Design Evaluation of Mechatronic Systems: The SysDICE Approach

National audienceMechatronic systems play a significant role in different types of industry, especially in trans- portation, aerospace, automotive and manufacturing. Although their multidisciplinary nature provides enormous functionalities, it is still one of the substantial challenges which frequently impede their design process. Notably, the conceptual design phase aggregates various engi- neering disciplines, project and business management fields, where different methods, modeling languages and software tools are applied. Therefore, an integrated environment is required to intimately engage the different domains together. This paper outlines a model-based research approach for an integrated conceptual design evaluation of mechatronic systems using SysML. Particularly, the state of the art is highlighted, most important challenges, remaining problems in this field and a novel solution is proposed, named SysDICE, combining model based system engineering and artificial intelligence techniques to support for achieving efficient design

Active patterns for self-optimization : Schemes for the design of intelligent mechatronic systems

Self-optimizing mechatronic systems react autonomously and flexibly to changing conditions. They are capable of learning and optimize their behavior throughout their life cycle. The paradigm of self-optimization is originally inspired by the behavior of biological systems. The key to the successful development of self-optimizing systems is a conceptual design process that precisely describes the desired system behavior. In the area of mechanical engineering, active principles based on physical effects such as friction or lever are widely used to concretize the construction structure and the behavior. The same approach can be found in the domain of software-engineering with software patterns such as the broker-pattern or the strategy pattern. However there is no appropriate design schema for the development of intelligent mechatronic systems covering the needs to fulfill the paradigm of self-optimization. This article proposes such a schema called Active Patterns for Self-Optimization. It is shown how a catalogue of active patterns can be derived from a set of four basic active patterns. This design approach is validated for a networked mechatronic system in a multiagent setting where the behavior is implemented according to a biologically inspired technique – the neuro-fuzzy learning method.1st IFIP International Conference on Biologically Inspired Cooperative Computing - Mechatronics and Computer ClustersRed de Universidades con Carreras en Informática (RedUNCI

Architecture and Design Methodology of Self-Optimizing Mechatronic Systems

The conceivable development of information and communication technology will enable mechatronic systems with inherent partial intelligence. We refer to this by using the term \"self-optimization\". Self-Optimizing systems react autonomously and flexibly on changing operation conditions. They are able to learn and optimize their behavior at runtime. The development of mechatronic and especially self-optimizing systems is still a challenge. A significant milestone within the development is the principle solution. It determines the basic structure as well as the operation mode of the system and is the result of the conceptual design. Additionally it is the basis for the concretization of the system which involves experts from several domains, such as mechanics, electrical engineering/electronics, control engineering and software engineering. This contribution presents a new specification technique for the conceptual design of mechatronic and self-optimizing systems. It also uses the railway technology as a complex example, to demonstrate how to use this specification technique and in which way it profits for the development of future mechanical engineering systems. Keywords Design Methodology, Mechatronics, Self-Optimization, Principle Solution, Conceptual Design, Domain-Spanning Specificatio

Application of TRIZ to develop an in-service diagnostic system for a synchronous belt transmission for automotive application

Development of robust diagnostic solutions to monitor the health of systems and components to ensure through life cost effectiveness is often technically difficult, requiring an effective integration of design development with research and innovation. This paper presents a structured application of TRIZ and USIT (Unified Structured Inventive Thinking) to generate concept solutions for an in-service diagnostic system for a synchronous belt drive system for an automotive application. The systematic exploration through TRIZ and USIT methods has led to the development of six concept solution ideas directed at the functional requirement to determine the state or condition of the belt. The paper demonstrates that the combined deployment of TRIZ and USIT frameworks is a valuable approach addressing difficult design problem