Fine-tuning of defensive behaviors in the dorsal periaqueductal gray by atypical neurotransmitters

This paper presents an up-to-date review of the evidence indicating that atypical neurotransmitters such as nitric oxide (NO) and endocannabinoids (eCBs) play an important role in the regulation of aversive responses in the periaqueductal gray (PAG). Among the results supporting this role, several studies have shown that inhibitors of neuronal NO synthase or cannabinoid receptor type 1 (CB1) receptor agonists cause clear anxiolytic responses when injected into this region. The nitrergic and eCB systems can regulate the activity of classical neurotransmitters such as glutamate and γ-aminobutyric acid (GABA) that control PAG activity. We propose that they exert a ‘fine-tuning’ regulatory control of defensive responses in this area. This control, however, is probably complex, which may explain the usually bell-shaped dose-response curves observed with drugs that act on NO- or CB1-mediated neurotransmission. Even if the mechanisms responsible for this complex interaction are still poorly understood, they are beginning to be recognized. For example, activation of transient receptor potential vanilloid type-1 channel (TRPV1) receptors by anandamide seems to counteract the anxiolytic effects induced by CB1 receptor activation caused by this compound. Further studies, however, are needed to identify other mechanisms responsible for this fine-tuning effect.

Calculation of parameter ranges for robust gain tuning of power system controllers

This work proposes a computational tool to assist power system engineers in the field tuning of power system stabilizers (PSSs) and Automatic Voltage Regulators (AVRs). The outcome of this tool is a range of gain values for theses controllers within which there is a theoretical guarantee of stability for the closed-loop system. This range is given as a set of limit values for the static gains of the controllers of interest, in such a way that the engineer responsible for the field tuning of PSSs and/or AVRs can be confident with respect to system stability when adjusting the corresponding static gains within this range. This feature of the proposed tool is highly desirable from a practical viewpoint, since the PSS and AVR commissioning stage always involve some readjustment of the controller gains to account for the differences between the nominal model and the actual behavior of the system. By capturing these differences as uncertainties in the model, this computational tool is able to guarantee stability for the whole uncertain model using an approach based on linear matrix inequalities. It is also important to remark that the tool proposed in this paper can also be applied to other types of parameters of either PSSs or Power Oscillation Dampers, as well as other types of controllers (such as speed governors, for example). To show its effectiveness, applications of the proposed tool to two benchmarks for small signal stability studies are presented at the end of this paper.