Outputs System Research Articles

An instant inertia estimated and operation burden considered frequency regulation method for low inertia power systems

The application of virtual inertia (VI) has become a novel solution and new orientation for the frequency regulation of the high variable renewable energy (VRE) penetrated low inertia systems. How to provide a frequency regulation strategy for the system with VI is a key problem. Firstly, the power system is a multi inputs multi outputs (MIMO) system, in which the coupling characteristics of VI control and the primary and secondary frequency controls can’t be ignored. Secondly, the system inertia constant is time-varying and the estimation of it is crucial for gaining a satisfying regulation performance. This paper intends to provide a frequency regulation strategy for this problem. In this work, an Elman neural network (ENN) based inertia estimation with a deadband method is proposed for the identification of the system’s instant inertia. And the Laguerre function-based rate of change of frequency (ROCOF) constrained MIMO-MPC is constructed to provide the collaboration strategy. Then, the control parameters are tuned by the gravitational search algorithm (GSA) considering both the system performance indexes and the operation burden indexes. The proposed strategy is testified based on a three-area power system. The results prove not only the robustness of the controller but also the effectiveness of the ROCOF constraint, the operation burden index, and the instant inertia estimation method.

SNART: Synchrotron Self Absorption Model For Non-relativistic Transients

We present SNART (DeMarchi & Finstad ), software for radio synchrotron self-absorption analysis, a generalized version of the model introduced in Chevalier, Chevalier & Fransson. SNART ingests flux density and frequency observations, fits them jointly, and outputs system physical parameters: magnetic field B, shock radius R, post shock energy U, electron number density n e , circumstellar density ρ CSM, and mass loss degenerate with wind velocity . SNART is written in Python and is publicly available via GitHub. The repository hosts an in-depth derivation of the model and a detailed description of parameter definitions in the literature. SNART is a generalized treatment of synchrotron self absorption that leaves the choice of values for p (the power-law index of the electron distribution), q (shock front acceleration), θ (electron pitch angle, commonly π/2), and f (the “filling factor,” often 0.5) explicit.

Synthesis of control and observation laws power system based on generalized formula Ackermann for MIMO systems

For an electric power system (EPS), as a dynamic system with many inputs and many outputs (Multi Inputs Multi Outputs System − MIMO), compact analytical formulas are obtained for calculating the coefficients of the controller matrix and the observer matrix of the state of the solution of the synthesis problem, providing a given placement of eigenvalues along full state vector. These formulas are generalizations to MIMO systems of the well-known Ackermann formula used to design the control of systems with one input and many outputs (Single Input Multi Outputs System − SIMO). The approach is based on the transformations used in the original multi-step (multilevel) decomposition method, as well as a nondegenerate similarity transformation in the form of the Kalman controllability matrix. The obtained formulas are applicable to dynamic systems, for which the dimension of the state space is a multiple of the dimension of the inputs (controls). This limitation is removed by using the Yokoyama transform. These formulas differ in terms of parameterization of the set of equivalent laws. An example of the synthesis of a control law for a synchronous generator in a complex EPS is considered in order to preserve the existing modes of electromechanical oscillations and meet additional requirements (roughness with respect to disturbances and/or increased sensitivity to changes in controlled parameters in a given region or frequency band).

Thermal management for conjugate heat transfer of curved solid conductive panel coupled with different cooling systems using non-Newtonian power law nanofluid applicable to photovoltaic panel systems

Thermal performance features for a coupled conjugate thermo-fluid system with different cooling configurations (flat channel (F-C), grooved channel (G-C) and impinging jets (I-J)) are explored numerically by using non-Newtonian nanofluid. The numerical work is performed for different Reynolds numbers (100≤Re≤300), index of power law (0.8≤n≤1.2), height (0.1H≤b≤0.6H) and number (2≤N≤9) of corrugation in the G-C system, number (2≤Nj≤9) and distance (5w≤sx≤25w) between jets in the I-J flow system. Different volume fractions (0≤ϕ≤0.04) and particle sizes (20nm≤dp≤80nm) of nanoparticles are used. When systems operating at the highest and lowest Re are compared, 9 K, 11 K and 8 K temperature reduction are achieved for F-C, G-C and I-J cooling systems. However, I-J flow system at higher Re is very effective on the thermal performance improvement when shear thickening fluid is used. For the G-C flow system, increasing the height and number of the corrugation waves resulted in improvement in the thermal performance. Up to 46% increment in the Nu number (average) and reduction of 6.5 K in the average surface temperature are achieved with varying the height of the corrugation while these values are 17% and 1.6 K when wave number is increased. The average Nu number rises by about 32% and temperature drops by about 6.5 K when jet number is varied from 3 to 11, while these values are obtained as 8% and 4 K for when distance between jets are varied from sx=5w to sx=25w. For F-C, G-C and I-J flow systems, average Nu rises by about 15.5% and 14.5% and 16.3% for shear thinning fluid while they become 16.6%, 9.94% and 12.8% for shear thickening fluid at the highest solid volume fraction. As the nanoparticle size is increasing, there is 6% and 7% reduction in the average Nu number. Thermal performance estimations are made with four inputs and four outputs system by using artificial neural networks.

Performance enhancement of hybrid‐SIM for optical wireless downlink communication with aperture averaging and receiver diversity

Error performance of hybrid subcarrier intensity modulation (hybrid-SIM) in optical free-space satellite downlink has been studied in this work. Bit error rate (BER) is improved by aperture averaging and spatial receiver diversity and it is found out be effective in strong turbulence regime. Subsequently, the reduction in scintillation index has been investigated by implementing a single large receiver and an array of point receivers of length n R with the same effective aperture area. Moreover, the BER at different turbulence conditions is compared with minimum shift keying and multiple levels of pulse position modulation pertaining to aperture averaging. Upon analysing the single input multiple outputs (SIMO) system, the desired response is obtained above a certain threshold in average received irradiance. At different zenith angles and turbulence strengths for n R = 4 , the threshold is 4.59 and 3.35 dB, respectively, and it rises by 13.6 and 26.43 dB when n R is increased to 9. This constraint can be exploited to optimise the number of receivers concerning system requirement and availability. Further, the pointing error effects are also investigated for SISO and SIMO systems, which takes into account both atmospheric turbulence and misalignment induced fading.

DAI based wireless sensor network for multimedia applications

In Wireless Multimedia Sensor Network (WMSN), the time critical and delay sensitive applications like video, audio, image demands high bandwidth and transmission resources. The provision of Cognitive Radio (CR) can effectively utilize the available spectrum in the most appropriate way to provide high bandwidth in the Wireless Sensor Network (WSN) environment as Cognitive Radio sensor network (CRSN). The CR features are applicable in WMSN paradigm with required changes in transmission parameter for bandwidth hungry multimedia applications. In this paper, we propose an approach for setting up a cost-efficient and higher data rates communication in Wireless Multimedia Cognitive Radio Sensor Network (WMCRSN). The process analyses power allocation for sensor nodes by dynamic channel modelling and allocates power using multi-agent based Distributed Artificial Intelligence (DAI) in WMCRSN applications. The novelty in the approach lies in analyzing the real-time spectrum sensing outputs system for high data rate wireless multimedia applications. The DAI makes the process of power allocation in a smart way for having low latency based intra and inter cluster communication between sensor nodes. The performance parameters of the network, i.e. probability of detection and false alarm with the modelled error rates are presented. The mathematical analysis and simulation results justifies the feasibility and merits of the proposed method over conventional methods.

FDD Cooperative Channel Estimation and Feedback for 3D Massive MIMO System

In this paper, a downlink cooperative channel estimation scheme is proposed for the three-dimensional massive multiple inputs multiple outputs (3D-mMIMO) system operating in the frequency division duplexing (FDD) mode. In the proposed cooperative scheme, users have to cooperate with each other via device-to-device (D2D) communication protocol to jointly exploit the sparsity structure property of the channel. Motivated by the sparsity property of the mMIMO channel in the angle-time domain, a parametric feedback scheme is proposed, where the feedback overhead is decreased by sending a limited version of the estimated coefficients rather than all the coefficients back to the BS. Then, a compressive sensing (CS) algorithm is proposed, which we named weighted fast iterative shrinkage thresholding (WFISTA). In the WFISTA, we first introduce new weights and threshold function to the original FISTA to enhance its sparsity-undersampling trade-off in the single measurement vector (SMV) case, then we extend the proposed WFISTA to the case of multiple measurement vector (MMV) problem by adopting ReMBo (reduce MMV and boost) strategy. The proposed WFISTA has the ability to estimate the mMIMO system's channel coefficients by exploiting the joint sparsity structure through cooperation among users' equipment (UEs). Complexity analysis and the probability of decreasing the feedback overhead are provided for the proposed cooperative estimation scheme. The simulation results verify the efficiency of the proposed cooperative algorithm scheme compared to several joint channel estimations.

A new constrained PSO for fuzzy predictive control of Quadruple-Tank process

This paper presents a new constrained predictive controller based on TS modelling approach and Particle Swarm Optimization for optimal operation of nonlinear Multi Inputs Multi outputs system. The developed Particle Swarm Optimization algorithm is used to determine the predictive controls by minimizing a constrained multivariable criterion. The TS fuzzy modelling approach is applied to forecast the states of the process and to establish the conditions for the closed-loop stability. At the optimization stage, the proposed PSO provides the control action taking into account stability conditions and constraints. The performances of the developed method are tested during its application in the Quadruple-Tank process.Therefore, the experimental results demonstrate the strategy ability developed to control a nonlinear multivariable process. In addition, the closed-loop performance of the developed method is compared to that obtained with the nonlinear generalized predictive control method.

I2C Sensors System for PLC Using Microcontroller

In general, PLCs has digital inputs and outputs system. The PLC additional system for analog input on the PLC is limited to sensor output in the form of a voltage of 1-5V (or 4mA to 20mA current). The development of I2C-based sensor technology is not suitable for PLCs. In this research, an I2C-based sensors system was designed and made that can be connected to the PLC. Data from the I2C sensor is sent to the DM memory in the PLC via RS232 serial communication. The sensor used was an LDR as a light sensor and a BMP180 sensor to measure atmospheric pressure and room temperature. From the experiment, the results of the LDR sensor were 100% successful and the data transmission from the BMP180 sensor was well recognized in the PLC

Internal Multimodel Control for Nonlinear Overactuated Systems

This paper deals with the synthesis of a novel internal multimodel control designed for nonlinear overactuated systems. The multimodel approach is proposed to deal with system nonlinearity. A base of linear models is considered to describe the nonlinear system in the whole operating domain and then squared by adding virtual outputs. An internal model controller, obtained by a specific inversion method, is proposed for each model of the base. Thus, the global system control parameters are deduced through fusion of the elementary controller parameters by means of two techniques: commutation or residual approach. The case of three inputs/two outputs system is studied to illustrate the ability of both techniques to satisfy a tolerance interval for position error values, overshoot, settling time specifications and robustness requirement.

Laser dimpling process parameters selection and optimization using surrogate-driven process capability space

Remote laser welding technology offers opportunities for high production throughput at a competitive cost. However, the remote laser welding process of zinc-coated sheet metal parts in lap joint configuration poses a challenge due to the difference between the melting temperature of the steel (∼1500°C) and the vapourizing temperature of the zinc (∼907°C). In fact, the zinc layer at the faying surface is vapourized and the vapour might be trapped within the melting pool leading to weld defects. Various solutions have been proposed to overcome this problem over the years. Among them, laser dimpling has been adopted by manufacturers because of its flexibility and effectiveness along with its cost advantages. In essence, the dimple works as a spacer between the two sheets in lap joint and allows the zinc vapour escape during welding process, thereby preventing weld defects. However, there is a lack of comprehensive characterization of dimpling process for effective implementation in real manufacturing system taking into consideration inherent changes in variability of process parameters. This paper introduces a methodology to develop (i) surrogate model for dimpling process characterization considering multiple–inputs (i.e. key control characteristics) and multiple–outputs (i.e. key performance indicators) system by conducting physical experimentation and using multivariate adaptive regression splines; (ii) process capability space (Cp–Space) based on the developed surrogate model that allows the estimation of a desired process fallout rate in the case of violation of process requirements in the presence of stochastic variation; and, (iii) selection and optimization of the process parameters based on the process capability space. The proposed methodology provides a unique capability to: (i) simulate the effect of process variation as generated by manufacturing process; (ii) model quality requirements with multiple and coupled quality requirements; and (iii) optimize process parameters under competing quality requirements such as maximizing the dimple height while minimizing the dimple lower surface area.

Fault actuators detection based on inputs-outputs data mapping: application to a robot manipulator

This paper deals with a fault estimation algorithm to reconstruct faulty inputs of a process under actuators faults. This approach is based on a generic model with outputs/inputs data mapping to reconstruct the faulty inputs. The key idea consists on dynamic parameters identification of this generic model in real time for abrupt and intermittent faults. To apply this approach, these dynamic parameters are estimated basing on the recursive least squares solution obtained from the sampling of the dynamic model along a closed loop tracking trajectory. Indeed, the control loop requires information about the state derivative of the outputs system. For this aim, a dynamic gains sliding mode differentiator is introduced. By using measured signals, the proposed approach is validated on a bi-axis robot manipulator to evaluate its usefulness on actuators faults detection.

Fault actuators detection based on inputs-outputs data mapping: application to a robot manipulator

This paper deals with a fault estimation algorithm to reconstruct faulty inputs of a process under actuators faults. This approach is based on a generic model with outputs/inputs data mapping to reconstruct the faulty inputs. The key idea consists on dynamic parameters identification of this generic model in real time for abrupt and intermittent faults. To apply this approach, these dynamic parameters are estimated basing on the recursive least squares solution obtained from the sampling of the dynamic model along a closed loop tracking trajectory. Indeed, the control loop requires information about the state derivative of the outputs system. For this aim, a dynamic gains sliding mode differentiator is introduced. By using measured signals, the proposed approach is validated on a bi-axis robot manipulator to evaluate its usefulness on actuators faults detection.

Synthesis of mechanisms integrated with motion and force transformation

The synthesis of mechanisms has an important effect in the product development. A mechanism has two basic kinds of functions, i.e. to transform motion and to transform force. However, current methods always focus on either motion synthesis or force synthesis. The paper proposed a dynamic programming-based synthesis of multi-input or multi-output mechanisms with the simultaneous consideration of motion and force transmission. A general function model is proposed with a result of function matrix of mechanisms. After the solving process of single input and single output (SISO) system using dynamic programming algorithm is proposed, the single input and multiple outputs (SIMO) system, and the multiple inputs and single output system (MISO) are also discussed in detail, together with design evaluation. The synthesis of mechanisms for jacking up system in offshore platform is taken as an example, which demonstrates that the methodology is helpful to produce valuable mechanisms.

Robust Model Predictive Control Applied to a WRIG-Based Wind Turbine

This paper proposes a robust nonlinear predictive controller (Robust NPC) applied to a wound-rotor induction generator (WRIG)-based wind turbine. The Taylor series expansion is used to predict the outputs system and the cost function which determines the control law. The objective of the paper is to ensure the WRIG optimum performances in terms of the tracking of the desired trajectory of the rotor speed and the controlling of the rotor current. The nonlinear predictive controller (NPC) cannot ensure the best performances of the system in the presence of the external perturbation. That’s the reason why a perturbation observer (POB) is necessary. It ensures a robustness against the perturbation by predicting its aerodynamic torque. The proposed controller is studied via simulation on a 1.5 MW WRIG-based wind turbine. Good results were obtained with respect to the rotor speed trajectory tracking and rotor current tracking that shows the benefits of using a robust NPC.

Active noise control of rocket engine noise in an engine test facility for quiet nearby communities

The objective of this research project is to develop an Active Noise Control (ANC) system based on the Filtered-X Least Mean Square algorithm. The ANC system developed here will be installed in a rocket engine testing facility of SpaceX Company near McGregor, Texas. As the SpaceX Company’s rocket engines have been increased in their powers, the engine noise from the testing facility is increasing rapidly. Although there is no noise complain currently from the nearby communities in McGregor, concerns are expected in the near future that the noise could possibly disturb people in McGregor. The ANC system can reduce the noise level using a few microphones and speakers connected to a DSP frontend, while a Passive Noise Control system would be much larger and require a higher cost to be implemented. This ANC system is currently implemented as a Single Input and Single Output system in a laboratory, effectively reducing the noise generated from a loudspeaker driven by the recorded rocket engine noise signal. Then, the system will be improved and operated as a Multiple Inputs and Multiple Outputs system to successfully adapt various wind, temperature, and humidity changes, leading to the maximum noise reduction toward McGregor.

Sustainable world through sustainable materials and integrated biorefineries

The present world, with all its advancement, is not a sustainable world, simply because it is based on non-renewable raw materials (non-RRMs). Sustainable world is best expressed in terms of sustainable development and non-RRMs must be replaced by sustainable materials. The sustainable materials needed by modern society are very wide and the main pillars are biofuels and bioproducts. Both pillars are best related through integrated biorefineries (IBRs) formed of related concepts which are very important for the economic development and sustainability of all countries on our planet. Integrated biorefineries include the production of biofuels and bioproducts and utilizing novel technologies. An IBR contains at least two routes: a biochemical route based on a sugar platform and a thermochemical-catalytic route based on a syngas platform. It is a multiple inputs–multi outputs (MIMO) system with design flexibility to accept a wide range of biofeedstock, especially wastes. If the biorefinery consists of only one route/platform, or is limited with regard to MIMO or biofuels/bioproducts produced, then it should be considered an elementary biorefinery (EBR). Sustainable development engineering which is a subsystem of sustainable development (and sustainable world) is more general than Environmental Engineering; and Clean and Green Technology, because it also includes the utilization of RRMs to achieve not only sustainability but also clean environment. An integrated system approach based on system theory is used to analyse sustainable development, sustainable world, sustainable materials, IBRs, EBRs and their interactions.

Multicellular Alamouti scheme performance in Rayleigh and shadow fading

In this paper, we study the performance of two downlink multicellular systems: a multiple inputs single output (MISO) system using the Alamouti code and a multiple inputs multiple outputs (MIMO) system using the Alamouti code at the transmitter side and a maximum ratio combining (MRC) as a receiver, in terms of outage probability. The channel model includes path-loss, shadowing, and fast fading, and the system is considered interference-limited. Two cases are distinguished: constant shadowing and log-normally distributed shadowing. In the first case, closed form expressions of the outage probability are proposed. For a log-normally distributed shadowing, we derive easily computable expressions of the outage probability. The proposed expressions allow for fast and simple performance evaluation for the two multicellular wireless systems: MISO Alamouti and MIMO Alamouti with MRC receiver. We use a fluid model approach to provide simpler outage probability expressions depending only on the distance between the considered user and its serving base station.

Analysis of multi-gigabits signal integrity through clock H-tree

The H-tree interconnect network is frequently used for the clock signal sharing in the microelectronic systems. Due to the increase of complexity and operating processing data speed, these interconnect effects can bottleneck the technological advancement. Hence, more accurate interconnect modelling methods are necessary for electronic designers. For this reason, a simple and accurate ultra-wide band (UWB) model of multilevel distributed interconnection clock trees as a single input multiple outputs (SIMO) system is developed in this article. Very accurate single input single output (SISO) model transfer functions are derived. This method allows the signal integrity prediction regarding the distributed H-tree characteristics including the source and load impedances. In order to demonstrate the relevance of model developed, analyses of two- and three-level tree networks were performed. Distributed H-tree realistic devices formed by sub-millimetre physical length lines for applications for standardised Printed Circuit Board (PCB) interconnections were experimented numerically. The piece of lines constituting the trees is modelled by UWB RLCG network from DC to 8 GHz which takes into account the frequency dispersions and dielectric loss effects. Thus, excellent correlations between simulations and the results from the models proposed were observed both in frequency and time domains regarding 2.5 Gbits/s clock input. Copyright © 2012 John Wiley & Sons, Ltd.

Fault estimation using a polynomial observer: A real-time application

This work has been developed in the context of the faults diagnosis problem for nonlinear systems. The problem is viewed as the estimation of fault signals using extended state observers theory. A differential algebra approach is proposed to determine the observability and diagnosability of the system. A polynomial observer is used, to estimate the faults, for a multiple available outputs system. Other two schemes of nonlinear observers are used in the faults reconstruction process, only for comparison purposes. The first one is a reduced order observer while the second one is a sliding mode observer. The results of a real-time application are shown to illustrate these methodologies. The approaches were tested in the experimental setting Amira DTS200.