AN APPROACH TO DESIGN OF DC-DC BOOST CONVERTER WITH DIGITAL CONTROL

This paper deals with the design of digital controller for DC-DC boost converter. This controller is a combination of a generalized minimum variance control and one-step-delayed disturbance estimator. The generalized minimum variance control algorithm design is based on the input/output converter model. It should provide the output voltage stability, whereas the disturbance estimator increases the robustness and the steady-state accuracy of converter in the presence of input voltage and load resistance variations. With these control techniques, the converter can achieve better power efficiency. Finally, the effectiveness of the proposed design procedure is verified by a digital simulation, showing satisfactory DC-DC boost converter performances

Enabling IoT ecosystems through platform interoperability

Today, the Internet of Things (IoT) comprises vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and adapt to the platform-specific API and information models. Having to perform these actions for each platform often outweighs the possible gains from adapting applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and prevent the emergence of broadly accepted IoT ecosystems. The BIG IoT (Bridging the Interoperability Gap of the IoT) project aims to ignite an IoT ecosystem as part of the European Platforms Initiative. As part of the project, researchers have devised an IoT ecosystem architecture. It employs five interoperability patterns that enable cross-platform interoperability and can help establish successful IoT ecosystems.Peer ReviewedPostprint (author's final draft

Identification of Nonlinear Systems Using the Hammerstein-Wiener Model with Improved Orthogonal Functions

Hammerstein-Wiener systems present a structure consisting of three serial cascade blocks. Two are static nonlinearities, which can be described with nonlinear functions. The third block represents a linear dynamic component placed between the first two blocks. Some of the common linear model structures include a rational-type transfer function, orthogonal rational functions (ORF), finite impulse response (FIR), autoregressive with extra input (ARX), autoregressive moving average with exogenous inputs model (ARMAX), and output-error (O-E) model structure. This paper presents a new structure, and a new improvement is proposed, which is consisted of the basic structure of Hammerstein-Wiener models with an improved orthogonal function of Müntz-Legendre type. We present an extension of generalised Malmquist polynomials that represent Müntz polynomials. Also, a detailed mathematical background for performing improved almost orthogonal polynomials, in combination with Hammerstein-Wiener models, is proposed. The proposed approach is used to identify the strongly nonlinear hydraulic system via the transfer function. To compare the results obtained, well-known orthogonal functions of the Legendre, Chebyshev, and Laguerre types are exploited

Tube Model Predictive Control with an Auxiliary Sliding Mode Controller

This paper studies Tube Model Predictive Control (MPC) with a Sliding Mode Controller (SMC) as an auxiliary controller. It is shown how to calculate the tube widths under SMC control, and thus how much the constraints of the nominal MPC have to be tightened in order to achieve robust stability and constraint fulfillment. The analysis avoids the assumption of infinitely fast switching in the SMC controller

Tube Model Predictive Control with an Auxiliary Sliding Mode Controller

This paper studies Tube Model Predictive Control (MPC) with a Sliding Mode Controller (SMC) as anauxiliary controller. It is shown how to calculate the tube widths under SMC control, and thus how muchthe constraints of the nominal MPC have to be tightened in order to achieve robust stability and constraintfulfillment. The analysis avoids the assumption of infinitely fast switching in the SMC controller

Enabling IoT ecosystems through platform interoperability

Today, the Internet of Things (IoT) comprises vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and adapt to the platform-specific API and information models. Having to perform these actions for each platform often outweighs the possible gains from adapting applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and prevent the emergence of broadly accepted IoT ecosystems. The BIG IoT (Bridging the Interoperability Gap of the IoT) project aims to ignite an IoT ecosystem as part of the European Platforms Initiative. As part of the project, researchers have devised an IoT ecosystem architecture. It employs five interoperability patterns that enable cross-platform interoperability and can help establish successful IoT ecosystems.Peer Reviewe