15 years of experience with mechatronics research and education

This paper describes the experiences with mechatronic research projects and several educational structures in the University of Twente since 1989. Education took place in a two-year Mechatronic Designer programme, in specialisations in Electrical and Mechanical Engineering and in an (international) MSc programme. There are two-week mechatronic projects in the BSc curricula of EE and ME. Many of the PhD and MSc projects were done in projects sponsored by the industry or by application-oriented research programs. Research topics included modelling and simulation (learning) control, embedded systems and mechatronic design

Improving the Accuracy of Industrial Robots via Iterative Reference Trajectory Modification

In this paper, a novel repetitive control (RC) scheme is presented and discussed. The general framework is the control of repetitive tasks of robotic systems or, more in general, of automatic machines. The key idea of the proposed scheme consists in modifying the reference trajectory provided to the plant in order to compensate for external loads or unmodeled dynamics that cyclically affect it. By exploiting the fact that uniform B-spline trajectories can be generated by means of dynamic filters, the trajectory planning phase has been integrated within an RC scheme that is able to modify in real time the reference signal in order to nullify the tracking errors occurring at the desired via-points. Because of this mechanism, the control scheme is very suitable for the application to industrial plants with off-the-shelf, unmodifiable controllers. Experimental results obtained with a standard industrial manipulator both in joint space and in workspace show the effectiveness of the proposed method

Modelling and real-time control of a high performance rotary wood planing machine

Rotary planing is one of the most valuable machining operations in the timber processing industry. It has been established that cutting tool inaccuracy and forced vibration during the machining process are the primary causes of surface quality degradation. The main aim of this thesis is to design a control architecture that is suitable for adaptive operation of a wood planing machining in order to improve the quality of its surface finish. In order to achieve the stated goal, thorough understanding of the effects of machine deficiencies on surface finish quality is required. Therefore, a generic simulation model for synthesising the surface profiles produced by wood planing process is first developed. The model is used to simulate the combined effects of machining parameters, vibration and cutting tool inaccuracy on the resultant surface profiles. It has been postulated that online monitoring of surface finish quality can be used to provide feedback information for a secondary control loop for the machining process, which will lead to the production of consistently high quality surface finishes. There is an existing vision-based wood surface profile measurement technique, but the application of the technique has been limited to static wood samples. This thesis extends the application of the technique to moving wood samples. It is shown experimentally that the method is suitable for in-process surface profile measurements. The current industrial wood planing machines do not have the capability of measuring and adjusting process parameters in real-time. Therefore, knowledge of the causes of surface finish degradation would enable the operators to optimise the mechanical structure of the machines offline. For this reason, two novel approaches for characterising defects on planed timber surfaces have been created in this thesis using synthetic data. The output of this work is a software tool that can assist machine operators in inferring the causes of defects based on the waviness components of the workpiece surface finish. The main achievement in this research is the design of a new active wood planing technique that combines real-time cutter path optimisation (cutting tool inaccuracy compensation) with vibration disturbance rejection. The technique is based on real-time vertical displacements of the machine spindle. Simulation and experimental results obtained from a smart wood planing machine show significant improvements in the dynamic performance of the machine and the produced surface finish quality. Potential areas for future research include application of the defects characterisation techniques to real data and full integration of the dynamic surface profile measurements with the smart wood planing machine

Novel control of a high performance rotary wood planing machine

Rotary planing, and moulding, machining operations have been employed within the woodworking industry for a number of years. Due to the rotational nature of the machining process, cuttermarks, in the form of waves, are created on the machined timber surface. It is the nature of these cuttermarks that determine the surface quality of the machined timber. It has been established that cutting tool inaccuracies and vibrations are a prime factor in the form of the cuttermarks on the timber surface. A principal aim of this thesis is to create a control architecture that is suitable for the adaptive operation of a wood planing machine in order to improve the surface quality of the machined timber. In order to improve the surface quality, a thorough understanding of the principals of wood planing is required. These principals are stated within this thesis and the ability to manipulate the rotary wood planing process, in order to achieve a higher surface quality, is shown. An existing test rig facility is utilised within this thesis, however upgrades to facilitate higher cutting and feed speeds, as well as possible future implementations such as extended cutting regimes, the test rig has been modified and enlarged. This test rig allows for the dynamic positioning of the centre of rotation of the cutterhead during a cutting operation through the use of piezo electric actuators, with a displacement range of ±15μm. A new controller for the system has been generated. Within this controller are a number of tuneable parameters. It was found that these parameters were dependant on a high number external factors, such as operating speeds and run‐out of the cutting knives. A novel approach to the generation of these parameters has been developed and implemented within the overall system. Both cutterhead inaccuracies and vibrations can be overcome, to some degree, by the vertical displacement of the cutterhead. However a crucial information element is not known, the particular displacement profile. Therefore a novel approach, consisting of a subtle change to the displacement profile and then a pattern matching approach, has been implemented onto the test rig. Within the pattern matching approach the surface profiles are simplified to a basic form. This basic form allows for a much simplified approach to the pattern matching whilst producing a result suitable for the subtle change approach. In order to compress the data levels a Principal Component Analysis was performed on the measured surface data. Patterns were found to be present in the resultant data matrix and so investigations into defect classification techniques have been carried out using both K‐Nearest Neighbour techniques and Neural Networks. The application of these novel approaches has yielded a higher system performance, for no additional cost to the mechanical components of the wood planing machine, both in terms of wood throughput and machined timber surface quality