This study investigates the problem of adaptive neural network asynchronous control for switching cyber-physical systems under unknown dead zones. A generalized switching rule, instead of a Markov/semi-Markov process,...
详细信息
This study investigates the problem of adaptive neural network asynchronous control for switching cyber-physical systems under unknown dead zones. A generalized switching rule, instead of a Markov/semi-Markov process, is utilized to scrutinize the switching behavior of subsystems. This approach characterizes the dynamic nature of sojourn probabilities using single-mode-based sojourn time, aiming to decrease computational load while meeting the demands of real-world scenarios. Considering the intricacies of network environments, the unknown dead zone inputs are considered, which can be effectively implemented via the adaptive neural network-based control law. To counteract the adverse effects of unforeseen information, a saturation-based observer is developed, in which the saturation level is dynamically adjusted with the hope of providing greater flexibility. Utilizing a Lyapunov function that correlates with the detected mode and the system mode, sufficient criteria are established to ensure that the closed-loop system remains bounded in probability. Eventually, the practicality and effectiveness of the proposed control methodology are verified through two simulated examples.
This study provides insights into the distillation sequence optimization of refinery system in a methanol to propylene plant with extractive distillation under multiple conditions. The simulated annealing algorithm(SA...
详细信息
This study provides insights into the distillation sequence optimization of refinery system in a methanol to propylene plant with extractive distillation under multiple conditions. The simulated annealing algorithm(SA) with relative cost function was used to solve a meaningful optimization problem. It was observed that different conditions had differed on the flowsheet. Case study shows the effectiveness of the proposed method.
Microgrid is an advanced application of distributed renewable energy utilization. With the development of energy Internet technology, microgrid is characterized by strong decentralization and high intelligence. The op...
详细信息
ISBN:
(数字)9781728176871
ISBN:
(纸本)9781728176888
Microgrid is an advanced application of distributed renewable energy utilization. With the development of energy Internet technology, microgrid is characterized by strong decentralization and high intelligence. The operation optimization of microgrid requires higher individual autonomy and rational ability, and the traditional centralized optimization is difficult to meet this development trend. In this paper, in order to better reflect the high autonomy of microgrid energy management, a distributed optimization based on potential game is proposed by comprehensively considering multiple independent individuals in the microgrid. Under this strategy, each individual makes decisions with the goal of maximizing their own profits, and completes the iterative solution of the strategy through communication with each other. Finally, a simulation example of islanded microgrid is used to verify the results, which shows that the individual autonomy and intelligence of the microgrid were improved, and the feasibility and effectiveness of the strategy are verified.
Increasing efforts in developing sustainable and economically viable technologies to produce transportation fuels have been made in the last decades. Particularly, the aviation industry has conceived that biojet fuels...
详细信息
ISBN:
(纸本)9788361506515
Increasing efforts in developing sustainable and economically viable technologies to produce transportation fuels have been made in the last decades. Particularly, the aviation industry has conceived that biojet fuels are vital to decrease 50% of the greenhouse gas emissions by 2050 and to achieve carbon-neutral growth by 2020. Thus, the goal of this study is to rank self-sufficient biorefineries for biojet fuel production in Brazil bases on an exergy-based performance analysis aiming to identify the processes irreversibilities. The production capacity assumed for this analysis covers 10% of the projected fuel demand by 2020 in São Paulo (Guarulhos) and Rio de Janeiro (Galeão) airports and considers that the biojet fuel produced is suitable for blending with fossil jet up to 50%. In this context, the base capacity analysed was 210 kton jet/year considering sugarcane (SC) and SC straw as feedstocks, largely available in Brazil. Hence, 24 scenarios were compared for lignocellulosic and lignin valorization processes. These technological pathways covers eight pre-treatment processes such as dilute acid (DA), dilute acid + alkaline treatment (DA-A), steam explosion (SE), steam explosion + alkaline treatment (SE-A), organosolv (O), wet oxidation (WO), liquid hot water (LHW) and liquid hot water + alkaline treatment (LHW-A), followed by enzymatic hydrolysis. Furthermore, three thermochemical processes for the direct conversion of bagasse and lignin upgrade to renewable jet fuel or electricity were considered (Fast pyrolysis, Gasification Fischer-Tropsch and Cogeneration). The exergy assessment evidenced that combined pretreatment processes with the alkaline treatment (DA-A, SE-A, LHW-A) have a better global exergetic performance than the lignocellulosic pre-treatments carried out standalone (DA, SE, O, WO, and LHW). In addition, the use of fast-pyrolysis as a technology for the lignin residues presented the higher performance for all the scenarios. It is shown that the CO2
Energy optimization of utility system helps to reduce the operating cost and save energy for the industrial plants. Widespread uncertainties such as device efficiency and process demand pose new challenges for this is...
详细信息
In this work, SiO2 core-shell spheres with a dendritic pore structure were used as chromatographic support and TiO2 was coated into the pores of the SiO2@dSiO2 shell using tetrabutyl orthotitanate (TBOT) as the titani...
详细信息
The train braking model (TBM) that describes the dynamic relations of operation speed, mileage, and control force is essential for achieving stable operation and precise stopping of heavy haul trains (HHTs). However, ...
详细信息
The train braking model (TBM) that describes the dynamic relations of operation speed, mileage, and control force is essential for achieving stable operation and precise stopping of heavy haul trains (HHTs). However, it is difficult to establish the TBM of HHTs due to complex characteristics: (i) the long body and air braking process of the HHTs may lead to unexpected time-delays of control force; and (ii) there are significant unmodeled dynamics caused by rough tracks and external poor environment. Traditional TBM does not take into account the unmodeled dynamics and time-delays caused by air transmission during braking. To address these issues, this study proposes a data mechanism hybrid modeling strategy, which incorporates a braking time-delay assisted mechanism model and an adaptive long and short-term memory (LSTM) model. A new Bayesian optimization based time-delay estimation method is first proposed to determine unknown time-delays of each carriage and the estimated time-delays are incorporated to generate the multi-point-mass kinetic mechanism model. Moreover, the error of the mechanism-driven model is adaptively compensated by a sliding window LSTM model to conduct the unmodeled dynamics. The effectiveness of the proposed method is demonstrated using the field data.
Data-driven evolutionary optimization has witnessed great success in solving complex real-world optimization problems. However, existing data-driven optimization algorithms require that all data are centrally stored, ...
详细信息
In this work, we investigate the finite-time boundedness (FTB) problem for a class of continuous-time uncertain systems via sliding mode control (SMC) method. A dynamic event-triggered scheme is introduced to determin...
详细信息
In this work, we investigate the finite-time boundedness (FTB) problem for a class of continuous-time uncertain systems via sliding mode control (SMC) method. A dynamic event-triggered scheme is introduced to determine whether the measurement output will be transmitted. And then, a state observer is designed by means of the transmitted output information, based on which a sliding surface in the estimation space is construct. It is shown that the corresponding SMC law can drive the system trajectories onto the specified sliding surface in a finite (possibly short) time. Meanwhile, a partitioning strategy is introduced to analyze the FTB over both reaching phase and the sliding motion, respectively. Finally, a numerical simulation is given.
Based on the switching strategy, this paper presents an finite frequency formulation for the robust stabilization of singularly perturbed uncertain systems. An uncertain system is modeled as a parallel connection of a...
详细信息
ISBN:
(纸本)9781728102634
Based on the switching strategy, this paper presents an finite frequency formulation for the robust stabilization of singularly perturbed uncertain systems. An uncertain system is modeled as a parallel connection of a nominal system and an error system represented in the form of a linear parameter-varying system. A family of dynamic output feedback controllers are designed to enhance the robustness of the error system against finite frequency uncertainties over the operational region. A hysteresis switching is proposed to coordinate the candidate controllers. The proposed scheme is applied in the longitudinal control of an F16 aircraft to verify its effectiveness and merits.
暂无评论