با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
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1 |
Reinforcement learning control for underactuated surface vessel with output error constraints and uncertainties
کنترل یادگیری تقویتی برای سطوح کم بهره با محدودیت ها و عدم قطعیت خطای خروجی-2020 This study investigates the trajectory tracking control problem of an underactuated marine vessel in the presence of output constraints, model uncertainties and environmental disturbances. The error transfor- mation technique can ensure that the tracking errors remain within the predefined constraint boundaries. The controller is designed in combination with the critic function and the reinforcement learning (RL) al- gorithm based on actor-critic neural networks. The RL method is applied to solve model uncertainties and disturbances, and the critic function modifies the control action to supervise the system performance. Based on Lyapunov’s direct method, a stability analysis is proposed to prove that the boundedness of system signals and the desired tracking performance can be guaranteed. Finally, the simulation illustrates the effectiveness and feasibility of the proposed controller. Keywords: Reinforcement learning | Actor-Critic (AC) | Output constraints | Underactuated marine vessel | Trajectory tracking | Neural networks |
مقاله انگلیسی |
2 |
PathZip: A lightweight scheme for tracing packet path in wireless sensor networks
فشرده سازی مسیر: طرح سبک برای ردیابی مسیر بسته در شبکه های حسگر بی سیم-2014 In order to provide reliable date delivery and system management for large scale wireless
sensor networks (WSNs), tracing the route path of packets in a lightweight manner is crucial
and critical. Real-time path tracing technology enables us to observe every data transmission
and analyze network dynamics in a fine-grained fashion. Due to resource constraints of
WSNs, however, it is difficult, if not impossible, to integrate into each packet with its full path
information. We attempt to capture such information with inserting a small and constant
overhead into each packet. This design, PathZip, let each sensor node performs lightweight
hash-based computations to passively label every packet forwarded. Meanwhile, the sink
extracts the label information so as to leverage the pre-knowledge on the network to compute
the full packet path. Both topology-aware and geometry-assistant techniques are utilized by
PathZip in order to exploit different network knowledge and reduce the computation and
storage overhead greatly. We conduct theoretical analysis and extensive simulations to
evaluate the performance of our design. The results show that our method is effective to trace
the full route path in large-scale WSNs, and outperforms the state-of-the-art methods.
Keywords:
Wireless sensor networks
Path compression
Hash function
Piece-wise linear approximation |
مقاله انگلیسی |