Practical Implementation of Attitude-Control Algorithms for an Underactuated Satellite

The challenging problem of controlling the attitude of satellites subject to actuator failures has been the subject of increased attention in recent years. The problem of controlling the attitude of a satellite on all three axes with two reaction wheels is addressed in this paper. This system is controllable in a zero-momentum mode. Three-axis attitude stability is proven by imposing a singular quaternion feedback law to the angular velocity trajectories.Two approaches are proposed and compared to achieve three-axis control: The first one does not require angular velocity measurements and is based on the assumption of a perfect zero momentum, while the second approach consists of tracking the desired angular velocity trajectories. The full-state feedback is a nonlinear singular controller. In-orbit tests of the first approach provide an unprecedented practical proof of three-axis stability with two control torques. The angular velocity tracking approach is shown to be less efficient using the nonlinear singular controller. However, when inverse optimization theory is applied to enhance the nonlinear singular controller, the angular velocity tracking approach is shown to be the most efficient. The resulting switched inverse optimal controller allows for a significant enhancement of settling time, for a prescribed level of the integrated torque

Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics

An inherent problem of reinforcement learning is performing exploration of an environment through random actions, of which a large portion can be unproductive. Instead, exploration can be improved by initializing the learning policy with an existing (previously learned or hard-coded) oracle policy, offline data, or demonstrations. In the case of using an oracle policy, it can be unclear how best to incorporate the oracle policy's experience into the learning policy in a way that maximizes learning sample efficiency. In this paper, we propose a method termed Critic Confidence Guided Exploration (CCGE) for incorporating such an oracle policy into standard actor-critic reinforcement learning algorithms. More specifically, CCGE takes in the oracle policy's actions as suggestions and incorporates this information into the learning scheme when uncertainty is high, while ignoring it when the uncertainty is low. CCGE is agnostic to methods of estimating uncertainty, and we show that it is equally effective with two different techniques. Empirically, we evaluate the effect of CCGE on various benchmark reinforcement learning tasks, and show that this idea can lead to improved sample efficiency and final performance. Furthermore, when evaluated on sparse reward environments, CCGE is able to perform competitively against adjacent algorithms that also leverage an oracle policy. Our experiments show that it is possible to utilize uncertainty as a heuristic to guide exploration using an oracle in reinforcement learning. We expect that this will inspire more research in this direction, where various heuristics are used to determine the direction of guidance provided to learning.Comment: Under review at TML

Dynamic replication strategies in data grid systems: A survey

In data grid systems, data replication aims to increase availability, fault tolerance, load balancing and scalability while reducing bandwidth consumption, and job execution time. Several classification schemes for data replication were proposed in the literature, (i) static vs. dynamic, (ii) centralized vs. decentralized, (iii) push vs. pull, and (iv) objective function based. Dynamic data replication is a form of data replication that is performed with respect to the changing conditions of the grid environment. In this paper, we present a survey of recent dynamic data replication strategies. We study and classify these strategies by taking the target data grid architecture as the sole classifier. We discuss the key points of the studied strategies and provide feature comparison of them according to important metrics. Furthermore, the impact of data grid architecture on dynamic replication performance is investigated in a simulation study. Finally, some important issues and open research problems in the area are pointed out

Optimal coordinated lateral control of a UAV formation using a virtual structure approach

International audienceThe ability to fly formations of multiple Unmanned Aerial Vehicles (UAVs) is increasingly being considered as a way of enabling a wealth of new applications, from multi observer unambiguous digital elevation mapping to interferometric imaging and receiver localization, to name a few. The main challenges in formation flying are associated with the need for fine coordinated guidance, with fine navigation and control of the absolute and relative positions and orientations of each vehicle. This paper addresses the coordinated lateral control problem of achieving an optimal tradeoff between formation keeping accuracy and energy consumption. The control approach uses a semi-autonomous virtual structure approach for formation control, where the absolute station keeping objective of the formation is ground planned from mission requirements and the UAVs autonomously control their two dimensional relative lateral positions and orientations to maintain a virtual structure. The virtual structure is chosen to be a triangular formation of three UAVs, without loss of generality. Two formation control strategies are compared. The first approach uses a nonlinear Lyapunov stabilizing controller. The second one uses feedback linearization laws, to which linear model predictive (MPC) controllers are superposed to optimize the formation keeping autopilots, in the presence of controller constraints. The feedback linearized MPC controller is easy to implement and outperforms the nonlinear controller in terms of settling time, under the same controller constraints

Solar evaporation enhancement using floating light-absorbing magnetic particles

We have demonstrated a new strategy for enhancing solar evaporation by using floating light-absorbing materials. Floating Fe3O4/C magnetic particles with an average size of 500 nm were synthesized by carbonization of poly(furfuryl alcohol) (PFA) incorporated with Fe3O4 nanoparticles. The Fe3O4/C particles had a BET surface area of 429 m2 g−1, and a density of 1.44 g cm−3. Because of their hydrophobicity and a bulk packing density of 0.53 g cm−3, Fe3O4/C particles were floatable on water. Our results indicated that these Fe3O4/C particles enhanced the water evaporation rate by as much as a factor of 2.3 in the solar evaporation of 3.5% salt water. In addition, Fe3O4/C particles were easily recycled using a magnet, and stable after being recycled three times. Our work provides a low-cost and highly effective way for accelerating solar evaporation for industrial applications such as solar desalination, salt production, brine management and wastewater treatment

Solar evaporation enhancement using floating light-absorbing magnetic particles

We have demonstrated a new strategy for enhancing solar evaporation by using floating light-absorbing materials. Floating Fe3O4/C magnetic particles with an average size of 500 nm were synthesized by carbonization of poly(furfuryl alcohol) (PFA) incorporated with Fe3O4 nanoparticles. The Fe3O4/C particles had a BET surface area of 429 m2 g−1, and a density of 1.44 g cm−3. Because of their hydrophobicity and a bulk packing density of 0.53 g cm−3, Fe3O4/C particles were floatable on water. Our results indicated that these Fe3O4/C particles enhanced the water evaporation rate by as much as a factor of 2.3 in the solar evaporation of 3.5% salt water. In addition, Fe3O4/C particles were easily recycled using a magnet, and stable after being recycled three times. Our work provides a low-cost and highly effective way for accelerating solar evaporation for industrial applications such as solar desalination, salt production, brine management and wastewater treatment

Continuous Process for Producing Carbon Nanotubes

The present invention relates to a continuous process for producing carbon nanotubes (herein after also referred to as “CNTs”) of single, double and/or multi-wall type, with any possible desired diameter and with high purity. The preferred embodiment provides means for continuous supply of a catalyst during the process for producing the carbon nanotubes, according to which one can achieve the advantageous continuity of the process

Hydrodesulphurization Nanocatalyst, Its Use and a Process for Its Production

A nano-supported hydrodesulphurization (HDS) catalyst is prepared for hydrodesulphurization of hydrocarbonaceous feed stock. The catalyst can be prepared through different methods and also used under milder conditions than those required for conventionally used HDS catalysts, but can also function under other hydrodesulphurization operating condition