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The increasing desire for using renewable energy sources throughout the world has resulted in a considerable amount of research into and development of concepts for wave energy converters. By now, many different concepts exist, but still, the wave energy sector is not at a stage that is considered commercial yet, primarily due to the relatively high cost of energy. A considerable amount of the wave energy converters are floating structures, which consequently need mooring systems in order to ensure station keeping. Despite being a well-known concept, mooring in wave energy application has proven to be expensive and has a high rate of failure. Therefore, there is a need for further improvement, investigation into new concepts and sophistication of design procedures. This study uses four Danish wave energy converters, all considered as large floating structures, to investigate a methodology in order to find an inexpensive and reliable mooring solution for each device. The study uses a surrogate-based optimization routine in order to find a feasible solution in only a limited number of evaluations and a constructed cost database for determination of the mooring cost. Based on the outcome, the mooring parameters influencing the cost are identified and the optimum solution determined.

Control of the geographic location of high-altitude balloons has been desired for decades due to the cost and simplicity of the systems. These balloon systems rely on variations in wind direction with altitude so that when a balloon changes height, it also changes the direction of its horizontal motion. An altitude control system can thus also control the horizontal position by transitioning to a wind layer with favorable winds. The system’s ability to navigate successfully thus relies on the existence of certain wind conditions. In this paper, we explore how the ability of a balloon to station-keep varies based on the geographic location and season. We used spatially and temporally variant ERA5 wind data with a tree-search-based algorithm to traverse potential trajectories, and we selected the altitude transitions that maximize time within 50 km of a target. The simulation’s outputs show large variations in success across both latitude and season. Midlatitudes are particularly challenging for station-keeping, while lower latitudes are more favorable. Summer is typically more favorable than winter. This demonstrates that for all balloon systems, the ability to station-keep is highly variant and not universally possible.

The use of autonomous underwater vehicles (AUVs) has expanded in recent years to include inspection, maintenance, and repair missions. For these tasks, the vehicle must maintain its position while inspections or manipulations are performed. Some station-keeping controllers for AUVs can be found in the literature that exhibits robust performance against external disturbances. However, they are either model-based or require an observer to deal with the disturbances. Moreover, most of them have been evaluated only by numerical simulations. In this paper, the feasibility of a model-free high-order sliding mode controller for the station-keeping problem is validated. The proposed controller was evaluated through numerical simulations and experiments in a semi-Olympic swimming pool, introducing external disturbances that remained unknown to the controller. Results have shown robust performance in terms of the root mean square error (RMSE) of the vehicle position. The simulation resulted in the outstanding station-keeping of the BlueROV2 vehicle, as the tracking errors were kept to zero throughout the simulation, even in the presence of strong ocean currents. The experimental results demonstrated the robustness of the controller, which was able to maintain the RMSE in the range of 1–4 cm for the depth of the vehicle, outperforming related work, even when the disturbance was large enough to produce thruster saturation.

The traffic control issue in the smart city scenario gives rise to the higher requirements of Global Navigation Satellite System (GNSS) services, especially in terms of navigation accuracy, together with coverage continuity, and multiplicity. The dense urban environment leads to higher elevation angles for navigation in such areas, which requires a lower altitude of the constellation, as well as a larger number of satellites. In the existing literature, the design and maintenance of the Low Earth Orbit (LEO) navigation constellation that fulfills the requirements of the smart city are not provided. Hence, based on the requirements and constraints of the smart city scenario, this article studies the relation between orbital height, user elevation angle, and coverage. It designs the configuration of an LEO navigation constellation that not only achieves global sensing coverage, but also provides a continuous lane-level navigation service with multiple coverages for the key area. In addition, considering the atmospheric drag in low orbits and the constraint of satellite power and attitude control, a method is proposed by rotating solar panels to change the effective frontal area of the satellite to achieve relative configuration maintenance of the LEO constellation. The results show that the LEO navigation constellation has a 0 s revisit time in five chosen smart cities, and each city has more than four-times coverage every second; the Geographic Dilution of Precision (GDOP) values of five cities are smaller than 0.47. The average navigation accuracy of five cities is 2.01. With the conduction of the one-year station-keeping simulation, the phase deviation of two satellites is less than 0.6° and it gradually converges to 0.1°, where the semi-major axis deviation is less than 80 m. With our proposed method, the active station-keeping control is not needed in one year, and the fuel consumption can be reduced. Finally, the continuity of the navigation service can be assured.

The European corn borer (Ostrinia nubilalis, Hübner) has been managed successfully in North America since 1996 with transgenic Bt-corn. However, field-evolved resistance to all four available insecticidal Bt proteins has been detected in four provinces of Canada since 2018. Evidence suggests resistance may be spreading and evolving independently in scattered hotspots. Evolution and spread of resistance are functions of gene flow, and therefore dispersal, so design of effective resistance management and mitigation plans must take insect movement into account. Recent advances in characterizing European corn borer movement ecology have revealed a number of surprises, chief among them that a large percentage of adults disperse from the natal field via true migratory behavior, most before mating. This undermines a number of common key assumptions about adult behavior, patterns of movement, and gene flow, and stresses the need to reassess how ecological data are interpreted and how movement in models should be parameterized. While many questions remain concerning adult European corn borer movement ecology, the information currently available is coherent enough to construct a generalized framework useful for estimating the spatial scale required to implement possible Bt-resistance prevention, remediation, and mitigation strategies, and to assess their realistic chances of success.

The dynamics of an autonomous underwater vehicle (AUV), which can perform manoeuvres with pitch angles in the range of 90° is investigated in this paper. The purpose of the AUV is to perform station keeping manoeuvre at about 90° pitch angle by varying propeller revolution. The AUV is launched / retrieved in horizontal orientation.  Quaternion mathematics, 4 quadrant propeller open water characteristics and PID controller for propeller revolution are incorporated in manoeuvring mathematical model for this purpose.  A procedure for optimizing the gain coefficients for the PID controller is developed using the manoeuvring mathematical model. Two design configuration of the AUV are investigated, positively buoyant and negatively buoyant. It is shown that both the optimal gain coefficients for the PID controller for propeller revolution and dynamic response of the AUV are different for each design configuration. 

This paper studies a low-thrust station-keeping of near rectilinear halo orbits in the Earth–Moon quasi-bicircular dynamical model, and it is illustrated using resonant near rectilinear halo orbits as nominal orbits. The control laws considered use a dynamical reshaping strategy that cancels the unstable Floquet modes and stabilize the motion. Furthermore, asymptotic stabilization can be achieved adding the central Floquet modes into the reshaping procedure. Using the Jet Transport technique, the control laws can be explicitly given as high-order Taylor polynomials in terms of the deviation between the state of the spacecraft and the corresponding isochronous state. The explicit closed-form of the controller, obtained using Jet Transport, allows fast control acceleration computation, which could be also of interest for an onboard implementation. Moreover, the robustness of the station-keeping method is shown introducing orbit determination errors in both position and velocity.

The stratospheric airship, as a near-space vehicle, is increasingly utilized in scientific exploration and Earth observation due to its long endurance and regional observation capabilities. However, due to the complex characteristics of the stratospheric wind field environment, trajectory planning for stratospheric airships is a significant challenge. Unlike lower atmospheric levels, the stratosphere presents a wind field characterized by significant variability in wind speed and direction, which can drastically affect the stability of the airship’s trajectory. Recent advances in deep reinforcement learning (DRL) have presented promising avenues for trajectory planning. DRL algorithms have demonstrated the ability to learn complex control strategies autonomously by interacting with the environment. In particular, the proximal policy optimization (PPO) algorithm has shown effectiveness in continuous control tasks and is well suited to the non-linear, high-dimensional problem of trajectory planning in dynamic environments. This paper proposes a trajectory planning method for stratospheric airships based on the PPO algorithm. The primary contributions of this paper include establishing a continuous action space model for stratospheric airship motion; enabling more precise control and adjustments across a broader range of actions; integrating time-varying wind field data into the reinforcement learning environment; enhancing the policy network’s adaptability and generalization to various environmental conditions; and enabling the algorithm to automatically adjust and optimize flight paths in real time using wind speed information, reducing the need for human intervention. Experimental results show that, within its wind resistance capability, the airship can achieve long-duration regional station-keeping, with a maximum station-keeping time ratio (STR) of up to 0.997.

Movement of adult western corn rootworm, Diabrotica virgifera virgifera LeConte, is of fundamental importance to this species’ population dynamics, ecology, evolution, and interactions with its environment, including cultivated cornfields. Realistic parameterization of dispersal components of models is needed to predict rates of range expansion, development, and spread of resistance to control measures and improve pest and resistance management strategies. However, a coherent understanding of western corn rootworm movement ecology has remained elusive because of conflicting evidence for both short- and long-distance lifetime dispersal, a type of dilemma observed in many species called Reid’s paradox. Attempts to resolve this paradox using population genetic strategies to estimate rates of gene flow over space likewise imply greater dispersal distances than direct observations of short-range movement suggest, a dilemma called Slatkin’s paradox. Based on the wide-array of available evidence, we present a conceptual model of adult western corn rootworm movement ecology under the premise it is a partially migratory species. We propose that rootworm populations consist of two behavioral phenotypes, resident and migrant. Both engage in local, appetitive flights, but only the migrant phenotype also makes non-appetitive migratory flights, resulting in observed patterns of bimodal dispersal distances and resolution of Reid’s and Slatkin’s paradoxes.

Stratospheric balloons serve as cost-effective platforms for wireless communication. However, these platforms encounter challenges stemming from their underactuation in the horizontal plane. Consequently, controllers must continually identify favorable wind conditions to optimize station-keeping performance while managing energy consumption. This study presents a receding horizon controller based on wind and balloon models. Two neural networks, PredRNN and ResNet, are utilized for short-term wind field forecast. Additionally, an online receding horizon controller, based on simultaneous optimistic optimization (SOO), is developed for action sequence planning and adapted to accommodate various constraints, which is especially suitable due to its gradient-free nature, high efficiency, and effectiveness in black-box function optimization. A reward function is formulated to balance power consumption and station-keeping performance. Simulations conducted across diverse positions and dates demonstrate the superior performance of the proposed method compared with traditional greedy and A* algorithms.