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En este trabajo se estima un modelo state space para la serie de observaciones mensuales que recoge la producción y distribución de la energia total en España, desde enero de 2013 hasta enero de 2021. Tras una breve descripción de estos modelos, se pasa a su aplicación, y para destacar la valía de los mismos se comparan sus predicciones con las de otros modelos utilizados con series temporales.

This paper introduces a distributed observer‐based emotional command‐filtered backstepping (DOECFB) approach for leader‐following cooperative output‐feedback control of heterogenous strict‐feedback multi‐agent systems (MAS) under mismatched uncertainties and input saturation. A novel state observer is designed based on radial‐basis emotional neural networks (RBENNs) that approximate uncertainties of model dynamics. To model inter‐agent dynamics with less complexity, emotion‐inspired approximated dynamics are shared among neighbouring followers, like emotional contagion in a group of people. An auxiliary system is also used to attenuate input saturation's negative effect on the cooperative tracking performance. Also, command filters and compensating signals are applied to avoid the ‘explosion of complexity’ in the backstepping design. Only local information from other agents is required for the proposed approach to guarantee convergence of the cooperative tracking error to a small region around zero and cooperatively semi‐globally uniformly ultimately boundedness of closed‐loop signals. Simulation examples on a second‐order uncertain MAS and multiple forced‐damped pendulums are conducted, and quantitative comparisons verify the effectiveness of DOECFB and the proposed observer. The authors introduce a cooperative observer‐based emotional command‐filtered backstepping controller that addresses mismatched uncertainties, inter‐agent interactions, limited actuation, and partial state measurement in heterogenous strict‐feedback multi‐agent systems. Specifically, based on radial‐basis emotional neural networks that approximate uncertainties of model dynamics with modified adaption laws, a novel state observer is designed. Also, by taking inspiration from the emotional contagion process in human societies, inter‐agent interactions are modelled with less complexity.

An adaptive command filtered backstepping control design strategy in the presence of quantized states is presented for uncertain nonlinear systems in the strict-feedback form. A uniform quantizer quantizes all state variables, and the quantized state variables are only available for feedback. The existing quantized feedback recursive control design is only applicable to systems with nonlinearities matched to the control input because of its restriction that the partial derivatives of the virtual control laws with respect to state variables should be constants. Compared with the existing result, the primary contribution of this paper is to develop a quantized feedback recursive design using the command filtered backstepping technique for dealing with unmatched nonlinearities without this restriction. An adaptive tracking scheme using quantized states is constructed to compensate for quantization effects, and a new stability analysis strategy is established by analyzing the boundedness of the quantization errors of signals in the command filtered backstepping design framework. The stability of the closed-loop system is analyzed in the sense of uniform ultimate boundedness.

This paper proposes an adaptive output feedback full state constrain (FSC) controller based on the adaptive neural disturbance observer (ANDO) for a nonlinear electro-hydraulic system (NEHS) with unmodeled dynamics. The Barrier Lyapunov Functions (BLFs) are utilized to ensure that all states of the system are specified within the constraints, and the approximation ability of radial basis function neural networks (RBFNNs) is used to cope with the unknown nonlinear functions. An adaptive neural compensation disturbance observer is elaborated to estimate the compound disturbance and oil leakage fault, effectively addressing these negative effects. Subsequently, observer-based output feedback command filter scheme is developed to diminish the explosion of complexity in the taking derivative procedure and obtain high precise tracking performance. The convergence of tracking errors into a small region around the equilibrium is demonstrated by the Lyapunov stability theory. Ultimately, simulation, experiment, and comparative studies are provided to further validate the effectiveness of the proposed control approach.

For the barrier Lyapunov function-based control of full-state time-varying constrained systems via the traditional backstepping technology, due to repeated differentiations of virtual control functions involving time-varying barriers, the adverse effects of “explosion of complexity” caused by the backstepping iteration are more serious, which even makes it impossible to implement for high-order systems. In order to eliminate this negative influence, we take advantage of the command filtered backstepping approach which introduces a command filter to approximate the constructed virtual control law in each procedure of the backstepping design. More importantly, the approximate errors arising from the introduced filters will be removed by constructing a series of compensating signals. Meanwhile, some relatively conservative assumptions will be released compared with existing control strategies. Furthermore, largely unknown external disturbances that may exist in the system will be estimated in real-time via high-gain disturbance observers and then compensated feedforwardly in designing the controller. Specially, the scheme of the resulting control algorithm is simple and online computation time is saved. Finally, the stability of the whole closed-loop system and the control performance is strictly certificated, respectively.

Double-junction tandem solar cells (TSCs), featuring a wide-bandgap top cell (TC) and narrow-bandgap bottom cell (BC), outperform single-junction photovoltaics, demanding meticulous subcell selection and optimization. Lead-free double perovskites offer sustainable photovoltaic solutions and are less toxic with enhanced stability, versatile compositions, and favorable optoelectronic characteristics. This study investigates the design and performance of a lead-free all-double-perovskite tandem solar cell (DPTSC), utilizing Cs2AgBiBr6 (CABB) with a bandgap of 2.05 eV and Cs4CuSb2Cl12 (CCSC) with a bandgap 1.6 eV as absorbers in the TC and BC, respectively. The TC and BC were individually simulated and calibrated against experimental data, forming the basis for tandem device design and optimization. Series and shunt resistance, along with temperature effects on their performance, were examined. Meticulous adjustment of absorber thicknesses achieved optimal current matching between subcells. This fine-tuning closely matches TC current under AM 1.5G spectrum with BC current under a filtered spectrum. At optimal current matching (absorber thickness: 0.365 µm for the TC and 1.4 µm for BC), the DPTSC exhibits impressive power conversion efficiency (PCE) of 28.08% (with Voc=2.47 V, Jsc=12.78mA/cm2, FF = 88.95%). The external quantum efficiency (EQE), Mott–Schottky and carrier generation/recombination profiles under current matching conditions have also been acquired to provide comprehensive device design insights. The designed TSC shows improved stability against temperature variations. These findings highlight the potential for lead-free and stable double perovskites to serve as subcell absorbers, enabling highly efficient, commercially viable, nontoxic, and eco-friendly tandem photovoltaic technologies. This work contributes valuable insights for advancing TSC technology, supported by comparisons with existing simulated and experimental data.

Numerous researchers have dedicated efforts toward enhancing the efficiency of solar cells, particularly through the utilization of multi-junction or tandem solar cell configurations. However, a common approach employed by many researchers involves the use of the standard absorption formula (SAF) to determine the transmitted spectrum from the top cell to illuminate the bottom cells. The SAF method relies on conventional absorption calculations, neglecting reflection, refraction, and parasitic absorption losses. In this study, the transfer matrix (TRM) method, which accounts for reflection and refraction losses and an interference effect, is reported for the accurate calculation of a filtered spectrum. A comparative analysis between the SAF and TRM approaches reveal that the TRM technique provides a more accurate representation of the transmitted spectrum, particularly when considering reflection, refraction, and parasitic absorption losses. The primary aim of this research is to precisely predict the efficiency of tandem configurations by integrating multiple low-bandgap semiconductor bottom cells (BCs) with a top cell (TC) based on high-bandgap perovskite (PVK). Furthermore, the optimization of current matching is achieved by adjusting the thicknesses of the top absorber layer (TAL) and bottom absorber layer (BAL) based on the obtained filtered spectra. Tandem devices optimized using the TRM approach exhibit superior performance, achieving efficiencies of 28.72% (PVK/c-Si), 27.88% (PVK/CIGS), and 29.99% (PVK/PVK). This comparative investigation underscores the importance of considering reflection and refraction losses in tandem solar cell design and highlights the effectiveness of the TRM technique in enhancing device performance.

Slurry tailings storage in large impoundments has been largely used worldwide for a long time, as their cost is very competitive. However, recent disasters have brought to light the need to better comprehend the mechanics of the materials stored and to search for disposal alternatives to overcome the drawbacks. One possibility is the filtered tailings disposal (dry stacking) which requires a better understanding of the material’s response in a dewatered (through filtration) and compacted condition. This paper compares two tailings from the same beneficiation (treatment) plant with different gradings and mineralogy, related to the beneficial processes they undergo. A series of triaxial tests comprising isotropic compression without shearing specimens, as well as isotropic compression followed by drained (CID) and undrained (CIU) shearing, and K-compression followed by undrained (CKU) shearing specimens were conducted over a range of confining pressures and initial compaction degrees. The experimental program allowed the evaluation of convergence for normal compression lines (NCLs) and the analysis under the light of critical state soil mechanics for the stress–strain response of the tested materials. The research outcomes show that changes in iron ore tailings gradings due to different production processes and the use of different compaction degrees had an influence on its behavior (compression and shearing) at lower stress levels, while at higher stresses levels, this difference is erased and there is a convergence for unique and parallels NCL and CSL on ν–ln p′ plane with a spacing of 2.71. On the p′–q plane both tailings showed a unique and similar CSL.

Based on the principle of symmetry, we propose a variable step-size FxLMS algorithm with double nonlinear functions cooperative coupling (DNVSS-FxLMS), aiming to optimize the contradiction between convergence rate and steady-state error in the active pressure pulsation control system of hydraulic systems. The algorithm innovatively couples two types of nonlinear mechanisms (rational-fractional and exponential-function-based), constructing a refined error-step mapping relationship to achieve a balance between rapid convergence and low steady-state error. Simulation experiments were conducted considering the complex time-varying operating environment of a simulation-based hydraulic system. The results demonstrate that, when the system undergoes unstable random changes, the DNVSS-FxLMS algorithm converges at least twice as fast as traditional and existing variable step size algorithms, while reducing steady-state error by 2–5 dB. The proposed DNVSS-FxLMS algorithm exhibits significant advantages in convergence rate, steady-state error reduction, and tracking capability, providing a highly efficient and robust solution for real-time active control of hydraulic system pressure pulsation under complex operating conditions.

The modified filtered-x affine projection (MFxAP) algorithm is effective for active noise control owing to its good convergence behavior and medium computational burden. The transient and steady-state performances of the MFxAP algorithm have been analyzed in previous studies, which presented a relatively good agreement between the theory and measured results. However, the correlation between the weight-error vector and the past noise vectors is disregarded in the existing methods. Hence, a more accurate theoretical analysis for the MFxAP algorithm is presented herein, in which the effect of the past noise vector on the weight-error vector is considered comprehensively. Simulation results indicate that the proposed theoretical results match the experimental results more precisely than the previous studies, in particular, at the steady state.