Efficient control of wave energy converters (WECs) is crucial for maximizing energy capture and reducing the Levelized Cost of Energy (LCoE). In this study, we employ a deep reinforcement learning (DRL) framework based on the Soft Actor-Critic (SAC) and Deep Deterministic Policy Gradient (DDPG) algorithms for WEC control. Our approach leverages a novel decoupled co-simulation architecture, training agents episodically in MATLAB to export a robust policy within the WEC-Sim environment. Furthermore, we utilize a rigorous benchmarking protocol to compare the SAC and DDPG agents against a classical Bang-Singular-Bang (BSB) optimal control benchmark. Evaluation under realistic, irregular Pierson-Moskowitz sea states demonstrates that the performance of the RL agents is very close to that of the BSB optimal control baseline. Monte Carlo simulations show that both the DDPG and SAC agents can perform even better than the BSB when the model of the BSB is different from the simulation environment.

For deep space missions, optimizing flyby sequences is essential to reach target destinations with sufficient fuel for scientific objectives. However, identifying optimal flyby sequences is challenging. Conventional global optimization algorithms typically demand a fixed number of design variables, which constrains their applicability for such complex problems. Even with a predefined number of flybys, the extensive design space makes the optimization process computationally expensive. To address this issue, the current study proposes a vectorized dynamic-size genetic algorithm (VDSGA) designed to rapidly generate optimal flyby sequences. To further enhance computational efficiency, the proposed VDSGA method is integrated with a neural network Lambert’s approximator (NNLA), enabling high-speed, accurate approximations of Lambert’s problem. This incorporation improves computational efficiency by leveraging GPU-assisted trajectory optimization without the need for implementation-level modifications, thereby reducing reliance on CPU processing. This approach also provides several different suboptimal flyby sequences, thus broadening the solution space for a given transfer. The accuracy and feasibility of these preliminary design solutions are validated through interplanetary mission examples in this paper.

Despite the significant potential of ocean wave energy, the high cost of the generated power remains a major challenge. This highlights the need for innovative conceptual designs that enhance energy conversion while maintaining comparable implementation and installation costs. Recently, the concept of Variable-Shape Buoy Wave Energy Converters (VSB WECs) was introduced that uses flexible buoy material. While many studies have demonstrated the improved performance of VSB WECs compared to Fixed-Shape Buoy Wave Energy Converters (FSB WECs) through numerical simulations, analytical validation is essential to support these findings. This paper presents an analytical derivation of the theoretical limit of power absorption for VSB WECs using the complex-conjugate criteria for the heave motion. In this study, a multi-degree-of-freedom (multi-DoF) VSB WEC model is developed using a thin spherical shell representation, incorporating Rayleigh–Ritz and Love approximations under the assumptions of small deformations and axisymmetric vibration. Hydrodynamic coefficients are computed using a Boundary Element Method (BEM) software. The variation in the theoretical power absorption limit with Young’s modulus is analyzed across a range of elastic materials. As a validation step, the derived theoretical limit criterion is applied to the standard reduced-order single-DoF model of an FSBWEC, successfully yielding the exact theoretical limit reported in the literature.

This paper presents a mathematical derivation for three new conserved quantities in the motion of spacecraft on optimal continuous-thrust trajectories in a central gravitational field. The process presented in this paper is rooted in Noether's theorem that connects the point symmetries of a dynamic system with the associated conservation laws of the system. In the approach presented in this paper, the system's Lagrangian is modified to account for the non-conservative control force. Using this generalized Lagrangian, the action functional to be minimized is written. Then, Killing equations are formulated to find the dynamic symmetries for this system. In this paper a process is laid out for how to solve the Killing equations; Noether's theorem is applied to this solution of the Killing equations to write the conserved quantities of the system. Conserved quantities are presented for both the two-dimensional and the three-dimensional trajectories in several different coordinate frames. Numerical simulations and mathematical proofs are used to demonstrate that the computed quantities are conserved.

Modern optimal control theory involves adjoining the already known equations of motion of a dynamic system to the objective function using dynamic costates; this is done in order to constrain the optimal control solutions to satisfy the equations of motion. The use of costates increases the number of variables and hence increases the complexity of the problem. On the other hand, variational methods of analytical mechanics finds the equations of motion by minimizing an action functional of the dynamic system, realizing control forces as external input to the system. In this paper a new disruptive approach for computing the optimal control is presented. This approach adopts the variational methods of analytical mechanics to derive equations for the control, in addition to the equations of motion. This is achieved by recognizing the control actuator as part of the dynamic system. In addition to the kinetic energy and potential energy, the action functional in this new approach includes additional energy terms that represent the control energy of the system. Two different methods are presented to write the modified action functional. The proposed approach is a significant departure from the modern optimal control theory, and it eliminates the need for costates when solving for the control. In this paper, a case study is presented to demonstrate the new approach.

This paper presents a method for simultaneous deep-space navigation and attitude determination using angles-only measurements. Using planetary ephemerides and observations of three known celestial bodies in the spacecraft body frame, a geometric construction is developed to derive an equation for the spacecraft's distance to one body. The derivative of the associated zero-finding function is obtained for Newton's method, which enables efficient equation solving. A sign ambiguity arises in the process, yielding nine possible combinations; a resolution strategy is proposed to identify the correct solution. Once the distance is determined, the spacecraft's position is triangulated in the inertial frame, after which any attitude determination algorithm can be applied using the body measurements. The method eliminates the need for matrix inversions and employs a computationally efficient Newton iteration, making it suitable for onboard navigation. Numerical examples, simulating measurements of the Sun and two additional celestial bodies, demonstrate the proposed approach, and an accuracy analysis is conducted considering measurement uncertainties.

Floating hybrid wind-wave systems combine offshore wind platforms with wave energy converters (WECs) to create cost-effective and reliable energy solutions. Adequately designed and tuned WECs are essential to avoid unwanted loads disrupting turbine motion while efficiently harvesting wave energy. These systems diversify energy sources, enhancing energy security and reducing supply risks while providing a more consistent power output by smoothing energy production variability. However, optimising such systems is complex due to the physical and hydrodynamic interactions between components, resulting in a challenging optimisation space. This study uses a 5-MW OC4-DeepCwind semi-submersible platform with three spherical WECs to explore these synergies. To address these challenges, we propose an effective ensemble optimisation (EEA) technique that combines covariance matrix adaptation, novelty search, and discretisation techniques. To evaluate the EEA performance, we used four sea sites located along Australia's southern coast. In this framework, geometry and power take-off parameters are simultaneously optimised to maximise the average power output of the hybrid wind-wave system. Ensemble optimisation methods enhance performance, flexibility, and robustness by identifying the best algorithm or combination of algorithms for a given problem, addressing issues like premature convergence, stagnation, and poor search space exploration. The EEA was benchmarked against 14 advanced optimisation methods, demonstrating superior solution quality and convergence rates. EEA improved total power output by 111 Additionally, in comparisons with advanced methods, LSHADE, SaNSDE, and SLPSO, EEA achieved absorbed power enhancements of 498 sea site, showcasing its effectiveness in optimising hybrid energy systems.

This study presents a multidisciplinary optimization technique for designing an end-to-end Mars aerobraking trajectory coupled with spacecraft design. Unlike typical approaches that analyze aerobraking trajectories based on a predefined spacecraft design, this study concurrently optimizes the spacecraft design as well as the trajectory. The optimization process consists of two key stages. The first stage involves a heliocentric transfer from Earth to Mars, while the second focuses on the Mars arrival trajectory. This second stage includes a capture phase, an aerobraking campaign, and the science orbit insertion. The near-Mars dynamic model considers the zonal harmonics and atmospheric drag. Three reference optimizations are conducted and compared with the proposed method. The first reference is separated optimization that optimizes the heliocentric transfer and Mars arrival trajectory sequentially. The second is the fixed spacecraft design method without optimizing the spacecraft hardware parameter but using a predefined value while optimizing the same problem. The last is a direct transfer without aerobraking. The particle swarm optimization is used for all the optimizations. The proposed end-toend Mars aerobraking trajectory optimization method, integrated with spacecraft design, demonstrates significant improvements in mission efficiency by quantifying its benefits. (c) 2025 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

This paper presents new methods for spacecraft relative pose estimation using the Unscented Kalman Filter (UKF), taking into account non-additive process and measurement noises. A twistor model is employed to represent the spacecraft’s relative 6-DOF motion of the chaser with respect to the target, expressed in the chaser body frame. The twistor model utilizes Modified Rodrigues Parameters (MRPs) to represent attitude with a minimal number of parameters, eliminating the need for the normalization constraint that exists in the quaternion-based model. Additionally, it incorporates both relative position and attitude in a single model, addressing kinematic coupling of states and simplifying the estimator design. Despite numerous existing pose estimation algorithms, many rely on the simplification of additive noise assumptions. This work enhances the robustness and improves the convergence of non-additive noise algorithms by deriving two methods to accurately approximate process and measurement noise covariance matrices for systems with non-additive noises. The first method utilizes the Stirling Interpolation Formula (SIF) to obtain equivalent process and measurement noise covariance matrices. The second method employs State Noise Compensation (SNC) to derive the equivalent process noise covariance matrix and uses SIF to compute the equivalent measurement noise covariance matrix. These methods are integrated into the UKF framework for estimating the relative pose of spacecraft in proximity operations, demonstrated through two scenarios: one with a cooperative target using Position Sensing Diodes (PSDs) and another with an uncooperative target using LiDAR for 3-D imaging. The effectiveness of these methods is validated against others in the literature through Monte Carlo simulations, showcasing their faster convergence and robust performance.

This study presents the results of experimental testing for a Flexible Oscillating Water Column (FlexOWC) system, a new wave energy converter designed to enhance energy capture efficiency. The FlexOWC is being developed at Peak Inc., with funding from the US Department of Energy (DOE) under award DE-SC0025144 [1], and is protected under a US provisional patent for its design and innovative features [2]. The experiments, conducted on a 1:20 scale model in a controlled wave flume environment at the Iowa Institute of Hydraulic Research, Hydroscience and Engineering (IIHR) at the University of Iowa, are compared to numerical simulations under regular wave conditions. Orifices are used to simulate the turbine load. Air compressibility modeling [3] has been accounted for while simultaneously satisfying Froude’s scaling criteria for waves using Air Vessels. Key findings include demonstrating changes in energy absorption when adding the flexible membrane to the oscillating water column. These experiments demonstrate enhanced energy capture compared to rigid OWC designs. These experiments build on methodologies for resolving wave reflections in experimental setups [5] and validate concepts of pulsating power extraction in OWC systems [6]. The paper will discuss critical insights into the dynamic behavior and scalability of the FlexOWC technology, the system’s adaptability to various wave climates, and the impact of membrane characteristics on pneumatic power, with a description of full-scale prototype implementations.

The Flexible Oscillating Water Column (FlexOWC) introduces an innovative wave energy conversion approach, using a flexible membrane to enhance energy harvesting and system efficiency. This paper presents a numerical investigation of the FlexOWC system integrated within a Coastal Structure Integrated (CSI) framework, advancing renewable energy technologies and coastal resilience. Two complementary numerical modeling techniques assessed the FlexOWC’sperformance. The computationally efficient potential flow model explored geometric and operational configurations across various wave conditions. Simultaneously, ahigh-fidelity Computational Fluid Dynamics (CFD) model developed in OpenFOAM captured hydrodynamic interactions and flexible membrane behavior, incorporatingturbulence and fluid-structure interaction models essential for understanding system dynamics. The results show substantial improvements in pneumatic power output compared to traditional rigid Oscillating Water Columns (OWCs). The flexible membrane increased power output under both regular and irregular wave conditions, attributed to its adaptive response to wave forces,creating favorable pressure distributions in the OWC chamber. These findings demonstrate the potential of flexible membrane technology to optimize energy capture in diverse wave climates. FlexOWC technology offers a scalable and sustainable solution for wave energy conversion, with dual benefits of renewable energy generation and coastal protection against extreme weather events when integrated into multifunctional coastal structures. Future work will focus on experimental validation through prototype testing and field deployment, with industry collaborations ensuring a streamlined path to commercialization and application.

Floating hybrid wind-wave systems combine offshore wind platforms and WECs to create cost-effective, reliable energy solutions. WECs that are properly designed and tuned are required to avoid unwanted loads that can interfere with turbine motion while efficiently extracting energy from waves. The systems diversify energy sources, enhance energy security, and reduce supply risks while delivering a smoother power output through the minimisation of energy production variability. However, optimisation of these systems is hindered by physical and hydrodynamic component-component interactions, which cause a challenging optimisation space. A 5-MW OC4-DeepCwind semi-submersible platform and three spherical WECs are taken into consideration in this paper in order to explore such synergies. To address these challenges, we propose an effective ensemble optimisation (EEA) technique that combines covariance matrix adaptation, novelty search, and discretisation techniques. To evaluate the EEA performance, we used four sea sites located along Australia's southern coast. In this framework, geometry and power take-off (PTO) parameters are simultaneously optimised to maximise the average power output of the hybrid wind-wave system. Ensemble optimisation methods enhance performance, flexibility, and robustness by identifying the best algorithm or combination of algorithms for a given problem, addressing issues like premature convergence, stagnation, and poor search space exploration. The EEA was benchmarked against 14 advanced optimisation methods, demonstrating superior solution quality and convergence rates. EEA improved total power output by 111%, 95%, and 52% compared to Whale Optimisation Algorithm (WOA), Equilibrium Optimiser (EO), and Artificial Hummingbird Algorithm (AHA), respectively. Additionally, in comparisons with advanced methods, Ensemble Sinusoidal Differential Covariance Matrix Adaptation (LSHADE), Self-adaptive Differential Evolution (SaNSDE), and Social Learning Particle Swarm Optimisation (SLPSO), EEA achieved absorbed power enhancements of 498%, 638%, and 349% at the Sydney sea site, showcasing its effectiveness in optimising hybrid energy systems.

The global optimization of the moon tour design problem is addressed in this paper. These missions are usually designed using graphical methods or grid search, which require simplifying assumptions, and a skillful mission designer. The grid search methods are computationally intense. Trajectories with a high number of flybys and multiple resonance flybys are usually hard to optimize, especially with small-size/short-period flyby moons. This work proposes a new mutation operator that is incorporated with the Monotonic Basin Hopping in the Evolutionary Mission Trajectory Generator tool; this mutation operator increases the exploration of resonance flybys to improve convergence in moon tour design optimization problems. In this work, the Hidden Genes Genetic Algorithm is used to optimize the undetermined number of moon flybys. A Europa Clipper-like mission is optimized assuming two-body dynamics, and a validation study for the proposed resonance mutation operator is presented. The results include an optimized baseline solution and a new solution with a different sequence of flybys with a different sequence of flybys for the Europa Clipper-like mission, in addition to an optimized moon tour in the Saturnian system.