Real-Time Error Detection in Nonlinear Control Systems Using Machine Learning Assisted State-Space Encoding
Real-Time Error Detection in Nonlinear Control Systems Using Machine Learning Assisted State-Space Encoding
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DOI：
10.1109/tdsc.2019.2903049
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发表时间：
2019-03
影响因子：
7.3
通讯作者：
Suvadeep Banerjee;Balavinayagam Samynathan;J. Abraham;A. Chatterjee
中科院分区：
文献类型：
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作者：
Suvadeep Banerjee;Balavinayagam Samynathan;J. Abraham;A. Chatterjee
自主系统在广泛的社会应用中的成功部署取决于底层信号处理和控制功能的无差错运行。非线性系统中的实时错误检测主要依赖于组件或算法级别的冗余，从而导致昂贵的面积和功率开销。本文描述了一种非线性控制系统的实时错误检测方法，用于检测传感器和执行器的退化以及由于数字处理器上执行控制算法时的软错误而导致的故障。我们的方法基于创建冗余检查状态，其值可以根据系统的当前状态以及先前可观察状态值和输入的历史（通过机器学习算法）计算出来。通过检查两者之间的一致性，可以低延迟地检测到错误。该方法通过两个测试案例模拟进行了演示——倒立摆平衡问题和滑模控制器驱动的线控制动（BBW）系统。此外，FPGA 上 ARM 内核表示的错误注入实验的硬件结果以及自平衡机器人上的人工传感器退化证明了实现的实际可行性。
Successful deployment of autonomous systems in a wide range of societal applications depends on error-free operation of the underlying signal processing and control functions. Real-time error detection in nonlinear systems has mostly relied on redundancy at the component or algorithmic level causing expensive area and power overheads. This paper describes a real-time error detection methodology for nonlinear control systems for detecting sensor and actuator degradations as well as malfunctions due to soft errors in the execution of the control algorithm on a digital processor. Our approach is based on creation of a redundant check state in such a way that its value can be computed from the current states of the system as well as from a history of prior observable state values and inputs (via machine learning algorithms). By checking for consistency between the two, errors are detected with low latency. The method is demonstrated on two test case simulations - an inverted pendulum balancing problem and a sliding mode controller driven brake-by-wire (BBW) system. In addition, hardware results from error injection experiments in an ARM core representation on an FPGA and artificial sensor degradations on a self-balancing robot prove the practical feasibility of implementation.