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Review Article

J. Dyn. Sys., Meas., Control. 2017;140(2):020801-020801-17. doi:10.1115/1.4037295.

This paper delivers an in-depth review of the state-of-the-art technologies relevant to rail flaw detection giving emphasis to their use in detection of rail flaw defects at practical inspection vehicle speeds. The review not only looks at the research being carried out but also investigates the commercial products available for rail flaw detection. It continues further to identify the methods suitable to be adopted in a moving vehicle rail flaw detection system. Even though rail flaw detection has been a well-researched area for decades, an in-depth review summarizing all available technologies together with an assessment of their capabilities has not been published in the recent past according to the knowledge of the authors. As such, it is believed that this review paper will be a good source of information for future researchers in this area.

Topics: Flaw detection , Rails , Waves
Commentary by Dr. Valentin Fuster

Research Papers

J. Dyn. Sys., Meas., Control. 2017;140(2):021001-021001-14. doi:10.1115/1.4037329.

The design of a robust fixed low-order controller for uncertain decoupled multi-input multi-output (MIMO) systems is proposed in this paper. The simplified decoupling is used as a decoupling system technique. In this work, the real system behavior is described by a linear model with parametric uncertainties. The main objective of the control law is to satisfy, in presence of model uncertainties, some step response performances such as the settling time and the overshoot. The controller parameters are obtained by resolving a min–max nonconvex optimization problem. The resolution of this kind of problems using standard methods can generate a local solution. Thus, we propose, in this paper, the use of the generalized geometric programming (GGP) which is a global optimization method. Simulation results and a comparison study between the presented approach, a proportional integral (PI) controller, and a local optimization method are given in order to shed light the efficiency of the proposed controller.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(2):021002-021002-12. doi:10.1115/1.4037270.

This paper investigates the supervisory-level, fault tolerant control of a 2004 Prius powertrain. The fault considered is an interturn short circuit (ITSC) fault in the traction drive (a surface mount permanent magnet synchronous machine (SPMSM) for which its rotor is part of the vehicle's driveline). ITSC faults arise from electrical insulation failures in the stator windings where part of a phase winding remains functional while the remaining decoupled windings form a self-contained loop. Because the permanent magnets on the rotor (driveline) shaft are able to induce very large eddy currents in this self-contained loop if its rotational velocity is left unchecked, the maximum allowable driveline speed, and consequently, vehicle speed, must be reduced to avoid exceeding the drive's operational thermal limits. A method for detecting these ITSC faults and the induced eddy current in an SPMSM using a moving horizon observer (MHO) is reviewed. These parameters then determine which previously computed, fault-level-dependent SPMSM input–output power efficiency map and maximum safe operating speed is utilized by the supervisory-level controller. The fault tolerant control is demonstrated by simulating a Prius over a 40 s drive velocity profile with fault levels of 0.5%, 1%, 2%, and 5% detected at the midpoint of the profile. For comparison, the Prius is also simulated without a traction motor fault. Results show that the control reduces vehicle velocity upon detection of a fault to an appropriate safe value.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(2):021003-021003-9. doi:10.1115/1.4037333.

This paper considers the problem of reliable finite-time robust control for uncertain mechanical systems with stochastic actuator failures and aperiodic sampling. A novel model of actuator failure capable of depicting various faulty modes is developed on the basis of homogenous Markov variable. To guarantee the finite-time stability (FTS) and boundedness, a novel fault-tolerant switching controller is developed by virtue of Lyapunov–Krasovskii functional and stochastic analysis technique, simultaneously, the finite-time H performance is also ensured to attenuate the mechanical vibration caused by external disturbances. With convex optimization algorithm, the anticipated controller can be procured by solving a set of linear matrix inequalities (LMIs). Finally, two practical examples of mechanical systems, one of which is governed by lumped parameters and the other is described by distributed parameters, are proposed to prove the effectiveness of the theoretical developments of this study.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(2):021004-021004-10. doi:10.1115/1.4037271.

This paper focuses on norm-optimal iterative learning control (NO-ILC) for single-input-single-output (SISO) linear time invariant (LTI) systems and presents an infinite time horizon approach for a frequency-dependent design of NO-ILC weighting filters. Because NO-ILC is a model-based learning algorithm, model uncertainty can degrade its performance; hence, ensuring robust monotonic convergence (RMC) against model uncertainty is important. This robustness, however, must be balanced against convergence speed (CS) and steady-state error (SSE). The weighting filter design approaches for NO-ILC in the literature provide limited design freedom to adjust this trade-off. Moreover, even though qualitative guidelines to adjust the trade-off exist, a quantitative characterization of the trade-off is not yet available. To address these two gaps, a frequency-dependent weighting filter design is proposed in this paper and the robustness, convergence speed, and steady-state error are analyzed in the frequency domain. An analytical expression characterizing the fundamental trade-off of NO-ILC with respect to robustness, convergence speed, and steady-state error at each frequency is presented. Compared to the state of the art, a frequency-dependent filter design gives increased freedom to adjust the trade-off between robustness, convergence speed, and steady-state error because it allows the design to meet different performance requirements at different frequencies. Simulation examples are given to confirm the analysis and demonstrate the utility of the developed filter design technique.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(2):021005-021005-12. doi:10.1115/1.4037287.

A method is presented for slip analysis of a wheeled mobile manipulator. The said system consists of an industrial manipulator mounted on a mobile platform performing aircraft manufacturing tasks. Unlike tracked/legged mobile robots that may slip when negotiating slopes or climbing stairs, a wheeled mobile manipulator may slip resulting from the manipulator movement or the forces from the end-effector during fastening. Slip analysis is crucial to ensure pose accuracy for operation. In this study, first a universal friction constraint is used to derive the slip condition of the system. Three cases are considered, with the first case considering the reaction force in relation to the stand-off distance between the mobile manipulator and the workpiece. The second case deals with the joint speeds to investigate the effect of coupling terms including centrifugal forces and gyroscopic moments on slip. The third case deals with the joint accelerations to investigate the effect of inertia forces and moments on slip. Simulations and experiments are carried out to verify the proposed method.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(2):021006-021006-8. doi:10.1115/1.4037297.

Developing a flywheel energy storage system (FESS) with permanent magnetic bearing (PMB) and spiral groove bearing (SGB) brings a great challenge to dynamic control for the rotor system. In this paper, a pendulum-tuned mass damper is developed for 100 kg-class FESS to suppress low-frequency vibration of the system; the dynamic model with four degrees-of-freedom is built for the FESS using Lagrange's theorem; mode characteristics, critical speeds, and unbalance responses of the system are analyzed via theory and experiment. A comparison between the theoretical results and the experiment ones shows that the pendulum-tuned mass damper is effective, the dynamic model is appropriate, and the FESS can run smoothly within the working speed range.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(2):021007-021007-11. doi:10.1115/1.4037388.

This paper deals with passive stabilization of thermoacoustic dynamics in a Rijke tube using a Helmholtz resonator. Thermoacoustic instabilities result from the dynamic coupling between the heat release and pressure in a chamber. Helmholtz resonators are used akin to vibration absorbers to suppress unwanted pressure oscillations in such structures and prevent instabilities. The first contribution of the paper is a state-space representation of the thermoacoustic dynamics for the resonator-mounted Rijke tube. This relationship happens to be in the class of linear time invariant, neutral multiple time delay systems (LTI-NMTDS). Then, benefiting from the cluster treatment of characteristic roots (CTCR) paradigm, we investigate the effect of resonator location on suppression of thermoacoustic instability. CTCR is a mathematical tool that determines the stability of LTI-NMTDS exhaustively and nonconservatively in the parameter space of the system. This capability provides a novel tool for the futuristic design concepts of combustors. These analytically obtained findings are also supported with experimental results from a laboratory-scale Rijke tube. In addition, a conceptual case study is presented where the stabilizing contributions of the resonator to the dynamics are investigated under strong thermoacoustic coupling.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Dyn. Sys., Meas., Control. 2017;140(2):024501-024501-7. doi:10.1115/1.4037288.

Real-time detection and decision and control of thermoacoustic instabilities in confined combustors are challenging tasks due to the fast dynamics of the underlying physical process. The objective here is to develop a dynamic data-driven algorithm for detecting the onset of instabilities with short-length time-series data, acquired by available sensors (e.g., pressure and chemiluminescence), which will provide sufficient lead time for active decision and control. To this end, this paper proposes a Bayesian nonparametric method of Markov modeling for real-time detection of thermoacoustic instabilities in gas turbine engines; the underlying algorithms are formulated in the symbolic domain and the resulting patterns are constructed from symbolized pressure measurements as probabilistic finite state automata (PFSA). These PFSA models are built upon the framework of a (low-order) finite-memory Markov model, called the D-Markov machine, where a Bayesian nonparametric structure is adopted for: (i) automated selection of parameters in D-Markov machines and (ii) online sequential testing to provide dynamic data-driven and coherent statistical analyses of combustion instability phenomena without solely relying on computationally intensive (physics-based) models of combustion dynamics. The proposed method has been validated on an ensemble of pressure time series from a laboratory-scale combustion apparatus. The results of instability prediction have been compared with those of other existing techniques.

Commentary by Dr. Valentin Fuster

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