Linear system identification [1]-[4] is a basic step in modern control design approaches. Starting from experimental data, a linear dynamic time-invariant model is identified to describe the relationship between the reference signal and the output of the system. At the same time, the power spectrum of the unmodeled disturbances is identified to generate uncertainty bounds on the estimated model. Linear system identification is also used in other disciplines, for example vibrational analysis of mechanical systems, where it is called modal analysis [5], [6]. Because linear time-invariant models are a basic model structure, linear system identification is frequently used in electrical [7]-[10], electronic, chemical [11], civil [12], and also in biomedical applications [13]. It provides valuable information to the design engineers in all phases of the design process.Starting from the late 1960s, system identification tools have been developed to obtain parametric models to describe the dynamic behavior of systems. A formal framework is set up to study the theoretical properties of the system identification algorithms [1]- [3]. The consistency (does the estimated model converge to the true system as the amount of data grows?) and the efficiency (is the uncertainty of the estimated model as small as possible?) are analyzed in detail. Underlying all these results are the assumptions that the system to be modeled is linear and time invariant.It is clear that these assumptions are often (mostly?) not met in real-life applications. Most systems are only linear to a first approximation. Depending on the excitation level, the output is disturbed by nonlinear distortions so that the linearity assumption no longer holds. This immediately raises doubts about the validity of the results obtained and validated by the linear system identification framework. The term nonlinear distortions indicates that nonlinear systems with a (dominant) linear term are considered. The deviations from the linear behavior are called nonlinear distortions.

Left-ventricular assist devices (LVADs) have evolved from being a bridge to total heart transplant to forming a bridge to recovery of the heart. With this development, the process of weaning has become more important, and consequently, the operation and control of the LVADs during this process is more important as well. To evaluate the function and the assist properties of LVADs, a mock circulation, featuring the properties of the (diseased) heart and the systemic circulation may prove to be a valuable tool.

Packaging of semiconductor chips, especially MEMSbased, always causes stress on the functional areas of the die causing unpredictable changes in chip performance. As a consequence such devices can only be calibrated individually after complete assembly. Melexis and TNO have developed an approach to reduce significantly packaging stress effects by means of additive manufacturing of the die package. The device is calibrated in a standard package with a standard calibration tool whereas the client specific shape is realized with additive manufacturing afterwards. The placement of a dedicated nozzle onto a SOIC16 package with a silicon pressure sensor illustrates the approach. Additive M anufacturingContinued advances in material properties and processing speed brought micro stereolithography (µ-SLA) into industrial manufacturing. For specific geometrical requirements and/or small series (down to 1 piece), µ-SLA has become a costeffective alternative to mold based processes. The micro stereolithography technology is elaborately described in numerous publications, as e.g. in refs [1] and [2]. BackgroundThe manufacturing of 3D objects by stereolithography is based on the spatially controlled solidification of a liquid resin by photo polymerization. Layer-by-layer the product is built, thus allowing for maximum freedom of form. To produce a layer a light projector is used to illuminate a pattern on the surface of a resin with a controlled illumination depth. As a result of this, the resin in the illuminated pattern is solidified and a product layer is formed. Both laser based light systems and Digital Light Processing (DLP) are methods to illuminate the resin. In DLP a digital micro mirror device (DMD) is used, which projects a complete 2-dimensional pixel-pattern, so a complete layer of resin can be cured at once. This method minimizes processing time and allows for smaller pixel sizes than laser based stereolithography.

No abstract

No abstract