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Our objective in this work is to demonstrate how physics-informed neural networks, a type of deep learning technology, can be utilized to examine the mechanical properties of a helicopter blade. The blade is regarded as a one-dimensional prismatic cantilever beam that is exposed to triangular loading, and comprehending its mechanical behavior is of utmost importance in the aerospace field. PINNs utilize the physical information, including differential equations and boundary conditions, within the loss function of the neural network to approximate the solution. Our approach determines the overall loss by aggregating the losses from the differential equation, boundary conditions, and data. We employed a physics-informed neural network (PINN) and an artificial neural network (ANN) with equivalent hyperparameters to solve a fourth-order differential equation. By comparing the performance of the PINN model against the analytical solution of the equation and the results obtained from the ANN model, we have conclusively shown that the PINN model exhibits superior accuracy, robustness, and computational efficiency when addressing high-order differential equations that govern physics-based problems. In conclusion, the study demonstrates that PINN offers a superior alternative for addressing solid mechanics problems with applications in the aerospace industry. [ABSTRACT FROM AUTHOR]

Controlling variable wind speed turbine (VWT) system based on a doubly-fed induction generator (DFIG) is a challenging task. It requires a control law that is both adaptable and robust enough to handle the complex dynamics of the closed control loop system. Sliding mode control (SMC) is a robust control technology that has shown good performance when employed as a passive fault-tolerant control for wind energy systems. To improve the closed control loop of VWT based on DFIG with the aim of improving energy efficiency, even in presence of nonlinearities and a certain range of bounded parametric uncertainties, whether electrically or mechanically, an adaptive passive fault tolerant control (AP-FTC) based on a self-tuning fractional integral sliding mode control law (ST-FISMC) developed from a novel hyperbolic fractional surface is proposed in this paper. ST-FISMC introduces a nonlinear hyperbolic function into the sliding manifold for self-tuning adaptation of control law, while fractional integral of the control law smooths discontinuous sign function to reduce chattering. Additionally, this work introduces an adaptive observer, developed and proved based on a chosen Lyapunov function. This observer is designed to estimate variations in electrical parameters and stator flux, ensuring sensorless decoupling in indirect field-oriented control (SI-FOC) of DFIG. Lyapunov theory is also used to prove stability of states vectors in closed control loop with presence of bounded parameters uncertainties or external disturbances. Simulation results show that the proposed approach offers better performance in capturing optimal wind energy, as well as the ability to regulate active/reactive power and high resilience in presence of occurring parameter uncertainties or external disturbances. [ABSTRACT FROM AUTHOR]

The fluctuations brought by the renewable energy access to the distribution network make it difficult to accurately describe the state space model of the distribution network's dynamic process, which is the basis of the existing dynamic state estimation methods such as the Kalman filter. The inaccurate state space model directly causes an error of dynamic state estimation results. This paper proposed a new dynamic state estimation method which can mitigates the impact of renewable energy fluctuation by considering PV power prediction in establishing distribution network state space model. Firstly, the proposed method mitigates the impact of renewable energy fluctuation by considering PV power prediction in establishing distribution network state space model. Secondly, SVSF filter is introduced to achieve more accurate estimation under noise. The case study and evaluations are carried out based on MATLAB simulation. The results prove that the smooth variable structure filter with photovoltaic power prediction has a better dynamic state estimation effect under the fluctuation of the distribution network compared with the existing Kalman filter. [ABSTRACT FROM AUTHOR]

Supercapacitors (SCs) are an emerging energy storage technology with the ability to deliver sudden bursts of energy, leading to their growing adoption in various fields. This paper conducts a comprehensive review of SCs, focusing on their classification, energy storage mechanism, and distinctions from traditional capacitors to assess their suitability for different applications. To investigate the voltage response of SCs, the existing electrical equivalent circuits are further studied. The analysis is carried forward with the parameter of impedance, which has not so far been addressed. Impedance analysis is essential for a better understanding of SCs as capacitors work on alternating source of supply. The paper also highlights the applications of SCs in electric automobiles and charging stations, showcasing their advantages such as fast charging and higher power density compared to traditional capacitors. Additionally, other applications in areas like the military, medicine, and industry are discussed, demonstrating the versatility of SC technology. [ABSTRACT FROM AUTHOR]

The increasing threat of cyber-attacks on modern power systems highlights the need for a comprehensive examination through simulations. This study conducts an in-depth simulation of cyber-attacks on critical smart grid components, including smart meters, substation automation, and battery management systems, to expose and analyze potential disruptions to power system operations. We identify vulnerabilities that can lead to severe grid instabilities, such as voltage variations, system collapses, and inverter failures. Our analysis underscores the complex interactions between cyber threats and grid components, revealing how disruptions extend beyond mere load interruptions to affect the core infrastructure. We advocate for integrating established cybersecurity frameworks like NIST, ISO/IEC 27001, and IEC 62443, essential in fortifying grid stability against these dynamic threats. Our findings highlight the urgent need for continuous adaptation and enforcement of these frameworks to enhance resilience and ensure the reliability of modern power grids against cyber-attacks. [ABSTRACT FROM AUTHOR]

To solve the delay problem of a unified power quality conditioner (UPQC) system during the separation of the fundamental positive-order components and to better filter out the DC and harmonic components to realize accurate phase locking, a mixed second-and third-order generalized integrator phase-locked loop (MSTOGI-PLL) has been designed to replace the traditional synchronous reference frame phase-locked loop (SRF-PLL). Under the premise of adopting the new phase-locking device of MSTOGI-PLL, the active disturbance rejection control (ADRC) controller or the super-twisting algorithm (STA) sliding mode controller is used in the DC voltage control module instead of the traditional PI controller, and the suitability of the two nonlinear controllers with the MSTOGI-PLL device is investigated. First, the new MSTOGI-PLL device is designed, and the new phase-locking method is applied to make the UPQC realize accurate phase locking under the non-ideal situation of the grid voltage containing unbalance, DC component, harmonics, and so on. Based on the above foundation, the ADRC or STA controller is independently adopted to replace the PI controller to construct the UPQC system with the ADRC + MSTOGI phase-locking device and the second-order STA + MSTOGI phase-locking device. Finally, a simulation comparison is carried out in a Simulink simulation platform regarding the UPQC system under different phase-locking devices, and the simulation results demonstrate that MSTOGI-PLL can successfully filter out the DC component and resolve the phase-locking process delay issue. Additionally, the UPQC system with ADRC + MSTOGI-PLL exhibits superior immunity and response speed to the PI controller and the second-order STA controller. [ABSTRACT FROM AUTHOR]

The elimination of traditional thermal generators and the increase of renewable energy source access reduced the inertia of the power system, and thermostatically controlled loads have the potential to provide ancillary services to the power system. This paper introduces a decentralized control strategy for thermostatically controlled loads (TCLs), which focuses on assisting large-scale TCLs in providing frequency support to power systems while considering energy efficiency ratio and measurement error correction. Initially, the nonlinear relationship between heat flow and TCLs' power is modeled using a polynomial relationship, and the coefficients are determined through a data-driven method to enhance accuracy in TCLs modeling and assess their regulation potential precisely. Subsequently, a decentralized control strategy tailored for power system frequency regulation is developed. To account for measurement errors in TCLs controllers, a measurement error back-correction method is proposed. Simulation examples demonstrate the effectiveness of the proposed control strategy in achieving accurate modeling and control of TCLs and reducing power system frequency fluctuations. [ABSTRACT FROM AUTHOR]

Municipal water supply system (WSS) consist of different pumping stages viz. intake, water treatment plant (WTP) and intermediate pumping station (IPS). Usually, the power supply for WSS is obtained through public power tapping sources. However, this often leads to load shedding and disruption of the water supply. This paper focuses on the concept, considering WSS as a multi-source multi-area microgrid scheme, this includes renewable energy sources (RES) such as solar, wind, etc. Moreover, the study incorporates a Battery Energy Storage System (BESS) and a Diesel Engine Generator (DEG) to provide power supply during peak demand at each pumping station. Frequency control is essential for optimizing system performance. This paper proposes Enhanced Harris Hawks Optimization Algorithm (EHHO) based PID controller for regulating the frequency in the multi-microgrid-based water supply system. The proposed controller is implemented in MATLAB simulation software, and its response is compared with other optimization methods such as Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). Moreover, implementation and comparison of higher degree order controller such as 3DOF-FOPIDN controller and 3DOF-TIDN controllers are tested under PSO method to observe the performance as well as robustness of the controller. The results indicate that the proposed controller provides better performance in controlling the load frequency deviation, thus improving the efficiency and reliability of the multi-microgrid system for consideration of municipal water supply. [ABSTRACT FROM AUTHOR]

To achieve frequency stability and economic efficiency in isolated microgrids, grid operators face a trade-off between multiple performance indicators. This paper introduces a data-driven adaptive load frequency control (DD-ALFC) approach, where the load frequency controller is modeled as an agent that can balance different objectives autonomously. The paper also proposes a priority replay soft actor critic (PR-SAC) algorithm to implement the DD-ALFC method. The PR-SAC algorithm enhances the policy randomness by using entropy regularization and maximization, and improves the learning adaptability and generalization by using priority experience replay. The proposed DD-ALFC method based on the PR-SAC algorithm can achieve higher adaptability and robustness in complex microgrid environments with multiple performance indicators, and improve both the frequency control and the economic efficiency. The paper validates the effectiveness of the proposed method in the Zhuzhou Island microgrid. [ABSTRACT FROM AUTHOR]

To preserve frequency and tie-line power flow within a tolerable range in modern intricate and renewable energy sources (RES) integrated power system, an intelligent, expert, and robust load frequency control (LFC) scheme is requisite. This paper proposes a new load frequency control (LFC) approach using a dual-stage controller composed of fractional-order tilted-integral-derivative (TID) and integer-order proportional-derivative (PD) controllers. The recently developed salp swarm algorithm has tuned the parameters of the controller. The proposed scheme exhibits robustness and fast disturbance rejection performance because the tilted-integral-derivative controller is structured in a fractional-order framework, and transient response is improved due to the proportional-derivative controller. The overall activity of the LFC has been further upgraded by incorporating the flexible AC transmission system (FACTS) device namely thyristor-controlled phase shifter (TCPS) unit and energy storage system called redox flow battery (RFB) units. The proposed control approach is applied to diverse types of multi-area multi-source power systems with thermal, hydro, and wind turbine units along with nonlinear functions namely generation rate constraint (GRC), governor dead band (GDB), and communication delay (CD). The simulation results yield improved frequency regulation activity with and without TCPS and RFB using the proposed control approach when compared with the recently developed LFC approaches. Sensitivity analysis also established the robustness of the proposed control approach. [ABSTRACT FROM AUTHOR]

Striking developments have taken place in feedback control theory after the evolution of the fractional-order (FO) control concept. However, for large-scale (high-order) systems, these well-established FO techniques become rigorous and lead to an infeasible solution. To overcome this issue, this paper proposes a three-fold control policy. The first step finds the optimal reduced-order (low-order) model using Big-Bang, Big-Crunch (BB–BC) optimisation algorithm. Based on the obtained reduced model, the control structure is formulated in the internal model control (IMC) framework. The controller acquires a PID form followed by an additional term and FO integrator. Unlike the FO-PID controller which demands five tuning parameters, the proposed controller requires only two tuning parameters whose evaluation is done on the basis of user specified gain crossover frequency and phase margin. To substantiate the design approach, a detailed simulation study has been carried out, in which the problems of tracking control, disturbance rejection, and time-delay compensation are illustrated. [ABSTRACT FROM AUTHOR]

In a feedback control loop, when there exists a delay in processing the control signal (often called computational delay), it is difficult to stabilize the system, particularly when the system exhibits uncertainty. To solve this problem, we proposed a new robust proportional integral control strategy for a class of uncertain systems exhibiting parametric uncertainty. A two-stage scheme is proposed in which the first stage identifies the worst plant that has the highest chance of facing instability; and in the second stage, based on the worst plant, the tuning parameters of the proportional integral controller are determined using the stability boundary locus approach under the desired closed-loop specifications of gain and phase margins. The efficiency of the proposed scheme is verified for servo and regulatory control problems. [ABSTRACT FROM AUTHOR]

In this paper, a soft computing based scheme is proposed for the model order reduction of single input-single output commensurate fractional-order (FO) systems. The fractional-order system is first converted into an integer order (IO) system. The reduced order model of the corresponding integer order system is then determined via big bang – big crunch (BBBC) optimization algorithm. Finally, the reduced IO transfer function is transferred back to its FO form through an inverse substitution. The proposed approach is substantiated by two numerical examples of different orders. The effectiveness of the technique is demonstrated by the comparison of two performance indices, i.e. integral square error (ISE) and H ∞ error and the response characteristics in time and frequency domain with the existing techniques from the literature. It is revealed that the response of the proposed BBBC based reduced order model is much closer to that of the original higher-order system. [ABSTRACT FROM AUTHOR]

This article presents a state-of-the-art review on automated control of blood sugar, especially for Type 1 diabetic patients. A brief introduction is provided so as to justify how this biomedical issue proves to be a control system problem in sense of blood glucose regulation. Various mathematical models and control strategies that have been used in recent research work for automated insulin delivery are discussed. An attempt has been made to provide a structural survey of research done till date in the development of artificial pancreas system. At the end, a general idea is presented on how control system can be designed for this biomedical control problem by employing Bergman's minimal model for blood glucose regulation and an internal model–based proportional–integral controller is designed. The controller exhibits faster response in maintaining the blood glucose when compared with other existing techniques. [ABSTRACT FROM AUTHOR]