Reduced graphene oxide (rGO) has been regarded as a promising electrode material for supercapacitors. However, its application has been restricted by the corrosive reducing agent, inevitable structure agglomeration, and limited electric double-layer capacitor (EDLC) performance. Here, we develop a 3D redox-active rGO/polymerized proanthocyanidins hybrid for high-performance supercapacitance. Using a green and effective hydrothermal process, oligomeric procyanidins (OPCs) have acted as an eco-friendly reductant for GO reduction. It also worked as a polymeric proanthocyanidin (GSP) precursor for the enhancement of pseudocapacitance, where GSP acted as a spacer for inhibiting the agglomeration of rGO/GSP sheets and improving the total specific capacitance. As a result, the as-prepared rGO/GSP composites display a cooperative energy storage mechanism of an electrochemical double-layer capacitor (EDLC) and a pseudocapacitor, with an increased specific capacitance from 141 F g–1 at 2 A g–1 for the pure rGO to 402 F g–1 at 2 A g–1 for the rGO/GSP hybrids. Meanwhile, the rGO/GSP-based symmetrical supercapacitor provides a high specific capacitance of 185 F g–1 at 0.8 A g–1, an energy density of 25.8 Wh kg–1 at a power density of 0.8 kW kg–1, and a good cycling stability with 60.8% capacitance retention over 10000 cycles at 2 A g–1. Such an excellent electrochemical performance comes from the agglomeration reduction structure and synergistic effects between the highly conductive graphene and pseudocapacitive GSP.

With the continuous development of the marine economy and the inland river transport, traditional vessels supervision methods have the shortcomings of short supervision range, small supervision scope, and high cost, which make it difficult to meet the requirements of modern maritime supervision. This paper proposes a novel maritime emergency search system based on unmanned aerial vehicle (UAV) and its landing platform. The system takes the base station with the cruise UAV, as the base point. Subsequently, TDMA system networking technology and wireless bridge communication technology are used to set up a local area network. Then, the improved three-dimensional raster processing is used to search the target waters. After that, several algorithms such as area optimization based on image filtering are applied to classify, integrate, and fit the waters. In addition, the base station distribution scheme and the emergency equipment intelligent management system software are designed to achieve more efficient and convenient management of the system. The system realizes unmanned, visualized, and normalized monitoring and management of the target waters through the coupling of UAV, aerial protection base stations and control terminals, and provides more detailed and accurate information for the development of search and rescue work.

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For non-linear systems (NLSs), the state estimation problem is an essential and important problem. This paper deals with the nonlinear state estimation problems in nonlinear and non-Gaussian systems. Recently, the Bayesian filter designer based on the Bayesian principle has been widely applied to the state estimation problem in NLSs. However, we assume that the state estimation models are nonlinear and non-Gaussian, applying traditional, typical nonlinear filtering methods, and there is no precise result for the system state estimation problem. Therefore, the larger the estimation error, the lower the estimation accuracy. To perfect the imperfections, a projection filtering method (PFM) based on the Bayesian estimation approach is applied to estimate the state. First, this paper constructs its projection symmetric interval to select the basis function. Second, the prior probability density of NLSs can be projected into the basis function space, and the prior probability density solution can be solved by using the Fokker–Planck Equation (FPE). According to the Bayes formula, the proposed estimator utilizes the basis function in projected space to iteratively calculate the posterior probability density; thus, it avoids calculating the partial differential equation. By taking two illustrative examples, it is also compared with the traditional UKF and PF algorithm, and the numerical experiment results show the feasibility and effectiveness of the novel nonlinear state estimation filter algorithm.