There is an enormous driving force in solid oxide fuel cells (SOFCs) to reduce the operating temperatures from high temperatures (800–1000 °C) to intermediate and low temperatures (400–800 °C) in ...order to increase the durability, improve thermal compatibility and thermal cycle capability, and reduce the fabrication and materials costs. One of the grand challenges is the development of cathode materials for intermediate and low temperature SOFCs with high activity and stability for the O2 reduction reaction (ORR), high structural stability as well as high tolerance toward contaminants like chromium, sulfur and boron. Lanthanum strontium cobalt ferrite (LSCF) perovskite is the most popular and representative mixed ionic and electronic conducting (MIEC) electrode material for SOFCs. LSCF-based materials are characterized by high MIEC properties, good structural stability and high electrochemical activity for ORR, and have played a unique role in the development of SOFCs technologies. However, there appears no comprehensive review on the development and understanding of this most important MIEC electrode material in SOFCs despite its unique position in SOFCs. The objective of this article is to provide a critical and comprehensive review in the structure and defect chemistry, the electrical and ionic conductivity, and relationship between the performance, intrinsic and extrinsic factors of LSCF-based electrode materials in SOFCs. The challenges, strategies and prospect of LSCF-based electrodes for intermediate and low temperature SOFCs are discussed. Finally, the development of LSCF-based electrodes for metal-supported SOFCs and solid oxide electrolysis cells (SOECs) is also briefly reviewed.
•A comprehensive review on lanthanum strontium cobalt ferrite (LSCF) perovskite of solid oxide fuel cells.•LSCF-based electrodes are the most important and representative cathode materials of SOFCs.•The relationship between performance, intrinsic and extrinsic factors for LSCF is presented.•Challenges and prospect of development of LSCF based electrodes for IT-SOFCs are discussed.•LSCF electrodes for metal-supported SOFC and solid oxide electrolysis cells are also reviewed.
This note studies the adaptive optimal output regulation problem for continuous-time linear systems, which aims to achieve asymptotic tracking and disturbance rejection by minimizing some predefined ...costs. Reinforcement learning and adaptive dynamic programming techniques are employed to compute an approximated optimal controller using input/partial-state data despite unknown system dynamics and unmeasurable disturbance. Rigorous stability analysis shows that the proposed controller exponentially stabilizes the closed-loop system and the output of the plant asymptotically tracks the given reference signal. Simulation results on a LCL coupled inverter-based distributed generation system demonstrate the effectiveness of the proposed approach.
This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic ...programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.
Solid oxide fuel cells (SOFCs) are the most efficient devices for the direct conversion of the chemical energy stored in fuels such as hydrogen and hydrocarbons into electricity. The development of ...highly efficient and robust SOFCs requires cathodes and anodes with high electrocatalytic activity for O
2 reduction and direct oxidation of hydrocarbon fuels, respectively. Nanoscale engineering of electrode structures via metal salt solution impregnation or infiltration attracts increasing attention as the most effective way to develop highly active and advanced electrode structures for SOFCs. The infiltration method opens a new horizon in the advanced electrode development as the method expands the set of variable electrode materials combinations with the elimination of thermal expansion mismatch and the suppression of potential detrimental reactions between electrode and electrolyte materials. In this article, the advances and challenges in the development of nanoscale and nano-structured electrodes and the fundamental understanding of the remarkable enhancement in the electrode performance are reviewed and discussed with primary focus on the progress and status of the field in the last 5 years.
► Nano-structured electrodes of solid oxide fuel cells by infiltration is reviewed. ► Infiltration is the most effective method to develop advanced electrodes for SOFCs. ► Promotion effect of infiltrated nanoparticles can be structural and/or catalytical. ► Most significant challenge for nano-structured electrode is the long-term stability.
The event-based control strategy is an effective methodology for tackling the distributed control of multi-agent systems with limited on-board resources. This technical note focuses on event-based ...leader-following consensus for multi-agent systems described by general linear models and subject to input time delay between controller and actuator. For each agent, the controller updates are event-based and only triggered at its own event times. A necessary condition and two sufficient conditions on leader-following consensus are presented, respectively. It is shown that continuous communication between neighboring agents can be avoided and the Zeno-behavior of triggering time sequences is excluded. A numerical example is presented to illustrate the effectiveness of the obtained theoretical results.
In this paper, a data-driven non-model-based approach is proposed for the adaptive optimal control of a class of connected vehicles that is composed of n human-driven vehicles only transmitting ...motional data and an autonomous vehicle in the tail receiving the broadcasted data from preceding vehicles by wireless vehicle-to-vehicle (V2V) communication devices. Considering the cases of range-limited V2V communication and input saturation, several optimal control problems are formulated to minimize the errors of distance and velocity and to optimize the fuel usage. By employing an adaptive dynamic programming technique, the optimal controllers are obtained without relying on the knowledge of system dynamics. The effectiveness of the proposed approaches is demonstrated via the online learning control of the connected vehicles in Paramics' traffic microsimulation.
This paper presents a novel method of global adaptive dynamic programming (ADP) for the adaptive optimal control of nonlinear polynomial systems. The strategy consists of relaxing the problem of ...solving the Hamilton-Jacobi-Bellman (HJB) equation to an optimization problem, which is solved via a new policy iteration method. The proposed method distinguishes from previously known nonlinear ADP methods in that the neural network approximation is avoided, giving rise to significant computational improvement. Instead of semiglobally or locally stabilizing, the resultant control policy is globally stabilizing for a general class of nonlinear polynomial systems. Furthermore, in the absence of the a priori knowledge of the system dynamics, an online learning method is devised to implement the proposed policy iteration technique by generalizing the current ADP theory. Finally, three numerical examples are provided to validate the effectiveness of the proposed method.
This article studies the distributed optimal output agreement problem for multiagent systems described by uncertain nonlinear models. By using the partial information of an objective function, the ...design aims to steer the outputs of the agents to an agreement on the optimal solution to the objective function. To solve this problem, this article introduces distributed coordinators to calculate the desired outputs, and designs reference-tracking controllers for the agents to follow the desired outputs. To deal with the nonlinear uncertain dynamics, the closed-loop multiagent system is considered as a dynamical network, and Sontag's input-to-state stability is employed to characterize the interconnections. It is shown that output agreement in multiagent nonlinear systems is achievable by means of distributed optimal controllers via a small-gain approach. The proposed design features a three-layer architecture, and the reference-tracking controllers can be implemented as successive nonlinear proportional-integral loops. A numerical example is employed to show the effectiveness of the design.
Compare with preterm formula, donor human milk (DM) is associated with a lower risk of mortality and morbidity in preterm infants. It is thus deemed superior to preterm formula as the sole diet or ...supplement to own mother's milk (OMM) for preterm infants, especially for those with very low birthweight (VLBW). This historic cohort study investigated the relationship between DM availability, and enteral feeding, body growth of VLBW infants by comparing two cohorts before and after the establishment of a human milk bank. A sub‐analysis was also conducted between small‐for‐gestational‐age (SGA) and non‐SGA infants in our cohorts. Our results showed that DM availability was associated with earlier initiation and faster advancement of enteral feeding, earlier attainment of full enteral feeding, and a higher proportion of OMM in enteral feeding. DM availability was also associated with earlier regain of birthweight, but not with better body growth. SGA and non‐SGA infants responded differently to DM availability with only the non‐SGA group showing improved enteral feeding associated with DM availability. The poor growth of VLBW infants with fortified DM warrants further investigations on better fortification strategies to further improve body growth. Studies are also needed on long‐term effects of DM feeding on the development of VLBW infants.
Compared with the infants before the introduction of donor human milk (DM), very low birthweight infants after that had improved enteral feeding process and had increased use of own mother's milk in this study. However, DM availability affects body growth to a limited extent, which calls for a better fortification strategy for DM‐fed infants.
Key points
Compared with the infants before the introduction of donor human milk (DM), very low birthweight infants after that had improved enteral feeding process, shown as earlier enteral feeding introduction, faster advancement, and earlier attainment of full enteral feeding.
DM availability affects body growth to a limited extent, which calls for a better fortification strategy for DM‐fed infants.
The setup of a human donor milk bank increased the use of own mother's milk for enteral feeding.
This paper studies event-based control of nonlinear systems with state quantization. Two configurations of the event-based quantized controller are considered: Quantization after sampling and ...quantization before sampling. The considered quantizer is assumed to have a finite quantization range. With input-to-state stability (ISS) tools, new event-triggering, and dynamic quantization mechanisms are designed to deal with the interaction of the quantizer and the sampler. For both of the configurations, infinitely fast sampling, and in particular the Zeno phenomenon, is avoided. And the system state asymptotically converges to the origin, if a growth condition is satisfied by the ISS gain of the controlled system.
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