Local Feedback Signals Research Articles

Improving the robustness of distributed secondary control in autonomous microgrids to mitigate the effects of communication delays

Distributed control has been employed in autonomous microgrids (MGs) to attain secondary control goals. However, the reliance of MG’s distributed secondary control on communication makes it vulnerable to degraded performance and the risk of instability due to communication delays. This paper enhances the flexibility of the MG control framework, with each distributed generator incorporating supplementary local feedback signals. This added flexibility strengthens the MG’s ability to counteract disturbances caused by delays and enhances its dynamic performance. The introduction of extra feedback signals has a direct impact on the dynamic response of the MG, leaving its steady-state condition unaffected. In comparison to the methods found in existing literature, the increased flexibility relaxes the inherent trade-off between the objectives of improved transient response and the system’s ability to mitigate disturbances caused by delays. To model the MG, a set of delay differential–algebraic equations (DDAEs) is used. The small-signal linearized model is derived and employed to evaluate the stability of the MG as well as fine-tune the control parameters. The effectiveness of this proposed control structure is demonstrated using the MATLAB/Simulink environment and a controller in the loop (CIL) setup, tested against both fixed universal and asynchronous delays, as well as time-varying delays.

Dynamic spatiotemporal coordination of neural stem cell fate decisions occurs through local feedback in the adult vertebrate brain.

SummaryNeural stem cell (NSC) populations persist in the adult vertebrate brain over a lifetime, and their homeostasis is controlled at the population level through unknown mechanisms. Here, we combine dynamic imaging of entire NSC populations in their in vivo niche over several weeks with pharmacological manipulations, mathematical modeling, and spatial statistics and demonstrate that NSCs use spatiotemporally resolved local feedback signals to coordinate their decision to divide in adult zebrafish brains. These involve Notch-mediated short-range inhibition from transient neural progenitors and a dispersion effect from the dividing NSCs themselves exerted with a delay of 9–12 days. Simulations from a stochastic NSC lattice model capturing these interactions demonstrate that these signals are linked by lineage progression and control the spatiotemporal distribution of output neurons. These results highlight how local and temporally delayed interactions occurring between brain germinal cells generate self-propagating dynamics that maintain NSC population homeostasis and coordinate specific spatiotemporal correlations.

Nutrient-Induced Cellular Mechanisms of Gut Hormone Secretion.

The gastrointestinal tract can assess the nutrient composition of ingested food. The nutrient-sensing mechanisms in specialised epithelial cells lining the gastrointestinal tract, the enteroendocrine cells, trigger the release of gut hormones that provide important local and central feedback signals to regulate nutrient utilisation and feeding behaviour. The evidence for nutrient-stimulated secretion of two of the most studied gut hormones, glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), along with the known cellular mechanisms in enteroendocrine cells recruited by nutrients, will be the focus of this review. The mechanisms involved range from electrogenic transporters, ion channel modulation and nutrient-activated G-protein coupled receptors that converge on the release machinery controlling hormone secretion. Elucidation of these mechanisms will provide much needed insight into postprandial physiology and identify tractable dietary approaches to potentially manage nutrition and satiety by altering the secreted gut hormone profile.

Computational principles of neural adaptation for binaural signal integration.

Adaptation to statistics of sensory inputs is an essential ability of neural systems and extends their effective operational range. Having a broad operational range facilitates to react to sensory inputs of different granularities, thus is a crucial factor for survival. The computation of auditory cues for spatial localization of sound sources, particularly the interaural level difference (ILD), has long been considered as a static process. Novel findings suggest that this process of ipsi- and contra-lateral signal integration is highly adaptive and depends strongly on recent stimulus statistics. Here, adaptation aids the encoding of auditory perceptual space of various granularities. To investigate the mechanism of auditory adaptation in binaural signal integration in detail, we developed a neural model architecture for simulating functions of lateral superior olive (LSO) and medial nucleus of the trapezoid body (MNTB) composed of single compartment conductance-based neurons. Neurons in the MNTB serve as an intermediate relay population. Their signal is integrated by the LSO population on a circuit level to represent excitatory and inhibitory interactions of input signals. The circuit incorporates an adaptation mechanism operating at the synaptic level based on local inhibitory feedback signals. The model’s predictive power is demonstrated in various simulations replicating physiological data. Incorporating the innovative adaptation mechanism facilitates a shift in neural responses towards the most effective stimulus range based on recent stimulus history. The model demonstrates that a single LSO neuron quickly adapts to these stimulus statistics and, thus, can encode an extended range of ILDs in the ipsilateral hemisphere. Most significantly, we provide a unique measurement of the adaptation efficacy of LSO neurons. Prerequisite of normal function is an accurate interaction of inhibitory and excitatory signals, a precise encoding of time and a well-tuned local feedback circuit. We suggest that the mechanisms of temporal competitive-cooperative interaction and the local feedback mechanism jointly sensitize the circuit to enable a response shift towards contra-lateral and ipsi-lateral stimuli, respectively.

Intrinsic regulation of enteroendocrine fate by Numb.

How terminal cell fates are specified in dynamically renewing adult tissues is not well understood. Here we explore terminal cell fate establishment during homeostasis using the enteroendocrine cells (EEs) of the adult Drosophila midgut as a paradigm. Our data argue against the existence of local feedback signals, and we identify Numb as an intrinsic regulator of EE fate. Our data further indicate that Numb, with alpha-adaptin, acts upstream or in parallel of known regulators of EE fate to limit Notch signaling, thereby facilitating EE fate acquisition. We find that Numb is regulated in part through its asymmetric and symmetric distribution during stem cell divisions; however, its de novo synthesis is also required during the differentiation of the EE cell. Thus, this work identifies Numb as a crucial factor for cell fate choice in the adult Drosophila intestine. Furthermore, our findings demonstrate that cell-intrinsic control mechanisms of terminal cell fate acquisition can result in a balanced tissue-wide production of terminally differentiated cell types.

Fuzzy based damping controller for TCSC using local measurements to enhance transient stability of power systems

This paper proposes a local fuzzy based damping controller (LFDC) for thyristor controlled series capacitor (TCSC) to improve transient stability of power systems. In order to implement the proposed scheme, detailed model of TCSC, based on actual behavior of thyristor valves, is adopted. The LFDC uses the frequency at the TCSC bus as a local feedback signal, to control the firing angle. The parameters of fuzzy controller are tuned using an off-line method through chaotic optimization algorithm (COA). To verify the proposed LFDC, numerical simulations are carried out in Matlab/Simpower toolbox for the following case studies: two-area two-machine (TATM), WSCC three-machine nine-bus and Kundur’s two-area four-machine (TAFM) systems under various faults types. In this regard, to more evaluate the effectiveness of the proposed method, the simulation results are compared with the wide-area fuzzy based damping controller (WFDC). Moreover, the transient behavior of the detailed and phasor models of the TCSC is discussed in the TATM power system. The simulation results confirm that the proposed LFDC is an efficient tool for transient stability improvement since it utilizes only local signals, which are easily available.

A Composite Strategy for Power Oscillation Damping Control Using Local and Wide Area Feedback Signals

Non-local measurements from wide area measurement systems can be used to synthesize feedback signals for FACTS or HVDC based power oscillation damping controllers. Although non-local feedback signals may have better damping influence than local feedback signals, they involve greater complexity and reduced robustness due to the possibility of partial or complete loss of communication. A composite control strategy is proposed in this paper, which uses both local and non-local feedback channels to achieve enhanced damping and improved robustness. Special local signals and their non-local equivalents are identified for series reactive and shunt real power injection devices, which facilitate the design of controllers with a simple structure and fewer parameters. Unlike modal speed signals, synthesis of these signals does not require an online eigen-solution. Case studies are presented which demonstrate the efficacy and robustness of this strategy.

Optical spike-timing-dependent plasticity with weight-dependent learning window and reward modulation.

Optical spike-timing-dependent plasticity (STDP) synapses form the basis of learning in photonic neuromorphic system. In biological neural systems, STDP synapses generally have multiplicative boundary mechanisms, and can be modulated by a third factor such as dopamine. Analogously, we introduce a third factor into optical STDP: The current-injection of semiconductor optical amplifiers can be modified in an adaptive way according to local or global feedback signals. The local one is present synaptic weight, which elicits an optical weight-dependent STDP, while the global one is a reward signal. We demonstrate that the optical weight-dependent STDP can emulate the behavior of biological STDP synapses more closely, and can be seen as an intermediate configuration between additive and multiplicative STDP, which balances stability and competition among synapses. Simulation studies with scalable photonic neurons further show that optical STDP with reward modulation enables reward-based reinforcement learning.

Early recurrent feedback facilitates visual object recognition under challenging conditions.

Standard models of the visual object recognition pathway hold that a largely feedforward process from the retina through inferotemporal cortex leads to object identification. A subsequent feedback process originating in frontoparietal areas through reciprocal connections to striate cortex provides attentional support to salient or behaviorally-relevant features. Here, we review mounting evidence that feedback signals also originate within extrastriate regions and begin during the initial feedforward process. This feedback process is temporally dissociable from attention and provides important functions such as grouping, associational reinforcement, and filling-in of features. Local feedback signals operating concurrently with feedforward processing are important for object identification in noisy real-world situations, particularly when objects are partially occluded, unclear, or otherwise ambiguous. Altogether, the dissociation of early and late feedback processes presented here expands on current models of object identification, and suggests a dual role for descending feedback projections.

Adaptive-length pendulum smart tuned mass damper using shape-memory-alloy wire for tuning period in real time

Due to the shift in paradigm from passive control to adaptive control, smart tuned mass dampers (STMDs) have received considerable attention for vibration control in tall buildings and bridges. STMDs are superior to tuned mass dampers (TMDs) in reducing the response of the primary structure. Unlike TMDs, STMDs are capable of accommodating the changes in primary structure properties, due to damage or deterioration, by tuning in real time based on a local feedback. In this paper, a novel adaptive-length pendulum (ALP) damper is developed and experimentally verified. Length of the pendulum is adjusted in real time using a shape memory alloy (SMA) wire actuator. This can be achieved in two ways i) by changing the amount of current in the SMA wire actuator or ii) by changing the effective length of current carrying SMA wire. Using an instantaneous frequency tracking algorithm, the dominant frequency of the structure can be tracked from a local feedback signal, then the length of pendulum is adjusted to match the dominant frequency. Effectiveness of the proposed ALP-STMD mechanism, combined with the STFT frequency tracking control algorithm, is verified experimentally on a prototype two-storey shear frame. It has been observed through experimental studies that the ALP-STMD absorbs most of the input energy associated in the vicinity of tuned frequency of the pendulum damper. The reduction of storey displacements up to 80 % when subjected to forced excitation (harmonic and chirp-signal) and a faster decay rate during free vibration is observed in the experiments.

Fault‐tolerant control design to enhance damping of inter‐area oscillations in power grids

SUMMARYIn this paper, passive and active approaches for the design of fault‐tolerant controllers (FTCs) are presented. The FTCs are used to improve the damping of inter‐area oscillations in a power grid. The effectiveness of using a combination of local and remote (wide area) feedback signals is first demonstrated. The challenge is then to guarantee a minimum level of dynamic performance following a loss of remote signals. The designs are based on regional pole placement using linear matrix inequalities. First, a passive FTC is proposed. It is shown that the computation of the controller reduces to the solution of bilinear matrix inequalities. An iterative procedure is then used to design the controller. Next, as an alternative to active, time‐varying controllers, one for each fault scenario, we propose an approach for the design of a ‘minimal switching’ FTC in which only one controller is designed, but where a simple switch is incorporated into the controller structure. A case study in a linear and nonlinear Nordic equivalent system is presented to show that the closed‐loop response using a conventional control design could deteriorate the performance or even destabilize the system if the remote signals are lost and to demonstrate the effectiveness of the proposed FTC designs. Copyright © 2013 John Wiley & Sons, Ltd.

The Arabidopsis Ortholog of Rice DWARF27 Acts Upstream of MAX1 in the Control of Plant Development by Strigolactones

Strigolactones (SLs) are carotenoid-derived plant hormones that regulate shoot branching, secondary growth, root development, and responses to soil phosphate. In Arabidopsis (Arabidopsis thaliana), SL biosynthesis requires the sequential action of two carotenoid cleavage dioxygenases, MORE AXILLARY GROWTH3 (MAX3) and MAX4, followed by a cytochrome P450, MAX1. In rice (Oryza sativa), the plastid-localized protein DWARF27 (OsD27) is also necessary for SL biosynthesis, but the equivalent gene in Arabidopsis has not been identified. Here, we use phylogenetic analysis of D27-like sequences from photosynthetic organisms to identify AtD27, the likely Arabidopsis ortholog of OsD27. Using reverse genetics, we show that AtD27 is required for the inhibition of secondary bud outgrowth and that exogenous application of the synthetic SL GR24 can rescue the increased branching phenotype of an Atd27 mutant. Furthermore, we use grafting to demonstrate that AtD27 operates on a nonmobile precursor upstream of MAX1 in the SL biosynthesis pathway. Consistent with the plastid localization of OsD27, we also show that AtD27 possesses a functional plastid transit peptide. We demonstrate that AtD27 transcripts are subject to both local feedback and auxin-dependent signals, albeit to a lesser extent than MAX3 and MAX4, suggesting that early steps in SL biosynthesis are coregulated at the transcriptional level. By identifying an additional component of the canonical SL biosynthesis pathway in Arabidopsis, we provide a new tool to investigate the regulation of shoot branching and other SL-dependent developmental processes.

Power Oscillation Damping Improvement using an Iterative Fault-tolerant Wide-area Control Approach

The effectiveness of using both local and remote (wide-area) feedback signals for power oscillation damping (POD) controllers is first demonstrated. The challenge is then to guarantee a minimum level of dynamic performance with only the local signals following a sudden loss of remote signals. A case study on the Nordic equivalent system is presented to show that the closed-loop response could deteriorate if the remote signals are lost. A fault-tolerant control (FTC) design methodology is presented to solve this problem and ensure an acceptable performance level even in case of loss of remote signals. The FTC design methodology is based on simultaneous regional pole-placement for normal and loss of (remote) signals conditions. First the problem is solved non-iteratively using a Linear Matrix Inequality (LMI) approximation and then it is shown that, although this procedure is linear and easy to implement, it has a drawback: the value of one of the control matrices is fixed before calculating the others. An iterative procedure is presented instead to ameliorate this problem and potentially improve the damping of the system. Case studies on the Nordic equivalent system confirm that the proposed iterative fault tolerant controller (FTCit) is able to improve performance against the non-iterative fault tolerant controller (FTC) and produce acceptable performance in case of loss of the remote signals while the response with a CC is unacceptable if a fault occurs.

Parameters tuning of power system stabilizers using improved ant direction hybrid differential evolution

The tuning of the PSS parameters for a multi-machine power system is usually formulated as an objective function with constraints consisting of the damping factor and damping ratio. A novel mixed-integer ant direction hybrid differential evolution algorithm, called MIADHDE, is proposed to solve this kind of problem. The MIADHDE is improved from ADHDE by the addition of accelerated phase and real variables. The performances of three different objective functions are compared to the MIADHDE in this paper. Both local and remote feedback signals of machine speed deviation measurements can be selected as input signals to the PSS controllers in the proposed objective function. The New England 10-unit 39-bus standard power system, under various system configurations and loading conditions, is employed to illustrate the performance of the proposed method with the three different objective functions. Eigenvalue analysis and nonlinear time domain simulation results demonstrate the effectiveness of the proposed algorithm and the objective function with a remote signal.

Power Oscillation Damping Using FACTS Devices: Modal Controllability, Observability in Local Signals, and Location of Transfer Function Zeros

Modal controllability, observability, and transfer function zeros play an important role in the selection of candidate locations and feedback signals for flexible ac transmission systems (FACTS)-based power swing damping controllers. This paper investigates location of zeros of the transfer function corresponding to FACTS devices and certain local feedback signals. Signals synthesized from locally measured signals are derived that can give good pole-zero separation. It is also shown that relative modal controllability of FACTS controllers at various locations can be directly inferred from relative modal observability in certain signals at those locations. These signals are identified for various FACTS devices. Case studies using detailed model are used to validate the results.

Decentralized control of a class of large-scale nonlinear systems using neural networks

This paper designs a decentralized neural network (NN) controller for a class of nonlinear large-scale systems, in which strong interconnections are involved. NNs are used to handle unknown functions. The proposed scheme is proved guaranteeing the boundedness of the closed-loop subsystems using only local feedback signals.

Global damping of noise or vibration fields with locally synthesized controllers.

A locally synthesized controller (LSC) is one that uses a local feedback signal in a noise or vibration field (VF) to synthesize the actuation signal. The global damping of a VF by available LSCs requires sensor-actuator collocation. This study presents a LSC for the global damping of a VF without requiring sensor-actuator collocation, which is important to noise control applications where a sensor may be placed away from an actuator to avoid the near field effects. It is proven that the LSC damps the entire VF instead of just a local feedback loop. This is different from other LSCs that may control local feedback loops without damping the VFs. A decentralized control law is presented here to extend the LSC to a decentralized damping system using multiple actuators.

Switching control for power systems with line losses

The control of initial swinging due to large power system disturbances justifies the use of controllers in a full-on full-off mode. Current control designs are based on linear controllers with saturating elements using local feedback signals. The paper develops a switching control strategy for the damping of power system interarea modes using multiple FACTS devices and angle transducers. The design is based on maximising the convergence rate of a system kinetic energy function. The function provides correct analysis of lossy systems so that the the load modulation by static VAr compensators, as well as the damping from controlled series capacitors, can be incorporated. Fast suppression of oscillations using multiple FACTS devices is demonstrated.

High-order single-stage single-bit oversampling A/D converter stabilized with local feedback loops

A new method for the stabilization of high-order (>2) single-stage single-bit oversampling A/D converters is proposed. In this approach, the stability of the modulator is achieved by preventing any unbounded increase in the internal node-voltages through the insertion of local feedback signals inside the modulator loop. In the past, absolute bounds for stability have been derived for the first-order converter. This property is exploited in stabilizing a higher order loop by activating local first-order loops as soon as the internal integrators overload. With local feedback, individual integrators are prevented from saturating and the output voltages are within the proper bounds. The error caused by the local feedback signals is cancelled by feeding these signals through alternate signal paths, in a way similar to the quantization noise cancellation mechanism in a MASH architecture. Since the frequency of overloading can be made very low by proper design, the effect of imperfect cancellation due to mismatches in the two signal paths caused by the modulator nonidealities is quite small. Hence, compared to the inherently stable MASH architectures, the proposed approach achieves stability and is yet much less sensitive to component mismatches. In a sampled data environment where the integrator is realized using op amps, this translates into a low op amp gain requirement. Simulation results confirm that third order modulators using op amps with gain as low as 50 achieve a peak signal-to-noise ratio (SNR) of about 83 dB with an oversampling ratio of 64. This is less than 1 dB from the SNR achieved with infinite op amp gain. >

Design of synchronous generator excitation controllers in multimachine power systems using inverse Nyquist array

Using a four-machine power system as an example, a basis for a systematic procedure is described for determining the feedback-gain settings of excitation controllers in a multimachine system over a wide spectrum of system-loading conditions. For illustrative purposes, electrical power and speed are used as the local feedback signals on each machine in addition to voltage feedback, whose gain setting is assumed fixed. For a given loading condition the inverse Nyquist array (i.n.a.) method is employed to estimate a range of feedback-gain settings for dynamic stability. For all machines of interest, a set of fixed gain settings is then chosen which provides a satisfactory small-signal dynamic performance over the range of system loading conditions. Some advantages of this application of the i.n.a. method are highlighted.