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IN THIS ISSUE

### Research Papers

J. Dyn. Sys., Meas., Control. 2019;141(10):101001-101001-10. doi:10.1115/1.4043488.

This paper presents an extended state observer (ESO) based robust friction compensation scheme for trajectory tracking control of a three-wheeled omnidirectional mobile robot. The proposed approach is practical in implementation, with no friction model required and only three parameters to be tuned. First, a dynamic model with unknown friction forces is given for the robot. Then, the controller is designed, consisting of two parts. One part of the control effort is to compensate the friction effects, which are estimated by ESO without using any friction model. The other part of the control effort is designed based on traditional resolved acceleration control to achieve the trajectory tracking goals. In addition, stability analysis of the designed control system is presented. Extensive simulations and experiments are conducted to validate the proposed control system design in compensating different friction forces.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2019;141(10):101002-101002-13. doi:10.1115/1.4043427.

This paper investigates the dynamic modeling and adaptive control of a single degree-of-freedom flexible cable-driven parallel robot (CDPR). A Rayleigh–Ritz cable model is developed that takes into account the changes in cable mass and stiffness due to its winding and unwinding around the actuating winch, with the changes distributed throughout the cables. The model uses a set of state-dependent basis functions for discretizing cables of varying length. A novel energy-based model simplification is proposed to further facilitate reduction in the computational load when performing numerical simulations involving the Rayleigh–Ritz model. For control purposes, the massive payload assumption is used to decouple the rigid and elastic dynamics of the system, and a modified input torque and modified output payload rate are used to develop a passive input–output map for the naturally noncollocated system. A passivity-based adaptive control law is derived to dynamically adapt to changes in cable properties and payload inertia, and different forms of the adaptive control law regressor are proposed. It is shown through numerical simulations that the adaptive controller is robust to changes in payload mass and cable properties, and the selection of the regressor form has a significant impact on the performance of the controller.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2019;141(10):101003-101003-12. doi:10.1115/1.4043489.

In this article, the effect of Pasternak foundation on free axisymmetric vibration of functionally graded circular plates subjected to mechanical in-plane force and a nonlinear temperature distribution (NTD) along the thickness direction has been investigated on the basis of classical plate theory. The plate material is graded in thickness direction according to a power-law distribution and its mechanical properties are assumed to be temperature-dependent (TD). At first, the equation for thermo-elastic equilibrium and then equation of motion for such a plate model have been derived by Hamilton's principle. Employing generalized differential quadrature rule (GDQR), the numerical values of thermal displacements and frequencies for clamped and simply supported plates vibrating in the first three modes have been computed. Values of in-plane force parameter for which the plate ceases to vibrate have been reported as critical buckling loads. The effect of temperature difference, material graded index, in-plane force, and foundation parameters on the frequencies has been analyzed. The benchmark results for uniform and linear temperature distributions (LTDs) have been computed. A study for plates made with the material having temperature-independent (TI) mechanical properties has also been performed as a special case. Comparison of results with the published work has been presented.

Commentary by Dr. Valentin Fuster

### Technical Brief

J. Dyn. Sys., Meas., Control. 2019;141(10):104501-104501-6. doi:10.1115/1.4043426.

Wind energy is a clean and desirable power source, but wind turbines can potentially operate to the detriment of grid stability. As wind turbine penetration increases, concerns grow regarding power intermittency and frequency regulation. These factors motivate a need for control methodologies that enable a wind turbine to support grid frequency regulation. In this paper, a control design is proposed for a wind turbine to operate in conjunction with a backup synchronous generator for primary frequency control in a microgrid. The proposed design capitalizes on the idea that the wind turbine has a significant amount of rotational inertia in its rotor, and so the power output of the wind turbine can be rapidly adjusted for frequency support via power electronic commands. A novel torque controller is proposed to quickly track the commanded power output without causing wind turbine instability, and an $H2$ gain-scheduled pitch controller has been developed to optimally track the commanded power output while avoiding turbine overspeeding. The proposed design may be used for either un-deloaded or deloaded wind turbine operation, depending on the available wind power. Simulation results show that the proposed wind turbine frequency control effectively enhances the grid frequency response by reducing the frequency deviation from its nominal value following a power imbalance event.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2019;141(10):104502-104502-6. doi:10.1115/1.4043428.

Real-time decision-making (e.g., monitoring and active control of dynamical systems) often requires feature extraction and pattern classification from short-length time series of sensor data. An example is thermoacoustic instabilities (TAI) in combustion systems, caused by spontaneous excitation of one or more natural modes of acoustic waves. The TAI are typically manifested by large-amplitude self-sustained pressure oscillations in time scales of milliseconds, which need to be mitigated by fast actuation of the control signals, requiring early detection of the forthcoming TAI. This issue is addressed in this technical brief by hidden Markov modeling (HMM) and symbolic time series analysis (STSA) for near-real-time recognition of anomalous patterns from short-length time series of sensor data. An STSA technique is first proposed, which utilizes a novel HMM-based partitioning method to symbolize the time series by using the Viterbi algorithm. Given the observed time series and a hidden Markov model, the algorithm generates a symbol string with maximum posterior probability. This symbol string is optimal in the sense of minimizing string error rates in the HMM framework. Then, an HMM likelihood-based detection algorithm is formulated and its performance is evaluated by comparison with the proposed STSA-based algorithm as a benchmark. The algorithms have been validated on a laboratory-scale experimental apparatus. The following conclusions are drawn from the experimental results: (1) superiority of the proposed STSA method over standard methods in STSA for capturing the dynamical behavior of the underlying process, based on short-length time series and (2) superiority of the proposed HMM likelihood-based algorithm over the proposed STSA method for different lengths of sensor time series.

Commentary by Dr. Valentin Fuster