Ari Arapostathis

Linearization of discrete-time systems

Abstract We characterize the equivalence of single-input single-output discrete-time nonlinear systems to linear ones, via a state-coordinate change and with or without feedback. Four cases are distinguished by allowing or disallowing feedback as well as by including the output map or not; the interdependence of these problems is analyzed. An important feature that distinguishes these discrete-time problems from the corresponding problem in continuous-time is that the state-coordinate transformation is here directly computable as a higher composition of the system and output maps. Finally, certain connections are made with the continuous-time case.

A statistical method for predicting the net harmonic currents generated by a concentration of electric vehicle battery chargers

This paper presents a method for predicting the net harmonic currents produced by a large number of electric vehicle (EV) battery chargers. The problem is stochastically formulated in order to account for randomness in individual charger start-time and battery state-of-charge. The authors introduce a model that allows for partial harmonics cancellation due to diversity in magnitudes and phase angles. A general solution technique is presented along with an example using data from a commercially available EV charger. Their results show that a limiting distribution of 7-10 chargers is adequate for accurately predicting harmonic injection currents using the central limit theorem. They also show that the expected values of net harmonic currents are considerably less than the peak values that would have been realized if the same number of chargers were operated in unison.

Power quality indices for transient disturbances

For reasonable power quality assessment of transient disturbances in electric power systems, new transient power quality indices are developed based on a signal processing technique, time-frequency analysis. Based on the time-frequency distribution of a transient disturbance, a set of time-frequency based power quality indices are developed. In this paper, the instantaneous disturbance energy ratio, normalized instantaneous disturbance energy ratio, instantaneous frequency, and instantaneous K-factor are suggested for transient power quality assessment. Time-frequency based power quality indices allow one to quantify the effects of transient disturbances with high-resolution and accuracy.

Analytical modeling of SRAM dynamic stability

In this paper, for the first time, a theory for evaluating dynamic noise margins of SRAM cells is developed analytically. The results allow predicting the transient error susceptibility of an SRAM cell using a closed-form expression. The key innovation involves using the methods of nonlinear system theory in developing the model. It is shown that when a transient noise of given magnitude affects a sensitive node of a cell, the bi-stable, feedback-driven nature of the cell determines whether the noise will be suppressed or will evolve to eventually flip state. The specific formal and quantitative result is a closed-form expression that can be used to predict whether a cell flip will occur for a noise signal with specific characteristics, and for a given SRAM cell design. Experiments show excellent match between the analytical prediction and the SPICE simulation results

The effect sampling on linear equivalence and feedback linearization

We investigate the effect of sampling on linearization for continuous time systems. It is shown that the discretized system is linearizable by state coordinate change for an open set of sampling times if and only if the continuous time system is linearizable by state coordinate change. Also, it is shown that linearizability via digital feedback imposes highly nongeneric constraints on the structure of the plant, even if this is known to be linearizable with continuous-time feedback. For n = 2, we show, under the assumption of completeness of adFG, that if the discretized system is lineariable by state coordinate change and feedback, then the continuous time affine complete analytic system is linearizable by state coordinate change only. Also, we suggest a method of proof when n ≥ 3.

A procedure for derating a substation transformer in the presence of widespread electric vehicle battery charging

This paper studies the effect of electric vehicle (EV) battery charging on a substation transformer that supplies commercial, residential, industrial, and EV load on a peak summer day. The analysis begins by modeling non-EV load with typical utility load shapes. EV load is modeled using the results from an analytical solution technique that predicts the net power and harmonic currents generated by a group of EV battery chargers. We evaluate the amount of transformer derating by maintaining constant daily transformer loss-of-life, with and without EV charging. This analysis shows that the time of day and the length of time during which the EVs begin charging are critical in determining the amount of transformer derating required. Our results show that with proper control, EV charging may have very little effect on power system components at the substation level.

Optimal Sensor Querying: General Markovian and LQG Models With Controlled Observations

This paper is motivated by networked control systems deployed in a large-scale sensor network where data collection from all sensors is prohibitive. We model it as a class of discrete-time stochastic control systems for which the observations available to the controller are not fixed, but there are a number of options to choose from, and each choice has a cost associated with it. The observation costs are added to the running cost of the optimization criterion and the resulting optimal control problem is investigated. Since only part of the observations are available at each time step, the controller has to balance the system performance with the penalty of the requested information (query). We first formulate the problem for a general partially observed Markov decision process model and then specialize to the stochastic linear quadratic Gaussian problem. We focus primarily on the ergodic control problem and analyze this in detail.

Joint Network Coding and Superposition Coding for Multi-User Information Exchange in Wireless Relaying Networks

A joint network coding and superposition coding (JNSC) scheme is proposed for information exchange between more than two users in a wireless relaying network. In this paper we consider two scenarios in a relaying network with four nodes: single and multiple information exchange loops between three source nodes, and two alternative transmission schemes, i.e. pure time division (PTD) and pure network coding (PNC), are also considered in order to compare with JNSC. The achievable rate regions of the PTD, PNC and JNSC schemes are all characterized, indicating the JNSC scheme is not always superior to the other two schemes. The sum rate optimization problem with a certain traffic pattern is also solved. We showed that the maximum coding gains of the JNSC and PNC schemes compared with the PTD scheme is achieved as the transmission rate of each node is one third of the sum rate in the network. Simulation results also reveal this phenomenon.

Minimum outage probability transmission with imperfect feedback for MISO fading channels

We study optimal transmission strategies in terms of minimum outage probability for a fading channel with multiple transmit antennas and a single receive antenna. We consider two cases of imperfect channel state information (CSI) feedback: mean feedback and covariance feedback. In both cases, the optimum strategy is shown to be transmission of multiple data streams to the same directions as when maximizing the ergodic channel capacity, but with different power allocation strategies which are closely related to the target rate. In the mean feedback case, the optimal power allocation strategy is also related to the accuracy of the feedback CSI, which affects significantly the achievable outage capacity.

On the Capacity of Gaussian Weak Interference Channels with Degraded Message sets

This paper is motivated by a sensor network on a correlated field where nearby sensors share information, and can thus assist rather than interfere with one another. We consider a special class of two-user Gaussian interference channels (IFCs) where one of the two transmitters knows both the messages to be conveyed to the two receivers. Both achievability and converse arguments are provided for a channel with Gaussian inputs and Gaussian noise when the interference is weaker than the direct link (a so called weak IFC). In general, this region serves as an outer bound on the capacity of weak IFCs with no shared knowledge between transmitters.