Pulse width modulation is widely used in modern engine control systems. Withthis control method, power is regulated by periodically turning on and off the load for a specified period of time. Mathematical models of d...
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this paper mainly focuses on various two-point methods of identifying the First Order Plus Time Delay (FOPTD) model, and their impact on control quality. the following criteria were used to match the identification me...
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ISBN:
(数字)9781665468589
ISBN:
(纸本)9781665468596;9781665468589
this paper mainly focuses on various two-point methods of identifying the First Order Plus Time Delay (FOPTD) model, and their impact on control quality. the following criteria were used to match the identification method: ISE between the response of the real system and the model and the normalized delay time. the work used two different tuning techniques: QDR and pidtune. A three-tank interacting and non-interacting system was used as a model for the tests. All tests were simulated in Matlab environment, ISE and settling time were used to assess the quality of control.
With a growing population, global food demand continues to rise. Many crops depend on wild and managed pollinators that are experiencing steep population declines. this directly impacts growers' ability to increas...
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ISBN:
(纸本)9781665483834
With a growing population, global food demand continues to rise. Many crops depend on wild and managed pollinators that are experiencing steep population declines. this directly impacts growers' ability to increase food production and is compounded by a lack of systems for monitoring and understanding pollinator behavior. Here, we present task allocation methodsthat would allow us to leverage existing agricultural robots to monitor both natural and wild pollinator behavior. this would supply growers with information key to improving orchard management such as the interaction between foragers and the orchard as well as the effect of foragers on crop growth. We compare three different task allocation methods for visual monitoring of pollinators designed around the type of activities necessary for an agricultural robot. Our approach is tested in a comprehensive simulator that considers the structure and bloom of an orchard and the time-evolving nature of honey bee flights. Our results indicate that intermittently monitoring an orchard permits estimations with a small (3-9 out of 25) pollinator error margin and that this strategy can also be used to detect spontaneous events.
In paper, forecasting models using exponential smoothing for Polish coal mining safety accidents are presented. Prior to this, data is analyzed and approach for building forecasting models in Tableau is described in d...
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ISBN:
(数字)9781665468589
ISBN:
(纸本)9781665468596;9781665468589
In paper, forecasting models using exponential smoothing for Polish coal mining safety accidents are presented. Prior to this, data is analyzed and approach for building forecasting models in Tableau is described in details. three forecasting models are revealed, respectively for all accidents in coal mines, fatal accidents and employment. Received results are promising and confidence intervals cover the predictions well. Improved forecast accuracy with presented models might provide coal mine enterprises more precise data, supporting safety management in those organizations.
Task-oriented dialog (TOD) systems use external knowledge sources to help users accomplish specific tasks. While most current TOD research focuses on simple information-collecting tasks in a slot-filling framework, mu...
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ISBN:
(数字)9789819607921
ISBN:
(纸本)9789819607914;9789819607921
Task-oriented dialog (TOD) systems use external knowledge sources to help users accomplish specific tasks. While most current TOD research focuses on simple information-collecting tasks in a slot-filling framework, multi-step reasoning tasks like troubleshooting remain under-explored. Leveraging the advancements of large language models (LLMs), we propose a novel LLM-based multi-agent learning framework to build troubleshooting dialogue systems and evaluate the effectiveness of various multi-agent learning settings in a TOD system. Our results show that LLMs designed for open-domain dialog face challenges when directly applied to TOD systems, but with multi-agent cooperative enhancements, LLMs can achieve commendable performance.
Simulation has played an important role in efficiently evaluating self-driving vehicles in terms of scalability. Existing methods mostly rely on heuristic-based simulation, where traffic participants follow certain hu...
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ISBN:
(数字)9781665468800
ISBN:
(纸本)9781665468800
Simulation has played an important role in efficiently evaluating self-driving vehicles in terms of scalability. Existing methods mostly rely on heuristic-based simulation, where traffic participants follow certain human-encoded rules that fail to generate complex human behaviors. therefore, the reactive simulation concept is proposed to bridge the human behavior gap between simulation and real-world traffic scenarios by leveraging real-world data. However, these reactive models can easily generate unreasonable behaviors after a few steps of simulation, where we regard the model as losing its stability. To the best of our knowledge, no work has explicitly discussed and analyzed the stability of the reactive simulation framework. In this paper, we aim to provide a thorough stability analysis of the reactive simulation and propose a solution to enhance the stability. Specifically, we first propose a new reactive simulation framework, where we discover that the smoothness and consistency of the simulated state sequences are crucial factors to stability. We then incorporate the kinematic vehicle model into the framework to improve the closed-loop stability of the reactive simulation. Furthermore, along with commonly-used metrics, several novel metrics are proposed in this paper to better analyze the simulation performance.
this paper proposes a navigation system for mobile robot working in indoor environment, which includes mapping and trajectory generation for the motion tracking problem of the real mobile robot. the mapping process co...
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ISBN:
(数字)9781665468589
ISBN:
(纸本)9781665468596;9781665468589
this paper proposes a navigation system for mobile robot working in indoor environment, which includes mapping and trajectory generation for the motion tracking problem of the real mobile robot. the mapping process comprises a Gaussian model to improve the accuracy of the environment representation. Withthis new mapping method, the mobile robot knows the obstacle in the environment around robot itself. For the trajectory generation process, a multimodality method is used to explore all feasible paths to reach the target point by estimating the density of distribution of the objective function. Finally, the experiments show the effectiveness of this navigation framework.
this paper presents a meta-reinforcement learning approach for quadrotor UAV attitude control, addressing the limitations of traditional control methods in complex, dynamic, and uncertain environments. Our method inte...
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the article presents new results in terms of Frequency Weighted (FW) model reduction method in application to approximate LTI discrete-time non-commensurate fractional-order systems based on the Grunwald-Letnikov nabl...
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ISBN:
(数字)9781665468589
ISBN:
(纸本)9781665468596;9781665468589
the article presents new results in terms of Frequency Weighted (FW) model reduction method in application to approximate LTI discrete-time non-commensurate fractional-order systems based on the Grunwald-Letnikov nabla fractional-order difference. the method applies the Fourier-based decomposition of the system and the FW model order reduction method. the main advantage of the proposed modeling approach is the specific representation of the fractional-order system enabling a simple, analytical formula for the determination of the Gramians. this significantly improves the computational efficiency of the proposed FW reduction method. the simulation experiments confirm the low computational effort of the introduced processing and its high modeling accuracy
Photovoltaic (PV) systems are recognized as an important section in the utilization of solar power, and the optimisation, control, and mockup of these systems are of great significance. However, the performance of PV ...
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Photovoltaic (PV) systems are recognized as an important section in the utilization of solar power, and the optimisation, control, and mockup of these systems are of great significance. However, the performance of PV systems is mainly motivated by model constraints that are varying and often absent, making their accurate and robust estimation a challenge for existing methods. In this study, the effect of using the Q-learning embedded sine cosine algorithm (QLESCA) in the selection of optimal PV model parameters is investigated. the performance of QLESCA is evaluated and compared with other optimizers. the results show that QLESCA achieves higher efficiency in accurately estimating PV model parameters. this research provides an efficient and effective method for identifying optimal PV model parameters and contributes to the field of PV system optimization, control, and simulation.
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