State Selection Scheme Research Articles

A Stacked Multilevel Inverter With Single DC Link for Open-End Winding Induction Motor Drive With Zero-Voltage Switching and Common-Mode Voltage Elimination

A switching-state selection scheme for a five-level stacked multilevel inverter for open-end winding motor drive is presented in this article. Using the proposed scheme, converter can be operated with a single dc supply and with zero common-mode voltage. In addition, the switching transition of high-voltage switches occurs at zero-voltage conditions. The degree of freedom provided by the redundant switching-states and voltage vectors of the inverter topology is utilized to design the modulation scheme. The proposed switching-state selection leads to inherent capacitor balancing without using any extra sensors and fundamental frequency switching of the high-voltage switches of the topology. The modulation scheme uses triangular carrier comparison and, hence, avoids the complexity of subsector identification and dwell time calculation. Half-wave symmetry in output waveforms is ensured by maintaining synchronous sampling with constant samples per fundamental cycle. The inverter topology and the effectiveness of the state selection scheme are experimentally validated on an open-end winding induction motor drive, and experimental results showing steady-state and dynamic operations are presented.

Weighting Factor Free Model Predictive Control for a Flying Capacitor Converter in a DC Microgrid

This paper presents a single-objective model predictive control for a bidirectional DC-DC flying capacitor (FC) converter, which integrates a battery to the microgrid. The presence of multiple FCs facilitates the converter to interface a low-voltage battery to a high-voltage DC bus at reduced voltage stress on its power switches. However, such converter requires a controller that fulfils multiple objectives, namely DC bus and FC voltage regulations, and bidirectional power flow. The key feature of the proposed controller is that it utilizes a model predictive control with a single-objective cost function based on battery current and a redundant state selection scheme to attain these multiple objectives. Adopting such a strategy not only reduces computational burden but also eliminates the need for weighting factors and requirement of complex numerical models for its estimation. Another notable aspect is that the controller employs an improved dynamic reference model to generate appropriate battery current reference for the DC bus voltage regulation, without necessitating a secondary control loop and additional current sensors. Finally, experimental results of the proposed system for a step-response of the DC bus voltage, varying PV power, and loads are validated and compared against finite control set model predictive control.

Sampling Latent States for High-Dimensional Non-Linear State Space Models with the Embedded HMM Method

We propose a new scheme for selecting pool states for the embedded Hidden Markov Model (HMM) Markov Chain Monte Carlo (MCMC) method. This new scheme allows the embedded HMM method to be used for efficient sampling in state space models where the state can be high-dimensional. Previously, embedded HMM methods were only applicable to low-dimensional state-space models. We demonstrate that using our proposed pool state selection scheme, an embedded HMM sampler can have similar performance to a well-tuned sampler that uses a combination of Particle Gibbs with Backward Sampling (PGBS) and Metropolis updates. The scaling to higher dimensions is made possible by selecting pool states locally near the current value of the state sequence. The proposed pool state selection scheme also allows each iteration of the embedded HMM sampler to take time linear in the number of the pool states, as opposed to quadratic as in the original embedded HMM sampler.

Satellite cluster flight using on-off cyclic control

Nano-satellite clusters and disaggregated satellites are new concepts in the realm of distributed satellite systems, which require complex cluster management – mainly regulating the maximal and minimal inter-satellite distances on time scales of years – while utilizing simple on-off propulsion systems. The simple actuators and long time scales require judicious astrodynamical modeling coupled with specialized orbit control. This paper offers a satellite cluster orbit control law which works for long time scales in a perturbed environment while utilizing fixed-magnitude thrusters. The main idea is to design a distributed controller which balances the fuel consumption among the satellites, thus mitigating the effect of differential drag perturbations. The underlying methodology utilizes a cyclic control algorithm based on a mean orbital elements feedback. Stability properties of the closed-loop cyclic control system do not adhere to the classical Lyapunov stability theory, so an effort is made to define and implement a suitable stability theory of noncompact equilibria sets. A state selection scheme is proposed for efficiently establishing a low Earth orbit cluster. Several simulations, including a real mission study, and several comparative investigations, are performed to show the strengths of the proposed control law.

A hybrid refinement scheme for intra- and cross- corpora phonetic segmentation

This paper proposes a hybrid refinement scheme for more accurate localization of phonetic boundaries by combining three different post-processing techniques, including statistical correction, fusion, and predictive models. A statistical method based on state-level correction is proposed to improve the segmentation results. Effects of search ranges on the statistical correction process are studied and a state selection scheme is used to enhance the correction results. This paper also examines the effects of time resolution, i.e., stepsize, of acoustic models on the accuracy of segmentation. A multi-resolution fusion process is proposed to further refine the statistically corrected results. Finally, predictive models are designed to improve the segmentation accuracy by incorporating various acoustic features and searching around the preliminary boundary with a smaller stepsize. By applying the hybrid refinement scheme on a well-known corpus, significant improvements of segmentation results in terms of segmentation accuracy with different tolerances, mean absolute error (MAE), and root-mean-square error (RMSE) can be observed. Furthermore, a scenario of cross-corpora segmentation is examined in generating the segmentation results for a new corpus with a small set of labeled data. Experimental results show that the proposed refinement procedure can generate segmentation results comparable to those given by well-trained acoustic models obtained from the new corpus.

Space-time-state block coded mimo communication systems using reconfigurable antennas

Reconfigurable antennas offer a promising solution to the problem of space limitation in high-performance wireless communication over handset devices. In this paper, we propose a novel transmission scheme capable of extracting the maximum diversity gains of a Multiple-Input Multiple-Output (MIMO) communication system employing reconfigurable antennas at the transmitter, the receiver or at both ends of the wireless link, without the need for feedback. For a MIMO communication system using reconfigurable antennas at the transmitter, we propose a state-switching scheme in combination with an appropriate three-dimensional block code in order to extract the maximum possible level of diversity. When reconfigurable antennas are placed at the receiver end, we propose a state-selection scheme and prove that the proposed scheme is capable of achieving maximum diversity gains. Moreover, the state-selection method is able to obtain selection gain in addition to diversity gain. As shown, both state-switching and state-selection schemes can be combined together when reconfigurable antennas are used at both ends of the wireless link. Furthermore, we discuss and quantify the effects of switching delay on the performance of both state-switching and state-selection schemes. Finally, we provide simulation results to validate the performance of the proposed schemes. To demonstrate the gains of our schemes in realistic propagation conditions, we also conduct simulations using an actual reconfigurable antenna known as the PIXEL antenna.

Measurement of15N csa/dipolar cross-correlation rates by means of Spin State Selective experiments

We propose a method for the determination of (15)N csa/dipolar cross-correlation rates based on the measurement of the two apparent transverse (or longitudinal) relaxation rates associated with each component of the nitrogen doublet (N(alpha) and N(beta)). This is achieved by inserting a spin state selective scheme in conventional inverse Carr-Purcell-Meiboom-Gill (or inversion-recovery) pulse sequence which allows for the edition of a HSQC-type spectrum for each of the spin states. Transverse cross-correlation rates necessitate two independent sets of measurements (for N(alpha) and N(beta), respectively), whereas for longitudinal cross correlation rates, besides N(alpha) and N(beta) measurements, the method requires the knowledge of both the (15)N longitudinal auto-relaxation rate and the longitudinal two-spin order (2NzHz) auto-relaxation rate. These additional parameters are mandatory because of the non-exponential behavior of the N(alpha) and N(beta) longitudinal decays. Conversely, the present method does not require any complex manipulation of 2D spectra, the cross-correlation rates being obtained from the difference of the two (N(alpha) and N(beta)) apparent relaxation rates. This approach is applied to (15)N-labelled ubiquitin at two different magnetic fields (9.4 T and 14.1 T).

A High-Speed Low-Power Divide-by-15/16 Dual Modulus Prescaler in 0.6 m CMOS

A new high-speed low-power dual modulus prescaler (DMP) topology is proposed. In this DMP, the synchronous part is designed as a divide-by-3/4 divider using a state-selection scheme. Compared with ...