Constant Admittance Research Articles

Correction of high-frequency (> 0.3 mHz) air pressure effects in gravity time-series

SUMMARY Correcting atmospheric effects in measurements of vertical acceleration is challenging, particularly at frequencies above 0.3 mHz. Corrections based on 4-D atmosphere models should be the most effective, but are limited in temporal and spatial resolutions. So these models are commonly combined with a constant admittance between air pressure and gravity, though the correction can be further improved by allowing a frequency-dependent admittance. This paper studies the effectiveness of such procedures given that air pressure admittance varies with time because of variability in the underlying local atmospheric process, and finds that admittances estimated by cross-spectral analysis gives better results than a constant admittance does. The best results are achieved by combining a 4-D model with admittances estimated from time-series that cover the event of interest.

Fuzzy Q-Learning interaction controller design for collaborative robot

Background: In physical human-robot interaction (pHRI), admittance control is widely used. The most critical thing in admittance control is the configuration of admittance parameters, but a constant admittance value can not meet the needs of interactive indicators smoothness especially. Variable admittance control is a method to overcome this limitation by adjusting the admittance value in real time. This paper proposes a fuzzy Q-learning (FQL) variable admittance control system, which integrates the fuzzy system (FIS) and reinforcement learning method Q-learning. Methods: FIS is used to turn a continuous input state into fuzzy set and Q-learning is used to train the premise strength of fuzzy rules to get the optimal policy of variable admittance value. To verify the performance of this method, an experiment was performed using an AUBO i5 robot. Training trajectory is point-to-point (PTP) trajectory, several interaction variables before and after training by the algorithm are compared to show the validity of algorithm. Results: Experimental results show that the reward converges to a smaller value in about 25 episodes, and the reward of the last five episodes reduces by 68%. The motion trajectory after algorithm training is closer to the ideal min-jerk trajectory and the deviation and mean value of interaction force become smaller. Conclusions: The proposed FQL method can converge in a few episodes and can improve the performance of pHRI by minimizing the jerk based cost function.

Efficient modelling of natural gas pipeline on electromagnetic transient simulation programs

Electromagnetic transient programs (EMTPs) are widely used for simulating electromagnetic transient in power systems. With the increasing interest in integrated energy system (IES), it would be beneficial to extend the scope of EMTP-type application to multi-physics transients in integrated electrical and gas networks. An efficient and accurate model of gas pipeline is proposed in EMTP for the simulation of pneumatic transients. The pipeline is split into a number of segments using spatial discretization. Analogies between pneumatic and electric quantities, such as flow and pressure, current, and voltage, are used to create a circuit representation of pipe segment. The pipeline is represented by a distributed-element model. In order to enhance the computational efficiency, the nodal equation for pipeline model is reformulated. The pipeline model appears as a two-port Norton equivalent with constant admittances. Case studies are performed to demonstrate the accuracy and efficiency of the proposed pipeline model. The implementation of the proposed pipeline model in the EMTP-type program power systems computer aided design (PSCAD) enables the analysis of diverse transients in integrated electrical and gas systems (IEGSs).

A fuzzy adaptive admittance controller for force tracking in an uncertain contact environment

Traditional constant admittance controller (CAC) in uncertain contact environment is highly dependent on environmental location and stiffness, which are always difficult to obtain in most applications. To address this problem, a fuzzy adaptive admittance controller (FAAC) based on fuzzy inference rules is proposed in this paper. Firstly, an adaptive admittance controller (AAC) that can compensate for the admittance parameters in real time based on force error information is proposed. Secondly, a fuzzy logic loop is introduced into the adaptive term of the AAC system to reduce the overshoot when force tracking, thus creating the FAAC. The detailed design method of FAAC is presented, and the stability conditions are analysed. Finally, simulations and experiments are conducted in several dynamic environments to demonstrate the force tracking performance of the proposed controller.

Variable Admittance Control Based on Trajectory Prediction of Human Hand Motion for Physical Human-Robot Interaction

In order to achieve effective physical human–robot interaction, human dynamic characteristics needs to be considered in admittance control. This paper proposes a variable admittance control method for physical human–robot interaction based on trajectory prediction of human hand motion. By predicting the moving direction of the robot end tool under human guidance, the admittance control parameters are adjusted to reduce the interaction force. The end tool trajectory of the robot under human guidance is used for offline training of long and short-term memory neural network to generate trajectory predictors. Then the trajectory predictors are used in variable admittance control to predict the trajectory and movement direction of the robot end tool in real time. The variable admittance controller adjusts the damping matrix to reduce the damping value in the moving direction. Experiment results show that, using the constant admittance method as a benchmark, the interaction force of the proposed method is reduced by 23%, the trajectory error is reduced by 51%, and the operating jerk is reduced by at least 21%, which proves that the proposed method improves the accuracy and compliance of the operation.

Reactive power allocation through the modified Z-bus and Aumann-Shapley method

This paper presents a new method based on the circuit theory and game theory for the allocation of reactive power. The allocation is calculated for each load, identifying and quantifying the responsibility of each reactive source. In the proposed method: the generators, line shunt, and bus shunt are modeled as current sources and loads are modeled as constant admittance, and obtained modified Z-bus matrix using circuit theory, which was coupled to the Aumann-Shapley method for calculating the unitary participation of each current source in the reactive power consumed by each load, considering each one as an independent player of the “reactive power allocation” game. The properties of the Aumann-Shapley method ensure equitable allocation and recovery of the total reactive power. Numerical results applied to the 5-bus and IEEE 30-bus systems are presented, discussed and compared with the other methods to demonstrate the applicability of the proposed method.

Objective Assessment of Human Workload in Physical Human-robot Cooperation Using Brain Monitoring

The notions of safe and compliant interaction are not sufficient to ensure effective physical human-robot cooperation. To obtain an optimal compliant behavior (e.g., variable impedance/admittance control), assessment techniques are required to measure the effectiveness of the interaction in terms of perceived workload by users. This study investigates electroencephalography (EEG) monitoring as an objective measure to classify workload in cooperative manipulation with compliance. An experimental study is conducted including two types of manipulation (gross and fine) with two admittance levels (low- and high-damping). Performance and self-reported measures indicate that a proper admittance level that enhances perceived workload is task-dependent. This information is used to form a binary classification problem (low- and high-workload) with spectral power density and coherence as the features extracted from EEG data. Using a subject-independent feature selection approach, a subject-dependent Linear Discriminant Analysis (LDA) is used for classification. An average classification rate of 81% is achieved that indicates the reliability of the proposed approach for assessing human workload in interaction with varying compliance across the gross and fine manipulation. Furthermore, to validate our proposed objective measure of workload, we have conducted a second experiment composed of both fine and gross motor tasks. Compared to interaction with a constant admittance, a lower EEG-based workload is observed with an open-loop variable admittance controller. This observation is in agreement with the subjective workload score (NASA-TLX).

Multi-Scale Induction Machine Model in the Phase Domain With Constant Inner Impedance

An efficient and accurate multi-scale induction machine model for simulating diverse transients in power systems is developed and validated. Voltages, currents, and flux linkages are described through analytic signals that consist of real in-phase and imaginary quadrature components, covering only positive frequencies of the Fourier spectrum. The stator is modeled in the abc phase coordinates of an arbitrary reference frame whose rotating speed is adjusted by a simulation parameter called shift frequency. When the reference frame is stationary at a zero shift frequency, then the model processes instantaneous signals to yield natural waveforms. When the reference frame is set to rotate at the synchronous frequency of the electric network, then the Fourier spectra of the analytic signals are shifted by this synchronous frequency to become dynamic phasors that allow for efficient envelope tracking. The shift frequency can be adapted during simulation. For any rotor position and independent of the variation of the magnetizing inductances with saturation, the induction machine model appears as a Norton current source with constant inner admittance in the abc phase domain to support the integration with simulators that represent the electric network in the abc phase domain. The analysis of test cases covering diverse transients substantiates the claims made in terms of accuracy and efficiency across different time scales.

Massively Parallel Computation for 3-D Nonlinear Finite Edge Element Problem With Transmission Line Decoupling Technique

Transmission line method (TLM) has been used in 2-D scalar finite-element (FE) analysis due to its parallelism and constant admittance matrix. In this paper, the TLM is extended for the 3-D nonlinear vector FE problem that is more widely used for electromagnetic apparatus in practice. TLM is specially adapted for tetrahedron edge elements to calculate quasi-static electromagnetic field distribution for eddy current problems, and a dummy scalar gauge is applied to make the reduced magnetic vector FE formulation full-ranked and uniquely solvable by TLM. For each element, the nonlinearity is separated by transmission lines and only local small-scale Newton–Rapson iteration is needed, which is suitable for massive parallelization due to the independence between different elements. The TLM is implemented on a many-core GPU for a nonlinear FE power inductor case study, and the comparison of the results with a commercial FE software shows over 50 times speedup with a relative error of less than 2%.

An Efficient Phase Domain Synchronous Machine Model With Constant Equivalent Admittance Matrix

In this paper, a new synchronous machine model is developed for electromagnetic transients program type simulations. The stator circuit is expressed in the abc phase domain. The machine model is represented as a Norton equivalent with a current source in parallel with a constant Norton admittance. The machine equations are reformulated so that the computational effort required for the modeling of the machine is reduced. Test studies demonstrate the accuracy of the proposed synchronous machine model and show that the proposed model is computationally more efficient than the existing constant conductance phase domain model and voltage-behind-reactance model.

EMI based monitoring of early-age characteristics of concrete and comparison of serial/parallel multi-sensing technique

Changes in admittance signatures measured using Electro-Mechanical Impedance (EMI) technique with a lead zirconate titanate (PZT) transducer, embedded in concrete is an indirect estimate of the localised changes in dynamic stiffness of the concrete in the proximity of the sensor. Experiments and observations of the EMI signatures obtained from PZT sensors bonded onto identical plates and embedded in concrete cubes with two sets of curing have been presented. Also, experiments are conducted on a concrete beam embedded with six PZT sensors bonded on carrier plates of differing thickness by subjecting the beam to differential curing. Feature extraction on the admittance signatures is carried out to identify the early age strength gain characteristics in the concrete. EMI measurements have been continued for 28 days until the signatures asymptote to vanishing changes. The contribution of the present work is the application of serial/parallel connected sensors embedded in concrete (in a Multi Input Single Output, MISO mode), that can be typically deployed in a large scale structural health monitoring (SHM) scenario. A novel methodology for separating the electrical and mechanical coupling in a multiplexed sensing scenario is a notable contribution. A hitherto unreported invariant factor which is obtained as the ratio of the parallel and serial admittance signatures is reasoned out and the removal of this results in separating the constant electrical admittance from the mechanical admittance. Well separated resonant peaks in the admittance signature is a pre-requisite for tracking and observing the changes, which is achieved through plates of different thickness resulting in different ultrasonic resonant modes. In the composite EMI signature which is representative of many sensors, individual peaks could be associated with separate sensors and their influencing regions.

Enhanced Model and Real-Time Simulation Architecture for Modular Multilevel Converter

This paper presents i) an equivalent model of the half-bridge modular multilevel converter (HB-MMC) which is suitable for real-time applications, ii) a hybrid central-processing unit/field-programmable gate array (CPU/FPGA)-based architecture for real-time simulation of electromagnetic transients of systems which include HB-MMC, and iii) a novel arrangement for sorting results referred to as the “sub-module (SM) rank list”, which tackles the bottleneck for parallel implementation of the MMC arm model solver on the FPGA. The Adam–Bashforth (AB) method is used for numerical integration of the HB-SM capacitor model. The second-order AB method provides a constant admittance matrix of the HB-MMC and, thus, reduces computational burden while offering the same accuracy as that of the widely used Trapezoidal method. The CPU/FPGA-based architecture is optimized to obtain maximum parallelism of the HB-MMC model implementation, adopting a standard, single-precision, floating-point computational engine. The proposed sorting arrangement is independent of the utilized sorting algorithm and its application to the odd–even bubble sorting scheme is presented in this paper. The proposed architecture offers a simulation time-step of 825 ns while including the sorting module as the SM capacitor voltage-balancing control unit. This enables accurate analysis of MMC controls based on either software-in-the-loop or hardware-in-the-loop approaches. Performance and accuracy of the MMC model and the hybrid CPU/FPGA-based architecture are evaluated based on a set of case studies on a 401-level HB-MMC-based HVDC station and verified based on offline simulation results in the PSCAD/EMTDC environment.

Study on Three-phase Stability Simulation Model of Distributed Generation System for Multi Energy Utilization

Abstract There are many different kinds of energy in future multi-energy system, such as electric, gas, heat and hydrogen. Distributed generation system integrated as microgrid is one of the most important use form of multi-energy system for customer-side. Considering typical grid-connected distributed generation system and three phase unbalanced feature of low-voltage micro-grid, three-phase stability simulation technique is a very important analysis tool for system-level energy optimization management, design of control strategy, structure stability and so on. A unified interface model of grid-connected system for synchronous generator and inverter is discussed in this paper. The unified model is given in three conventional dq coordinates and described by Norton model which is the parallel connection of injection current source and constant admittance matrix. Based on the characteristics of the unified interface model and detailed dynamics of distributed sources, an alternative implicit trapezoidal integration algorithm is developed for the stability simulation of distributed generation system. The significance of the proposed modeling method is validated by test example simulation results.

On the ratio of dynamic topography and gravity anomalies in a dynamic Earth

AbstractGrowing evidence from a variety of geologic indicators points to significant topography maintained convectively by viscous stresses in the mantle. However, while gravity is sensitive to dynamically supported topography, there are only small free‐air gravity anomalies (<30 mGal) associated with Earth's long‐wavelength topography. This has been used to suggest that surface heights computed assuming a complete isostatic equilibrium provide a good approximation to observed topography. Here we show that the apparent paradox is resolved by the well‐established formalism of global, self‐gravitating, viscously stratified Earth models. The models predict a complex relation between dynamic topography, mass, and gravity anomalies that is not summarized by a constant admittance—i.e., ratio of gravity anomalies to surface deflections—as one would infer from analytic flow solutions formulated in a half‐space. Our results suggest that sizable dynamic topography may exist without a corresponding gravity signal.

A search for atmospheric effects on gravity at different time and space scales

We investigate in this paper various approaches to correct gravity changes for the effect of atmospheric pressure changes. Two specific locations are considered: Strasbourg (France) as mid-latitude station, where regular pressure fronts occur and Djougou (Benin) as equatorial station with large thermally driven S1 and S2 waves of planetary extent. We first review the classical approaches based on a constant or frequency-dependent admittance using only local pressure and gravity data. We consider then a model of atmospheric loading and show the barometric admittance in terms of elastic, Newtonian and total load, as a function of the distance from the station. We consider both a 2D pressure model (surface loading) and a 2.5D model, where the density decreases with height (standard atmosphere). Assuming horizontal advection in the atmospheric dynamics, we convert this spatially dependent admittance into a frequency-dependent admittance. Using global pressure data from European Centre for Medium-Range Weather Forecasts (ECMWF) at about 12km spatial resolution and 3h sampling, we compute the model-predicted pressure admittance for Djougou and Strasbourg and we simulate the frequency dependence inferred from gravity and pressure observations below 4 cycle per day. A long gravity and pressure data set (1996–2013) from Strasbourg is used to investigate the low frequency part of the pressure admittance while a common 2.5 year data set (August 2010–February 2013) for Strasbourg and Djougou is then analyzed to investigate the high frequency part of the admittance. In both cases, our results are in close agreement with the predictions inferred from an atmospheric 2.5D loading model with a distance–time relationship due to horizontal advection. The frequency dependence of the barometric admittance is explained by the competing contributions of Newtonian attraction and elastic surface deformation according to the distance from the gravimeter. In the far field (low frequencies), the magnitude of the admittance decreases with frequency because of the combined elasticity effect and Newtonian attraction (when the atmosphere is below the horizon) while, on the contrary, in the near field (high frequencies), elasticity becomes negligible and the pressure admittance mainly decreases with increasing frequency because of the decreasing attraction effect of the atmospheric masses inside the cylindrical pressure cell centered on the sensor location of decreasing radius. In the last part, we show that there is variability in time in the pressure admittance for both stations.

Power flow in PME distribution systems during an open neutral condition

The open neutral condition, in distribution networks, can cause significant damage to customer installations. Due to this, the continuity of the neutral conductor is important to the power utilities. In this paper, a power flow algorithm for three-phase four-wire distribution networks with protective multiple earthing (PME), during an open neutral condition, is presented. This algorithm is based on a modified backwards-forwards technique. Additionally, the return current flow is explicitly modeled. Results from three different distribution feeders with different load unbalance and topology are presented and discussed. Furthermore, the effects of the grounding resistances, the load model (constant admittance or constant power), and the neutral breakage point (abruption point) on the voltage levels, are investigated.

An Efficient Synchronous Machine Model for Electromagnetic Transients

This paper proposes a new synchronous machine model based on the application of Park's transformation to the discretized equations of the phase-domain model. The proposed approach maintains the precision of the phase-domain model and eliminates its computational inefficiencies through a constant admittance matrix. The model includes magnetic saturation. Precision analysis is performed within the accuracy constraints of the surrounding network.

Complex Losses Allocation to Generators and Loads Based on Circuit Theory and Aumann-Shapley Method

This paper presents a new method to allocate active and reactive losses simultaneously to generators and loads. The allocation is calculated for each transmission branch, identifying and quantifying the buses' responsibilities in losses. This is a two-step process. In the first step, generators are modeled as current injections and loads as constant admittances in order to determine generator participations in losses. In the second step, loads are modeled as current sources and generators as constant admittances in order to determine load participations in losses. The Aumann-Shapley and circuit theories are used to calculate the participation of each real and imaginary current component, considering them as independent players in the “complex losses allocation” game. The properties of the Aumann-Shapley method ensure equitable allocation and recovery of the total active and reactive losses. Counter-flow, cross-subsidy, and negative allocation issues are discussed. Numerical results are presented and discussed to demonstrate the applicability of the proposed method.

A Hybrid Network Model for Small Signal Stability Analysis of Power Systems

Small signal stability analysis in a power system is typically concerned with electromechanical oscillations. For this purpose, it is adequate to model the transmission system using a constant admittance matrix. For torsional oscillations and HVDC interactions, the frequency of interest is much higher and the constant admittance representation is not sufficient. This paper proposes a hybrid model, which allows the parts of the transmission network in the vicinity of HVDC converters or any other dynamic devices to be modeled with their dynamics and the remaining parts to be modeled as constant admittances. The proposed hybrid methodology for small signal stability assessment is the main contribution of this paper. The proposed methodology is validated against an electromagnetic transient simulation program (PSCAD/EMTDC) using time responses. The proposed model and two other small signal models are compared against each other in the frequency domain using modal analysis.

Correcting gravimeters and tiltmeters for atmospheric mass attraction using operational weather models

Abstract The Newtonian attraction of the atmosphere is a major source of noise in precise gravimetric measurements. A major part of the effect is eliminated using local air pressure records and constant admittance factors. However, vertical mass shifts under constant surface pressure or distant pressure anomalies are not covered by this technique although they affect the gravimeter. In order to improve the atmospheric correction and to evaluate the horizontal components of attraction as well, the Newtonian attraction is computed based on the spatial density distribution derived from three-dimensional weather models. Operational models from the German Weather Service (DWD) of various scales were used, supplemented by a global data set from the European Centre of Medium Weather Forecast (ECMWF) for comparison. The low temporal resolution and the improper point-mass assumption in the near field are tackled by a cylindrical local model by computing the attraction analytically based on local air pressure records with high temporal resolution. It is shown that a height of at least 50 km and global coverage is required to meet a threshold of 1 nm/s2. Neglecting the upper atmosphere leads to an overestimation of the seasonal gravity signal. At distances greater than 10 ° the time consuming three-dimensional computation can be replaced by a two-dimensional surface pressure approach without significant error. The results show differences up to 20 nm/s2 as compared to the linear regression method. The three-dimensional atmospheric correction significantly reduces noise in the time series, giving more insight into other signals such as hydrological effects or deformation processes.