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首页> 外文期刊>IEEE / ASME Transactions on Mechatronics >Soft-Computing-Based Embedded Design of an Intelligent Wall/Lane-Following Vehicle
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Soft-Computing-Based Embedded Design of an Intelligent Wall/Lane-Following Vehicle

机译：智能壁挂式跟车的基于软计算的嵌入式设计

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摘要

Soft computing techniques are generally well suited for vehicular control systems that are usually modeled by highly nonlinear differential equations and working in unstructured environments. To demonstrate their applicability in real-world applications, two intelligent controllers based on fuzzy logic and artificial neural network are designed for performing a wall-following task. Based on performance and flexibility considerations, the two controllers are implemented onto a reconfigurable hardware platform, namely a field-programmable gate array. As comparative studies of these two embedded hardware controllers designed for the same vehicular application are limited in literature, this research also presents an evaluation of the two controllers, comparing them in terms of hardware resource requirements, operational speeds, and trajectory tracking errors in following different predefined trajectories.
机译：软计算技术通常非常适合通常由高度非线性微分方程建模并在非结构化环境中工作的车辆控制系统。为了证明其在实际应用中的适用性，设计了两个基于模糊逻辑和人工神经网络的智能控制器来执行跟踪墙任务。基于性能和灵活性的考虑，这两个控制器被实现在一个可重新配置的硬件平台上，即现场可编程门阵列。由于针对同一车载应用设计的这两种嵌入式硬件控制器的比较研究在文献中是有限的，因此本研究还对这两种控制器进行了评估，并在以下方面对它们进行了比较：硬件资源需求，运行速度和轨迹跟踪误差预定义的轨迹。

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