Concurrent Learning Based Dual Control for Exploration and Exploitation in Autonomous Search

In this paper, a concurrent learning framework is developed for source search in an unknown environment using autonomous platforms equipped with onboard sensors. Distinct from the existing solutions that require significant computational power for Bayesian estimation and path planning, the proposed solution is computationally affordable for onboard processors. A new concept of concurrent learning using multiple parallel estimators is proposed to learn the operational environment and quantify estimation uncertainty. The search agent is empowered with dual capability of exploiting current estimated parameters to track the source and probing the environment to reduce the impacts of uncertainty, namely Concurrent Learning for Exploration and Exploitation (CLEE). In this setting, the control action not only minimises the tracking error between future agents position and estimated source location, but also the uncertainty of predicted estimation. More importantly, the rigorous proven properties such as the convergence of CLEE algorithm are established under mild assumptions on sensor noises, and the impact of noises on the search performance is examined. Simulation results are provided to validate the effectiveness of the proposed CLEE algorithm. Compared with the information-theoretic approach, CLEE not only guarantees convergence, but produces better search performance and consumes much less computational time.

Origin of Improved Photoelectrochemical Water Splitting in Mixed Perovskite Oxides

Owing to the versatility in their chemical and physical properties, transition metal perovskite oxides have emerged as a new category of highly efficient photocatalysts for photoelectrochemical water splitting. Here, to understand the underlying mechanism for the enhanced photoelectrochemical water splitting in mixed perovskites, we explore ideal epitaxial thin films of the BiFeO3-SrTiO3 system. The electronic struture and carrier dynamics are determined from both experiment and density-functional theory calculations. The intrinsic phenomena are measured in this ideal sytem, contrasting to commonly studied polycrstalline solid solutions where extrinsic structural features obscure the intrinsic phenomena. We determined that when SrTiO3 is added to BiFeO3 the conduction band minimum position is raised and an exponential tail of trap states from hybridized Ti 3d and Fe 3d orbitals emerges near the conduction band edge. The presence of these trap states strongly suppresses the fast electron-hole recombination and improves the photocurrent density in the visible-light region, up to 16 times at 0 VRHE compared to the pure end member compositions. Our work provides a new design approach for optimising the photoelectrochemical performance in mixed perovksite oxides.