Department of Control (1995 - Present)
electrical engineering
, Wichita State, U.S.A
electrical engineering
, Wichita State, U.S.A
electrical engineering
, Nebraska, U.S.A
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Nowadays, energy management aims to propose different strategies to utilize available energy resources, resulting in sustainability of energy systems and development of smart sustainable cities. As an effective approach toward energy management, non-intrusive load monitoring (NILM), aims to infer the power profiles of appliances from the aggregated power signal via purely analytical methods. Existing NILM methods are susceptible to various issues such as the noise and transient spikes of the power signal, overshoots at the mode transition times, close consumption values by different appliances, and unavailability of a large training dataset. This paper proposes a novel event-based NILM classification algorithm mitigating these issues. The p
In recent years, modern appliances with high electricity demand have played a significant role in residential energy consumption. Despite the positive impact of these appliances on the quality of life, they suffer from major drawbacks, such as serious environmental concerns and high electricity bills. This paper introduces a consolidated framework of load management to alleviate those drawbacks. Initially, benefiting from a demonstrative analysis of home energy consumption data, controllable and responsive appliances in smart home are identified. Then, the energy consumption pattern is reduced and shifted using flexible load models and better utilization of existing energy storage systems. This can be achieved through data mining approaches
In this paper, we introduce a distributed secondary voltage and frequency control scheme for an islanded ac microgrid under event-triggered communication. An integral type event-triggered mechanism is proposed by which each distributed generator (DG) periodically checks its triggering condition and determines whether to update its control inputs and broadcast its states to neighboring DGs. In contrast to existing event-triggered strategies on secondary control of microgrids, the proposed event-triggered mechanism is able to handle the consensus problem in case of asynchronous communication. Under the proposed sampled-data based event-triggered mechanism, DGs do not need to be synchronized to a common clock and each individual DG checks its
A promising approach toward efficient energy management is non-intrusive load monitoring (NILM), that is to extract the consumption profiles of appliances within a residence by analyzing the aggregated consumption signal. Among efficient NILM methods are event-based algorithms in which events of the aggregated signal are detected and classified in accordance with the appliances causing them. The large number of appliances and the presence of appliances with close consumption values are known to limit the performance of event-based NILM methods. To tackle these challenges, one could enhance the feature space which in turn results in extra hardware costs, installation complexity, and concerns regarding the consumer's comfort and privacy. This
Nowadays, energy management aims to propose different strategies to utilize available energy resources, resulting in sustainability of energy systems and development of smart sustainable cities. As an effective approach toward energy management, non-intrusive load monitoring (NILM), aims to infer the power profiles of appliances from the aggregated power signal via purely analytical methods. Existing NILM methods are susceptible to various issues such as the noise and transient spikes of the power signal, overshoots at the mode transition times, close consumption values by different appliances, and unavailability of a large training dataset. This paper proposes a novel event-based NILM classification algorithm mitigating these issues. The p
This paper transforms the Keller–Miksis (KM) model, which is the main equation describing the bubble behavior, into a state space representation and presents a stability condition for the system using the linearized form of the KM equation. The dynamic of the cavitation bubble is analyzed for different gases, and its burst time is measured. Then, a sliding mode controller (SMC) is designed for the nonlinear system to regulate the radius of a single spherical bubble and prevent collapse occurrence, which has a great importance in some industrial applications. The system's robustness in the presence of uncertainties in bubble parameters is one of its most significant control objectives obtained in the controller designed in this paper. A co
The present study proposes a stable control strategy based on the finite-control-set model-predictive control (FCS-MPC) for normal operation and fault conditions in a permanent magnet synchronous generator (PMSG). Voltage should be recovered in grid fault conditions to satisfy the requirements of low voltage ride through (LVRT) in some grid codes. The proposed control method will be based on a control Lyapunov function (CLF) in continuous control law for stabilizing the closed loop system. The cost function will be minimized using at least one discrete switching state in the FCS-MPC. This method prevents a sudden rise in the voltage of the DC-link by storing active power as the rotor inertia. The effectiveness of the proposed control system
A set of coupled Kuramoto oscillators is the main applied model for harmonization study of oscillating phenomena in physical, biological and engineering networks. In line with the previous studies and to bring the analytical results into conformity with further realistic models, in present paper the synchronization of Kuramoto oscillators has been investigated and the necessary and sufficient conditions for the frequency synchronization and phase cohesiveness have been introduced using the contraction property. The novelty of this paper lies in the following:(I) we consider the heterogeneous second-order model with non-uniformity in coupling topology;(II) we apply a non-zero and non-uniform phase shift in coupling function;(III) we introduc
A novel distributed secondary layer control strategy based on average consensus and fractional‐order proportional‐integral (FOPI) local controllers is proposed for the regulation of the bus voltages and energy level balancing of the energy storage systems (ESSs) in DC microgrids. The distributed consensus protocol works based on an undirected sparse communication network. Fractional‐order local controllers increase the degree of freedom in the tuning of closed‐loop controllers, which is required for DC microgrids with high order dynamics. Therefore, here, FOPI local controllers are proposed for enhanced energy balancing of ESSs and improved regulation of the bus voltages across the microgrid. The proposed control strategy operates
Demand side management (DSM) plays a critical role in dealing with power system reliability as one of the main challenges of generating energy in stand-alone residential buildings. This paper introduces a new effective approach of DSM based on predetermined hourly generation and time-varying tariffs to enhance the reliability and quality of a stand-alone energy system. This research focus on two main novelties: 1) analyzing data via clustering method to improve the efficiency and accuracy of DSM, and 2) a state-of-the-art modeling framework DSM for a stand-alone residential building. Looking at first novelty, the well-known linkage-ward clustering method is used for defining time-varying tariffs and in the second novelty the mixed integer l
In many industrial and medical systems, there is a bubble between two elastic walls. On the other hand, the collapse of bubbles is considered a constant source of energy lost and causes system damage. This research is the first attempt to prevent from bubble collapse between two elastic boundaries by using control algorithms. In this paper, first, the nonlinear dynamic model of the bubble between two elastic walls is introduced and then rewritten into a state-space form. The second part of this paper is devoted to the design of the sliding mode controller, where the ultrasonic pressure plays the role of control input and the output is bubble radius. At first, terminal sliding mode control is proposed. Although this method ensures finite-tim
In this paper, a robust fractional-order PID (FOPID) controller is proposed to regulate islanded microgrid (MG) frequency. The considered MG is composed of a photovoltaic system, a wind turbine generation, a diesel generator, a battery energy storage system, the control unit, and loads. Some challenges in islanded MGs such as unpredictable variation in output power of renewable energy sources and model uncertainties, affect the system performance and lead to frequency deviations from the nominal value. For designing the proposed robust controller, the wind power and solar radiation are considered as disturbance inputs. Also, uncertainties are assumed in the inertia constant and the load damping coefficient parameters of the system. The FOPI
This paper presents modification of standard Kalman filter (KF) based on augmented input estimation (AIE) and deadbeat dissipative FIR filtering (DDFF) for maneuvering target tracking. Although KF is a well-known tool in estimation and tracking but it has two weaknesses, disability in maneuvering motions and lack of robustness against temporary model uncertainty. For the first problem, the AIE is proposed to cover both the non-maneuvering and maneuvering parts of motion and so the maneuver detection procedure is eliminated. This model with an input estimation (IE) approach is a special augmentation in the state space model which considers both the state vector and the unknown input vector as a new augmented state vector. Also, KF is based o
Using inverter-based topologies and lack of rotational masses can lead to a noticeable reduction in the inertia of modern systems and have detrimental effects on the resiliency, stability and strengths of microgrids. Effective frequency control ancillary services and modern adaptive control mechanisms can be proposed to resolve the mentioned challenges practically. From this perspective, several flexible and intelligent control approaches have been recently introduced to create a balance between generation and load demand during various operational conditions in low-inertia power systems. This study suggests a supportive collaboration between two distributed generations including virtual inertia of wind turbine generator and fast speed micr
In this letter, the formation control problem of multi-agent systems with directed communication graphs is considered. A novel distributed event-triggered approach, which involves complex Laplacian, is proposed to address the problem. The event condition depends on periodic samplings of agent states, which automatically eliminates the possibility of Zeno behavior. Then, it is shown that, under simple verifiable conditions, the proposed control strategy results in the desired formation of agents. Finally, the results are verified by numerical examples.
Non-intrusive load monitoring (NILM), aims to infer the power profiles of appliances from the aggregated power signal via purely analytical methods. Existing NILM methods are susceptible to various issues such as the noise and transient spikes of the power signal, overshoots at the mode transition times, close consumption values by different appliances, and unavailability of a large training dataset. This paper proposes a novel event-based NILM classification algorithm mitigating these issues. The proposed algorithm (i) filters power consumption signals and accurately detects all events,(ii) extracts specific features of appliances, such as operation modes and their respective power consumption intervals, from their power consumption signal
One of the basic requirements of today's sophisticated world is the availability of electrical energy, and neglect of this matter may have irreparable damages such as an extensive blackout. The problems which were introduced about the traditional power grid, and also, the growing advances in smart technologies make the traditional power grid go towards smart power grid. Although widespread utilisation of telecommunication networks in smart power grid enhances the efficiency of the system, it will create a critical platform for cyber attacks and penetration into the system. Automatic generation control (AGC) is a fundamental control system in the power grid, and it is responsible for controlling the frequency of the grid. An attack on the da
In this paper, we tackle the problem of non-intrusive load monitoring (NILM). The purpose of algorithm NILM, is to disaggregate the total power consumption of a house-hold into individual consumption of appliances by analyzing changes in the power signal using analytical methods. One of the main challenges in this field is the existence of appliances consuming nearly-equal power. Different studies tried to extract and define specific features for these appliances to overcome this challenge. In this research, we incorporate the water consumption patterns of appliances into our analysis to separate otherwise-indistinguishable appliance. More precisely, we perform NILM via an event-based multi-label classification method in which water consump
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