State of charge (SOC) is a critical factor to guarantee that a battery system is operating in a safe and reliable manner. Many uncertainties and noises, such as fluctuating current, sensor measurement accuracy and bias, temperature effects, calibration errors or even sensor failure, etc. pose a challenge to the accurate estimation of SOC in real applications. This paper adds two contributions t...

In this paper, we study differential attacks against ARX schemes. We build upon the generalized characteristics of de Cannière and Rechberger and the multi-bit constraints of Leurent. We describe a more efficient way to propagate multi-bit constraints, that allows us to use the complete set of 2 2.5-bit constraints, instead of the reduced sets used by Leurent. As a result, we are able to build ...

We present several improvements to the framework of differential-linear attacks with a special focus on ARX ciphers. As demonstration their impact, we apply them Chaskey and ChaCha are able significantly improve upon best published so far.

Passenger comfort and vehicle stability are key aspects that must be guaranteed on ground vehicles, semi-active suspensions have offered an outstanding solution to meet these opposite objectives. This contribution describes a novel autoregressive with exogenous input (ARX) model-based predictive control strategy handled by driver block applied suspension improve passenger road holding when comp...

in this paper, we consider the problem of efficient computation of the forward kinematics of a 6 DOF robot manipulator built to use in rehabilitation purpose. Forward kinematics problem (FKP) of parallel robots is very difficult to solve in comparison to the serial manipulators. This problem is almost impossible to solve analytically. Numerical methods are one of the common solutions for this p...

Blind system identification is known to be a hard ill-posed problem and without further assumptions, no unique solution is at hand. In this contribution, we are concerned with the task of identifying an ARX model from only output measurements. Driven by the task of identifying systems that are turned on and off at unknown times, we seek a piecewise constant input and a corresponding ARX model w...

Efficient and robust fault detection and diagnosis (FDD) can potentially play an important role in developing building management systems (BMS) for high performance buildings. Our research indicates that, in comparison to traditional model-based or data-driven methods, the combination of time series modeling and machine learning techniques produces higher accuracy and lower false alarm rates in...

We consider the identification of ARX systems which are observed via a binary sensor. Previous solutions typically assumed the complete knowledge of the noise distribution and that the inputs can be chosen by the user. Here, we only make mild assumptions on the noise and we make no assumptions that we can control the inputs. However, we assume that we can choose the threshold of the binary sens...