scholarly journals Diagnosis of Fault Modes Masked by Control Loops with an Application to Autonomous Hovercraft Systems

Author(s):  
Christopher Sconyers ◽  
Young-Ki Lee ◽  
Kilsoo Kim ◽  
Sehwan Oh ◽  
Dimitri Mavris ◽  
...  

This paper introduces a methodology for the design, testing and assessment of incipient failure detection techniques for failing components/systems of critical engineered systems/processes masked or hidden by feedback control loops. It is recognized that the optimum operation of critical assets (aircraft, autonomous systems, industrial processes, etc.) may be compromised by feedback control loops, which mask severe fault modes while compensating for typical disturbances. Detrimental consequences of such occurrences include the inability to detect expeditiously and accurately incipient failures, loss of control, and inefficient operation of assets in the form of fuel overconsumption and adverse environmental impact. A novel control-theoretic framework is presented to address the masking problem. Major elements of the proposed approach are employed in simulation to develop, implement and validate how faults are distinguished from disturbances and how faults are detected and identified with performance guarantees, i.e., prescribed confidence level and given false alarm rate.The demonstration and validity of the tools/methods employed necessitates, in addition to the theoretical content, a suitable testbed. We have employed and describe briefly in this paper an autonomous hovercraft as the test prototype. We pursue a systems engineering process to design, construct and test the prototype hovercraft instrumented appropriately for purposes of fault injection, monitoring and the presence of control loops. We emphasize a general control-theoretic framework to the masking problem and utilize a simulation environment to derive results and illustrate the efficacy of the methodology.

Author(s):  
Jens Trautmann ◽  
Arthur Beckers ◽  
Lennert Wouters ◽  
Stefan Wildermann ◽  
Ingrid Verbauwhede ◽  
...  

Locating a cryptographic operation in a side-channel trace, i.e. finding out where it is in the time domain, without having a template, can be a tedious task even for unprotected implementations. The sheer amount of data can be overwhelming. In a simple call to OpenSSL for AES-128 ECB encryption of a single data block, only 0.00028% of the trace relate to the actual AES-128 encryption. The rest is overhead. We introduce the (to our best knowledge) first method to locate a cryptographic operation in a side-channel trace in a largely automated fashion. The method exploits meta information about the cryptographic operation and requires an estimate of its implementation’s execution time.The method lends itself to parallelization and our implementation in a tool greatly benefits from GPU acceleration. The tool can be used offline for trace segmentation and for generating a template which can then be used online in real-time waveformmatching based triggering systems for trace acquisition or fault injection. We evaluate it in six scenarios involving hardware and software implementations of different cryptographic operations executed on diverse platforms. Two of these scenarios cover realistic protocol level use-cases and demonstrate the real-world applicability of our tool in scenarios where classical leakage-detection techniques would not work. The results highlight the usefulness of the tool because it reliably and efficiently automates the task and therefore frees up time of the analyst.The method does not work on traces of implementations protected by effective time randomization countermeasures, e.g. random delays and unstable clock frequency, but is not affected by masking, shuffling and similar countermeasures.


Author(s):  
Adhiti T. Raman ◽  
Venkat N. Krovi ◽  
Matthias J. A. Schmid

A new class of distributed, autonomous systems is emerging, capable of exploiting multimodal distributed and networked spatial and temporal data (at significantly larger scales). A renaissance autonomy engineer requires proficiency in both traditional engineering concepts as well as a systems engineering skillset for implementing the ensuing complex systems. In this paper, we describe goals, development and first offering of a scaffolded course: “AuE 893 Autonomy: Science and Systems” to begin addressing this goal. Geared towards graduate engineering students, with limited prior exposure, the course complements the concepts from traditional courses (on mobile-robotics) with experiential hands-on system-integration efforts (building on the F1tenth.org kits). The staged course structure initially builds upon open-source Robotics Operating System (ROS) tutorials on simulated systems (Gazebo/RViz) with networked communication; Hardware-in-the-loop realization (with a Turtlebot platform) then aids the exploration (and reinforcement) of autonomy concepts. The course culminates in a final-project comprising performance testing with student-team integrated scaled Autonomous Remote Control cars (based on the F1tenth.org parts-list). All three student teams were successful in navigating around a closed racecourse at speeds of 10–15 miles per hour, using Simultaneous Localization and Mapping (SLAM) for situational awareness and obstacle-avoidance. We conclude with discussion of lessons-learnt and opportunities for future improvement.


2007 ◽  
Vol 19 (5) ◽  
pp. 1179-1214 ◽  
Author(s):  
H. P. Snippe ◽  
J. H. van Hateren

Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain signal (resp. the attenuation signal) is obtained through a concatenation of an instantaneous nonlinearity and a linear low-pass filter operating on the output of the feedback loop. For input steps, the dynamics of gain and attenuation can be very different, depending on the mathematical form of the nonlinearity and the ordering of the nonlinearity and the filtering in the feedback loop. Further, the dynamics of feedback control can be strongly asymmetrical for increment versus decrement steps of the input. Nevertheless, for each of the models studied, the nonlinearity in the feedback loop can be chosen such that immediately after an input step, the dynamics of feedback control is symmetric with respect to increments versus decrements. Finally, we study the dynamics of the output of the control loops and find conditions under which overshoots and undershoots of the output relative to the steady-state output occur when the models are stimulated with low-pass filtered steps. For small steps at the input, overshoots and undershoots of the output do not occur when the filtering in the control path is faster than the low-pass filtering at the input. For large steps at the input, however, results depend on the model, and for some of the models, multiple overshoots and undershoots can occur even with a fast control path.


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