An Effective Model-Free Predictive Current Control for Synchronous Reluctance Motor Drives

The performances of a model predictive control algorithm largely depend on the knowledge of the system model. A model-free predictive control approach skips all the effects of parameters variations or mismatches, as well as of model nonlinearity and uncertainties. A finite-set model-free current predictive control is proposed in this paper. The current variations predictions induced by the eight base inverter voltage vectors are estimated by means of the previous measurements stored into lookup tables. To keep the current variations information up to date, the three current measurements due to the three most recent feeding voltages are combined together to reconstruct all the others. The reconstruction is performed by taking advantage of the relationships between the three different base voltage vectors involved in the process. In particular, 210 possible combinations of three-state voltage vectors can be found, but they can be gathered together in six different groups. A light and computationally fast algorithm for the group identification is proposed in this paper. Finally, the current reconstruction for the prediction of future steps is thoroughly analyzed. A compensation of the motor rotation effect on the input voltages is proposed, too. The control scheme is evaluated by means of both simulation and experimental evidences on two different synchronous reluctance motors

Motor Parameter-Free Predictive Current Control of Synchronous Motors by Recursive Least-Square Self-Commissioning Model

This article deals with a finite-set model predictive current control in synchronous motor drives. The peculiarity is that it does not require the knowledge of any motor parameter. The inherent advantage of this method is that the control is self-adapting to any synchronous motor, thus easing the matching between motor and inverter coming from different manufacturers. Overcoming the flaws of the existing lookup table based parameter-free techniques, the article elaborates the past current measurements by a recursive least-square algorithm to estimate the future behavior of the current in response to a finite set of voltage vectors. The article goes through the mathematical basis of the algorithm till a complete set of experiments that prove the feasibility and the advantages of the proposed technique

Wasserstein Distributionally Robust Look-Ahead Economic Dispatch

We consider the problem of look-ahead economic dispatch (LAED) with uncertain renewable energy generation. The goal of this problem is to minimize the cost of conventional energy generation subject to uncertain operational constraints. The risk of violating these constraints must be below a given threshold for a family of probability distributions with characteristics similar to observed past data or predictions. We present two data-driven approaches based on two novel mathematical reformulations of this distributionally robust decision problem. The first one is a tractable convex program in which the uncertain constraints are defined via the distributionally robust conditional-value-at-risk. The second one is a scalable robust optimization program that yields an approximate distributionally robust chance-constrained LAED. Numerical experiments on the IEEE 39-bus system with real solar production data and forecasts illustrate the effectiveness of these approaches. We discuss how system operators should tune these techniques in order to seek the desired robustness-performance trade-off and we compare their computational scalability

A sensorless initial rotor position's estimation for permanent magnet synchronous machines

Permanent magnet synchronous motors for the effective start require information about the initial position of a rotor. In this regard, most systems use position sensors, which substantially increase entirely a cost of an electrical drive [1-3]. The aim of this article is to develop a new method, allowing determining the absolute angular position of the permanent magnet synchronous motors' rotor [4,5]. With a certain voltage pulses applied to the motor, its stator is magnetized by currents leakage in the windings. This allows using a special algorithm to calculate the absolute position of the rotor without using any motor parameters [6]. Simulation results prove the simplicity and efficiency of this method for determining an initial position of the permanent magnet synchronous motors' rotor. Thus, this method can be widely used in the electrical industry

Comparison of two novel MRAS strategies for identifying parameters in permanent magnet synchronous motors

Two Model Reference Adaptive System (MRAS) estimators are developed for identifying the parameters of permanent magnet synchronous motors (PMSM) based on Lyapunov stability theorem and Popov stability criterion, respectively. The proposed estimators only need online detection of currents, voltages and rotor rotation speed, and are effective in the estimation of stator resistance, inductance and rotor flux-linkage simultaneously. Their performances are compared and verified through simulations and experiments. It shows that the two estimators are simple and have good robustness against parameter variation and are accurate in parameter tracking. However, the estimator based on Popov stability criterion, which can overcome the parameter variation in a practical system, is superior in terms of response speed and convergence speed since there are both proportional and integral units in the estimator in contrast to only one integral unit in the estimator based on Lyapunov stability theorem. In addition, there is no need of the expert experience which is required in designing a Lyapunov function

siRNA Off-Target Effects Can Be Reduced at Concentrations That Match Their Individual Potency

Small interfering RNAs (siRNAs) are routinely used to reduce mRNA levels for a specific gene with the goal of studying its function. Several studies have demonstrated that siRNAs are not always specific and can have many off-target effects. The 3′ UTRs of off-target mRNAs are often enriched in sequences that are complementary to the seed-region of the siRNA. We demonstrate that siRNA off-targets can be significantly reduced when cells are treated with a dose of siRNA that is relatively low (e.g. 1 nM), but sufficient to effectively silence the intended target. The reduction in off-targets was demonstrated for both modified and unmodified siRNAs that targeted either STAT3 or hexokinase II. Low concentrations reduced silencing of transcripts with complementarity to the seed region of the siRNA. Similarly, off-targets that were not complementary to the siRNA were reduced at lower doses, including up-regulated genes that are involved in immune response. Importantly, the unintended induction of caspase activity following treatment with a siRNA that targeted hexokinase II was also shown to be a concentration-dependent off-target effect. We conclude that off-targets and their related phenotypic effects can be reduced for certain siRNA that potently silence their intended target at low concentrations

Rapid Dopaminergic Modulation of the Fish Hypothalamic Transcriptome and Proteome

Background - Dopamine (DA) is a major neurotransmitter playing an important role in the regulation of vertebrate reproduction. We developed a novel method for the comparison of transcriptomic and proteomic data obtained from in vivo experiments designed to study the neuroendocrine actions of DA. // Methods and Findings - Female goldfish were injected (i.p.) with DA agonists (D1-specific; SKF 38393, or D2-specific; LY 171555) and sacrificed after 5 h. Serum LH levels were reduced by 57% and 75% by SKF 38393 and LY 171555, respectively, indicating that the treatments produced physiologically relevant responses in vivo. Bioinformatic strategies and a ray-finned fish database were established for microarray and iTRAQ proteomic analysis of the hypothalamus, revealing a total of 3088 mRNAs and 42 proteins as being differentially regulated by the treatments. Twenty one proteins and mRNAs corresponding to these proteins appeared on both lists. Many of the mRNAs and proteins affected by the treatments were grouped into the Gene Ontology categorizations of protein complex, signal transduction, response to stimulus, and regulation of cellular processes. There was a 57% and 14% directional agreement between the differentially-regulated mRNAs and proteins for SKF 38393 and LY 171555, respectively. // Conclusions - The results demonstrate the applicability of advanced high-throughput genomic and proteomic analyses in an amendable well-studied teleost model species whose genome has yet to be sequenced. We demonstrate that DA rapidly regulates multiple hypothalamic pathways and processes that are also known to be involved in pathologies of the central nervous system