This paper presents the design and analysis of two permanent magnet generators with dual-wound stators for aviation applications. The generators have a radial-flux structure with a surface-mounted permanent-magnet rotor. The rotor magnet arrangement generates magnetic fields with double dominant space harmonics and a different number of poles. The stator has dual windings corresponding to different pole numbers. Two stator windings are magnetically decoupled, allowing them to be electrically loaded separately. The generators have a nominal power of 650 kW at 15,000 rpm. A developed 2 D analytical method and a 2D finite element method are used for the design and analysis of radial-flux permanent-magnet generators with a dual-wound stator.

This paper presents a graph theory based method for optimally placing in-series transmission line actively controlled blocking devices for the mitigation of high-altitude electromagnetic pulses (HEMPs), as well as a comparison of controller requirements for global and local optimal control laws. The complexity of the interconnected transmission lines form collections of fractal antennas that readily receive power from HEMP signals. These fractal antennas are described as graph cycles. Placement decisions are achieved by determining all cycles within a graph representing a power grid and counting how often each transmission line appears in these cycles. The transmission lines with the highest occurrences in the cycles are protected first. The cycle blocking method provides a close approximation to the minimum number of required blocking devices (predicted 4 vs. true 3 for the global control solution and 12 vs. true 11 for the local control solution) of the all-permutations baseline test case. In comparison, the genetic algorithm (GA) yields a minimal placement with 5 controllers for the global controller and 13 for the local controller. This is in contrast to the 15 out 15 placements required to meet the bounding case criterion. That is, mitigation of the E3 HEMP disturbance may be guaranteed if all edges are protected in the system (Lehman et al., 2025). In addition, the required computation time for each method has important consequences. The all-permutations case performs 16⋅215=524,288 iterations to find the optimal solution, the GA performs 190,464 iterations for the global control solution and 286,720 iterations for the local control solution while the graph theory method performs 240 iterations for both the global and local control schemes—an iteration reduction of 3 orders of magnitude from the GA and all-permutations solutions.

As multiple-degree-of-freedom (3-DOF) wave energy converters (WECs) have demonstrated the ability to produce more power than single-degree-of-freedom devices, the challenge of designing buoys for efficient energy harvesting has increased in complexity. In this paper, a cylindrical WEC is designed to naturally resonate in surge, pitch, and heave modes at a specific target frequency of 0.2 Hz. By utilizing a penalty-based optimization method to balance buoyancy requirements with natural resonance, the design achieves minimal control force input, thereby reducing fluctuations in energy output and local energy storage requirements. The performance is evaluated under irregular sea states using a Bretschneider spectrum. Results indicate that a buoy optimized to naturally resonate at the modal frequency of a sea state provides consistent power with significantly reduced reactive power demand compared to non-optimized designs.

This paper introduces a reinforced learning-based supervisory control architecture that oversees multiple Recursive Least Squares (RLS) based self-tuning pump controllers and determines when each loop is permitted to adapt its gains. The supervisor learns adaptation policies that minimize interaction between loops while preserving responsiveness to changing hydraulic conditions. A two-loop pump station simulation is used to evaluate performance under product changes and transient flow disturbances. The results show that the supervisory layer reduces the number of simultaneous adaptation events by over 70%, leading to a 32% lower pressure-tracking error and 45% fewer gain-induced oscillations compared to conventional independent adaptive control. The reinforcement learning policy converges within 15 training episodes, resulting in stable adaptation scheduling and seamless transitions. The key novelty of this work lies in introducing decentralized reinforcement-learning-based coordination for adaptive pump control, enabling supervisory decision-making that actively prevents interference between controllers during transients. This approach provides a scalable and lightweight solution for coordinating multi-loop pump stations, enhancing robustness and operational performance in real-world pipeline systems.

In large-scale fluid transport systems, distributed pump and valve stations must coordinate their operations to prevent overpressure while minimizing energy use and control effort. This paper presents a communication-aware, game-theoretic coordination framework in which stations act as rational agents that iteratively adjust operating setpoints based on locally computed utilities. Existing station-level pressure controllers regulate local pressures and flows, while a slower supervisory negotiation layer governs inter-station coordination using steady-state hydraulic surrogates derived from pump affinity laws and pipeline loss relationships. The proposed framework does not rely on centralized optimization or exhaustive enumeration of strategies. Instead, stations update setpoints sequentially, evaluating incremental changes in utility to determine beneficial adjustments and detect equilibrium conditions. Cooperative behavior emerges naturally when communication is available, enabling stations to internalize the hydraulic impact of their actions on neighboring stations. When communication is lost, the system transitions seamlessly to a non-cooperative mode in which each station optimizes its local objective while maintaining safe operation. Simulation studies conducted on a multi-station pipeline with mixed actuator types demonstrate measurable performance improvements over fixed-setpoint operation. Cooperative coordination reduces total system energy usage from 39.6 MW to 38.8 MW while increasing average control valve openness from 60.4% to 63.7%. Non-cooperative operation converges more rapidly but results in higher energy consumption (39.2 MW) and greater valve throttling. Under partial communication loss, the system preserves near-cooperative energy performance (38.8 MW) with a modest increase in convergence time, demonstrating robustness to degraded communication. Across all simulated scenarios, the iterative game converged to stationary operating points consistent with Nash-equilibrium behavior in non-cooperative settings and Pareto-stationary solutions in cooperative communication settings.

This paper presents a comparison of methods to determine the minimum number of placement locations for neutral blocking, global linear quadratic regulator (G-LQR), and local linear quadratic regulator (L-LQR) controllers throughout a power grid to prevent transformer saturation during the onset of an E3 high-altitude electromagnetic pulse (HEMP) disturbance. Different device placement configurations yield different efficacies in E3 HEMP mitigation. The first placement method discussed is a genetic algorithm (GA), which serves as a baseline optimizer test case. The scaling and run time of the GA depend on the complexity of the objective function and often times becomes intractable as the count of transformers on the grid increases. As a scalable alternative, this paper introduces the novel nodal elimination method, where a power grid is represented as a graph and critical nodes based on node degree are removed one at a time. Unlike the GA, which may run anywhere from O(1) to O(nn) depending on function complexity, the nodal elimination method is guaranteed to run in O(n). The novelty of this method is in its application to the power grid for HEMP E3 mitigation. The nodal elimination method identifies optimal placement locations with three orders of magnitude fewer iterations than the GA, demonstrating its viability and computational efficiency for optimal neutral blocking device placements. It is shown that with centralized and decentralized LQR controllers on a 20-bus and 150-bus grid, the nodal elimination method also finds solutions that require fewer controllers than the GA solutions.

This paper presents a novel approach for protecting transformers during an E3 HEMP insult as well as the associated technology-agnostic voltage, power, energy storage, and bandwidth requirements of various control laws. The mitigation is performed by placing a controlled voltage supply in series with the primary winding of a transformer. The controlled voltage supply is subjected to four control laws: an integral controller (capacitor), a linear quadratic regulator (LQR), a nonlinear energy storage optimal feedforward control law, and a Hamiltonian feedback control law. The research gap addressed is that most E3 mitigation discussions emphasize neutral-side blocking, whereas transmission-level (high-side) assets may offer a lower-upgrade pathway in some grids and require different actuator sizing and control structure. The results show that the Hamiltonian feedback control law performs the same as the energy storage optimized control law and requires the same specifications. Both of these control laws require less than 30 kV of control effort, 0 W of power, 0 kWh of energy storage, and 16 Hz of bandwidth. This suggests that the Hamiltonian feedback control law is an energy storage optimized feedback control law. These specifications should be considered bounds to the requirements, as power and energy storage requirements will change, depending on the efficiency of the actuator chosen to implement the control laws. These two controllers outperform the blocking capacitor and LQR solutions, despite having significantly less stringent specifications.

Securing the power grid is of extreme concern to many nations as power infrastructure has become integral to modern life and society. A high-altitude electromagnetic pulse (HEMP) is generated by a nuclear detonation high in the atmosphere, producing a powerful electromagnetic field that can damage or destroy electronic devices over a wide area. Protecting against HEMP attacks (insults) requires knowledge of the problem’s bounds before the problem can be appropriately solved. This paper presents a collection of analyses to determine the basic requirements for controller placements on a power grid. Two primary analyses are conducted. The first is an inverted controllability analysis in which the HEMP event is treated as an unbounded control input to the system. Considering the HEMP insult as a controller, we can break down controllability to reduce its influence on the system. The analysis indicates that either all but one neutral path to ground must be protected or that all transmission lines should be secured. However, further exploration of the controllability definition suggests that fewer blocking devices are sufficient for effective HEMP mitigation. The second analysis involves observability to identify the minimum number of sensors needed for full-state feedback. The results show that only one state sensor is required to achieve full-state feedback for the system. These requirements suggest that there is room to optimize controller design and placement to minimize total controller count on a power grid to ensure HEMP mitigation. As an example, the Horton et al. system model with 15 transformers and 15 transmission lines is used to provide a baseline comparison for future optimization studies by running all permutations of neutral and transmission line blocking cases. The minimum number of neutral controllers is 8, which is approximately half of the bounding solution of 14. The minimum number of transmission line controllers is 3, which is one-fifth of the bounding solution of 15 and less than half of the required neutral controllers.

This paper introduces a novel control archetype designed to mitigate high-altitude electromagnetic pulse (HEMP) E3 disturbances on the power grid, as well as information on performance and specifications of different control laws for the controller archetype. This method of protection has been overlooked in the literature until now. A controlled voltage supply is placed on the load-side of a transformer, diverting unwanted power from the transformer core to prevent saturation. The controlled voltage source is modeled using four control laws: an integral controller (capacitor), Linear Quadratic Regulator (LQR), an energy storage minimized feedforward control law, and a Hamiltonian feedback law. Results show that the Hamiltonian feedback law and the energy storage minimization feedforward control law both flat-line magnetic flux with similar actuator requirements. The LQR approach requires less energy storage than the other two laws, depending on control tuning, as it allows greater exogenous current flow through the neutral path to ground. This leads to further optimization opportunities based on acceptable exogenous current levels. A sweep of different LQR gains revealed a reduction of approximately 32% in minimum control effort, 47% in minimum power to maintain saturation bounds, 20% in energy storage requirements, and 59% in required controller bandwidth. Voltage and bandwidth requirements of the load-side controller are comparable to neutral blocking requirements with energy and power requirements being higher for the load-side controller. This, however, comes with the benefit of being able to use pre-existing assets—neutral blocking devices have not been deployed. Additionally, the load-side blocking capacitor degrades transformer performance compared to the unmitigated system.

This paper explores the use of a solid state transformer (SST) to mitigate the E3A component of a high-altitude electromagnetic pulse (HEMP) insult using external energy storage optimal control techniques. In lieu of conventional passive blocking devices or feedback-controlled energy storage devices, a novel implementation of Hamiltonian error tracking is utilized to develop a feedback control law for the variable converter ratio in an SST. The findings of the simulations performed in this paper suggest that additional energy storage is not necessary to protect an individual load from a HEMP insult. The simulations performed examine the response of a single-phase SST connected to a single voltage source on a long transmission line on the one side and a single linear resistor on the other. The control law is specifically developed for the late-time, low-frequency portion of a HEMP insult, namely the E3A components. The Hamiltonian error-based converter ratio control law is compared with nonlinear optimal feedforward controls to show that the HSSPFC is an external energy storage optimal controller.

The purpose of this paper is to investigate high-altitude electromagnetic pulse (HEMP) insult mitigation strategies. State-of-the-art solutions currently endorse capacitor blocks on the neutral path. These devices cause system ringing which introduces unnecessary stress on the electrical grid and adjacent components. The scope of this paper is to explore and contrast five different control laws. Performance metrics for this trade study of control laws look at minimizing: i) magnetic core flux saturation, ii) voltage and control effort ringing/oscillations, iii) required energy storage, and iv) transient decay. Additionally, minimizing control effort does not necessarily imply minimized energy storage. Highlights for the results of two of the potential control designs contrast a modern linear quadratic regulator (LQR) feedback controller with a novel Hamiltonian feedback control. The novel controller produced minimal amount of energy storage required to mitigate the HEMP insult.

Pipeline transportation of petroleum products remains one of the safest and most efficient methods of bulk energy delivery, yet overpressure events continue to pose serious operational and regulatory challenges. Traditional fixed-gain PI controllers, commonly used with centrifugal pump drives, cannot adapt to varying product densities or transient disturbances such as valve closures that generate water hammer. This paper proposes a self-tuning adaptive controller based on Recursive Least Squares (RLS) parameter estimation to improve safety and efficiency in pipeline pump operations. A nonlinear simulation model of a centrifugal pump driven by an induction motor is developed, incorporating pipeline friction losses via the Darcy–Weisbach relation and pressure transients induced by rapid valve closures. The RLS algorithm continuously estimates effective loop dynamics, enabling online adjustment of proportional and integral gains under changing fluid and operating conditions. Simulation results demonstrate that the proposed RLS-based adaptive controller maintains discharge pressure within ±2% of the target setpoint under density variations from 710 to 900 kg/m3 and during severe transient events. Compared to a fixed-gain PI controller, the adaptive strategy reduced pressure overshoot by approximately 31.9% and settling time by 6%. Model validation using SCADA field data yielded an R2 = 0.957, RMSE = 3.95 m3/h, and normalized NRMSE of 12.6% (by range), confirming strong agreement with measured system behavior. The findings indicate that RLS-based self-tuning provides a practical enhancement to existing pipeline control architectures, offering both improved robustness to abnormal transients and greater efficiency during steady-state operation. This work establishes a foundation for higher-level supervisory and game-theoretic coordination strategies to be explored in subsequent studies.

This paper presents the design and analysis of novel axial flux permanent magnet generators. They have a single rotor and double-sided stators. Two double-sided stators are magnetically decoupled, thereby generating dual-output voltages. The generated voltages have different frequencies, achieved through a novel rotor magnet arrangement structure. A 2D analytical method is developed to analyze generators. 2D and 3D finite element methods are also utilized for detailed analysis of generators. The performance calculations consider two axial flux permanent magnet generators with different dimensions, speeds, and pole numbers.

This paper explores the feasibility of implementing a flywheel energy storage system designed to generate voltage for the purpose of mitigating current flow through the transformer neutral path to ground, which is induced by a high-altitude electromagnetic pulse (HEMP) event. The active flywheel system presents the advantage of employing custom optimal control laws, in contrast to the conventional approach of utilizing passive blocking capacitors. A Hamiltonian-based optimal control law for energy storage is derived and integrated into models of both the transformer and the flywheel energy storage system. This Hamiltonian-based feedback control law is subsequently compared against an energy-optimal feedforward control law to validate its optimality. The analysis reveals that the required energy storage capacity is 13Wh, the necessary power output is less than 5kW at any given time during the insult, and the required bandwidth for the controller is around 5Hz. These specifications can be met by commercially available flywheel devices. This methodology can be extended to other energy storage devices to ensure that their specifications adequately address the requirements for HEMP mitigation.

High altitude electromagnetic pulses (HEMPs) and solar-geomagnetic disturbances (GMDs) both have the potential to impact the reliable operation of the electric power grid. GMDs, and the low-frequency portion of HEMP insults, introduce currents into the grid that can result in the magnetic cores of large power transformers becoming saturated. This paper presents a novel approach to HEMP/GMD mitigation, wherein actively controlled voltage sources are utilized to nullify a low frequency EMP insult. This method is evaluated on several power system case studies, including a single transformer system, a 20-bus system, and a 150-bus system. Results show that the active mitigation is able to successfully prevent transformer saturation in all cases.

Pursuing sustainable energy solutions has prompted researchers to focus on optimizing energy extraction from renewable sources. Control laws that optimize energy extraction require accurate modeling, often resulting in time-varying, nonlinear differential equations. An energy-maximizing optimal control law is derived for time-varying, nonlinear, second-order, energy harvesting systems. We demonstrate that sustaining periodic motion under this control law when subjected to periodic disturbances necessitates identifying appropriate initial conditions, inducing the system to follow a limit cycle. The general optimal solution is applied to two point absorber wave energy converter models: a linear model where the analytical derivation of initial conditions suffices and a nonlinear model demanding a numerical approach. A stable limit cycle is obtained for the latter when the initial conditions lie within an ellipse centered at the origin of the phase plane. This work advances energy-maximizing optimal control solutions for nonautonomous nonlinear systems with application to point absorbers. The results also shed light on the significance of initial conditions in achieving physically realizable periodic motion for periodic energy harvesting systems.

The following paper provides details of a model predictive control designed to operate a four-zone medium-voltage AC/DC electric ship. The control incorporates a reduced order model (ROM) that describes the ship components, a discretization of the dynamics produced by the ROM, and an optimization formulation that determines the ship's behavior. This includes details on how to effectively abstract the power system components into a form that integrates well with computational optimizers. Then, the control is validated on a operational vignette based on mission profiles.

With more focus on multiple-degree-of-freedom wave energy converters, the tools needed to analyze these dimensions properly must expand accordingly. This paper uses Floquet theory to examine the parametrically excited pitch-surge modes and a numerical solver to determine the system's stability. It then shows how control methods and coupling affect this stability. The findings demonstrate that the coupled system has regions of instability close to linear resonance and parametric excitation frequency ratios which significantly affect the wave energy converter's ability to produce power.

A new paradigm in DC microgrid modeling and control has become more and more necessary due to the increasingly dynamic nature of sources, loads, and storage. Many conventional methods face difficulties when dealing with the nonlinearities and uncertainties that naturally exist in these systems. Emerging as a powerful alternative, Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) offers a robust and elegant approach to navigating these complexities. Using the rich framework of Hamiltonian mechanics, this approach shapes the energy surface of the system and guides the flow of power along desired trajectories with minimal effort and guaranteed stability. This offers exciting possibilities for the efficient and resilient operation of DC microgrids, enabling seamless integration of renewables and paving the way for a new generation of distributed energy systems. This paper will present the general methodology and procedures for using the HSSFPC tools in the modeling, control, and analysis of a DC microgrid.

The uptick in stochastic power generation present on the grid has posed a unique set of problems for grid operators. Photovoltaics (PVs) and wind turbines act unpredictably on a minute-to-minute basis, raising concerns around transmission efficiency and grid stability. One solution to the concerns of efficiency and stability is the implementation of energy storage-based power packet networks (PPNs). Modern grids are limited to one frequnecy and the limitations of being synchronous. Asynchronous variable frequency PPN control design is able to handle less predictable power sources. This paper presents a multi-frequency grid using a Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) paradigm to design a controller capable of routing generator power to loads while considering energy storage sizing. A bandpass filter is emulated on bus loads using an integral-derivative controller on voltage sources.