This paper introduces a robust controller designed for load frequency control in a dual-area integrated power grid. Here, the suggested controller is a blend of a fuzzy logic controller with an integral controller. Th...
This paper introduces a robust controller designed for load frequency control in a dual-area integrated power grid. Here, the suggested controller is a blend of a fuzzy logic controller with an integral controller. The parameters of the integral controller and frequency bias settings are optimized to enhance the dynamic response of the proposed controller. To attain this, three distinct optimization algorithms are employed, i.e., genetic algorithm, simulated annealing, and pattern search. A new objective function using settling time, settling-max, and settling-min with a suitable weight factor is used to improve the parameters estimation process. A comparative analysis is performed using the proposed approach and classical-I controller under two cases considering several load disturbance scenarios. Furthermore, the suggested hybrid controller is evaluated and compared with similar models in the literature. As expected, the proposed controller exhibits superior performance.
Networked collaborative tripping can effectively reduce the construction complexity of the backup protection system, but there is still a lack of research on the reachability and real-time verification of the tripping...
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ISBN:
(纸本)9781665400657
Networked collaborative tripping can effectively reduce the construction complexity of the backup protection system, but there is still a lack of research on the reachability and real-time verification of the tripping algorithm. In this paper, the networked cooperative trip system is regarded as a reactive real-time system, and a method for verifying the cooperative characteristics of the protection system based on a timed automata is proposed. First, the timed automata are used to give the calculation model of the protection IED, the circuit breaker XCBR and the overall protection system, and then UPPAAL is used to model the model, and the description method of time characteristics is given, and the UPPAAL tool is used to verify the model. The algorithm model in the bus 12node system has been effectively verified. This method can complete the accessibility and real-time evaluation of the tripping algorithm, which is of great significance for reducing the hidden dangers in the system design.
Skin cancer is a highly dangerous type of cancer that requires an accurate diagnosis from experienced physicians. To help physicians diagnose skin cancer more efficiently, a computer-aided diagnosis (CAD) system can b...
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Reinforcement learning (RL) has gained wide attention, but its implementation in autonomous vehicles is still limited by insufficient sample efficiency and heavy training costs. The training efficiency of RL agents is...
Reinforcement learning (RL) has gained wide attention, but its implementation in autonomous vehicles is still limited by insufficient sample efficiency and heavy training costs. The training efficiency of RL agents is influenced by the dimension of the state space, which can be partitioned to reduce the complexity of sampling and computation. This study proposes a hierarchical clustering-based state grouping reinforcement learning (HCSG-RL) method for the switching decision of autonomous vehicles. First, we partition the base state space into groups and generate a hierarchical tree of state space groups. Then, we train multiple sub-agents for each node in the hierarchical tree. Finally, we add these trained-well sub-model into master policy. This method allows us to fully explore all state spaces and improve the training efficiency of individual agents, which handles the “long-tail” issue and the curse of dimensionality issue. We conduct experiments in a simulation environment and results show that the proposed method has 16–72% reward improvement compared to the tree model in different road length.
Due to large-scale wind power integration, the operation and reserve of power system has been seriously affected. It is necessary to utilize other resources to replace conventional generators to provide reserve capaci...
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Due to large-scale wind power integration, the operation and reserve of power system has been seriously affected. It is necessary to utilize other resources to replace conventional generators to provide reserve capacity for power system. Taking multiple types of reserve resources into account, an optimal scheduling strategy of spinning reserve considering coordination between source and load for power system is proposed. Firstly, according to the mode and operation constraints of reserve resources, the reserve models of conventional generators, wind farm and demand response are established. Secondly, with the objective function of minimizing the operation cost and reserve cost of power system, the optimal scheduling model of spinning reserve based on source load coordination is constructed. Finally, a case of 6-machine 30 bus system is carried out to prove that the economy of power system is improved obviously, and the effectiveness of the proposed optimal scheduling strategy is verified. Furthermore, the impact of wind farm and demand response reserve cost on the system spinning reserve capacity allocation is analyzed respectively, and it has a certain reference significance for reserve resource bidding mechanism of power system.
Motion planning for a tractor-trailer system is a challenging problem due to the nonholonomic constraints and highly nonlinear nature of the system. In this paper, we present a motion planning approach based on the Hy...
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ISBN:
(纸本)9781665409797
Motion planning for a tractor-trailer system is a challenging problem due to the nonholonomic constraints and highly nonlinear nature of the system. In this paper, we present a motion planning approach based on the Hybrid A* algorithm which produces smooth, collision-free, and kinematically feasible paths for a tractor-trailer system in a known environment. Kinematic model based on the on-axle hitching configuration of the tractor-trailer system is used for node expansion. Voronoi graph is used to compute sub-goals that guide the search towards the goal faster. A pure pursuit controller is employed to track the generated trajectory. The planning approach is evaluated over a number of Monte-Carlo simulation runs, and the experimental results indicate a perfect accuracy.
Motivated by governance models adopted in blockchain applications, we study the problem of selecting appropriate system updates in a decentralised way. Contrary to most existing voting approaches, we use the input of ...
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Skin cancer is a highly dangerous type of cancer that requires an accurate diagnosis from experienced physicians. To help physicians diagnose skin cancer more efficiently, a computer-aided diagnosis (CAD) system can b...
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ISBN:
(数字)9798350313338
ISBN:
(纸本)9798350313345
Skin cancer is a highly dangerous type of cancer that requires an accurate diagnosis from experienced physicians. To help physicians diagnose skin cancer more efficiently, a computer-aided diagnosis (CAD) system can be very helpful. In this paper, we propose a novel model, which uses a novel attention mechanism to pinpoint the differences in features across the spatial dimensions and symmetry of the lesion, thereby focusing on the dissimilarities of various classes based on symmetry, uniformity in texture and color, etc. Additionally, to take into account the variations in the boundaries of the lesions for different classes, we employ a gradient-based fusion of wavelet and soft attention-aided features to extract boundary information of skin lesions. We have tested our model on the multi-class and highly class-imbalanced dataset, called HAM10000, and achieved promising results, with a 91.17% F1-score and 90.75% accuracy. The code is made available at: https://***/AyushRoy2001/WAGF-Fusion.
Summary What is already known about this topic?Human immunodeficiency virus(HIV)testing is a critical tool in reducing HIV transmission among men who have sex with men(MSM);young MSM frequently use mobile phone applic...
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Summary What is already known about this topic?Human immunodeficiency virus(HIV)testing is a critical tool in reducing HIV transmission among men who have sex with men(MSM);young MSM frequently use mobile phone applications and participate in social hook-ups.
In this paper, the algorithm and theory of supervisory predictive control (SPC) based on T-S fuzzy neural network is proposed and applied in Circulating fluidized bed (CFB) boiler system successfully. SPC combines bot...
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ISBN:
(纸本)9781665426480
In this paper, the algorithm and theory of supervisory predictive control (SPC) based on T-S fuzzy neural network is proposed and applied in Circulating fluidized bed (CFB) boiler system successfully. SPC combines both the plant economic process optimization and regulatory process control into a hierarchical control structure, in which the economic optimization is at the upper level and the dynamic tracking is at the lower level. Nonlinear CFB process is expressed by T-S fuzzy neural network. The simulation results of CFB system show that the SPC has more reliable and satisfactory control effects.
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