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### Research Papers

J. Dyn. Sys., Meas., Control. 2017;140(4):041001-041001-13. doi:10.1115/1.4037838.

We develop a first-principles model of the regenerator component of a generic Stirling engine. The model is based on the Euler equations of one-dimensional gas dynamics coupled with its convective/conductive heat transfer with the embedded mesh material. We investigate various methods for deriving simpler and low-order control-oriented models from this first principles model, the basic criterion being high fidelity representation of the dynamics of the regenerator when coupled to other dynamic components of the engine. We identify several nondimensional parameters that potentially categorize different modes of operation, and investigate the corresponding time-scale separation. A hierarchy of singularly perturbed models is derived in which acoustic dynamics are eliminated, periodic mesh dynamics are averaged, and the shape of the distributed regenerator gas state is approximated. In addition, since the reduced model is to be operated cyclically when connected to other parts of the engine, we develop such a feedback-aware model reduction algorithm based on a proper orthogonal decomposition (POD) with a chirped signal input (chirp-POD). This algorithm yields reduced models that are accurate over a range of engine operating frequencies.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(4):041002-041002-9. doi:10.1115/1.4037835.

Over the past 20 years, with the increase in the complexity of engines, and the combinatorial explosion of engine variables space, the engine calibration process has become more complex, costly, and time consuming. As a result, an efficient and economic approach is desired. For this purpose, many engine calibration methods are under development in original equipment manufacturers and universities. The state-of-the-art model-based steady-state design of experiments (DOE) technique is mature and is used widely. However, it is very difficult to further reduce the measurement time. Additionally, the increasingly high requirements of engine model accuracy and robust testing process with high data quality by high-quality testing facility also constrain the further development of model-based DOE engine calibration. This paper introduces a new computational intelligence approach to calibrate internal combustion engine without the need for an engine model. The strength Pareto evolutionary algorithm 2 (SPEA2) is applied to this automatic engine calibration process. In order to implement the approach on a V6 gasoline direct injection (GDI) engine test bench, a simulink real-time based embedded system was developed and implemented to engine electronic control unit (ECU) through rapid control prototyping (RCP) and external ECU bypass technology. Experimental validations prove that the developed engine calibration approach is capable of automatically finding the optimal engine variable set which can provide the best fuel consumption and particulate matter (PM) emissions, with good accuracy and high efficiency. The introduced engine calibration approach does not rely on either the engine model or the massive test bench experimental data. It has great potential to improve the engine calibration process for industries.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(4):041003-041003-7. doi:10.1115/1.4037531.

The paper proposes a method to estimate the contact resistance inside the outlet between a charging cable and an electric vehicle. First, an electrothermal model of some components close to the contact area inside the vehicle outlet (in the female part of the outlet) and of the harness inside the vehicle is proposed. The charging cable and the associated components are the male parts of the outlet and are not modeled as these components are not identical for each charging. They also depend on the mode and the charging infrastructure used. It is only supposed that the charging cable evacuates an unknown thermal heat rate. A linear approximation of the electrothermal model is then obtained and used to design a closed-loop estimator of the total heat rate at the contact area. Using this information, a least square method is used to estimate the contact resistance that can be deduced from the first values of the total heat rate after a step variation of the current in the charging cable.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(4):041004-041004-9. doi:10.1115/1.4037654.

Precision-guided airdrop systems have shown considerable accuracy improvements over more widely used unguided systems through high-quality position, velocity, and time feedback provided by global positioning system (GPS). These systems, like many autonomous vehicles, have become solely dependent on GPS to conduct mission operations. This necessity makes airdrop systems susceptible to GPS blackout in mountainous or urban terrain due to multipathing issues or from signal jamming in active military zones. This work overcomes loss of GPS through an analysis of guidance, navigation and control (GNC) capabilities using a single radio frequency (RF) beacon located at the target. Such a device can be deployed at the target by ground crew on site to retrieve package delivery. Two novel GNC algorithms are presented, which use either range from or direction to a RF beacon. Simulation and experimental flight testing results indicated that beacon-based methods can achieve similar results as GPS-based methods. This technology provides a simple and elegant solution to GPS blackout with best method studied showing only a 21% decrease in landing accuracy in comparison to GPS-based methods.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(4):041005-041005-10. doi:10.1115/1.4037732.

This paper proposes a new sliding mode filter augmented by a linear low-pass filter (LPF) for mitigating the effect of high-frequency noise. It is based on the derivation of three new variants of Jin et al.'s (2012, “Real-Time Quadratic Sliding Mode Filter for Removing Noise,” Adv. Rob., 26(8–9), pp. 877–896) parabolic sliding mode filter (J-PSMF) and investigation on their frequency-response characteristics. The new filter is developed by augmenting one of the variants of J-PSMF by a second-order linear LPF. It has better balance between the noise attenuation and signal preservation than both linear LPFs and J-PSMF. The effectiveness of the new filter is experimentally evaluated on a direct current (DC) servomotor equipped with an optical encoder. This paper also shows the application of the proposed filter to a positioning system under PDD2 (proportional, derivative, and second derivative) control, which successfully realizes the noise attenuation and the nonovershooting response simultaneously.

Topics: Filters , Signals
Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(4):041006-041006-13. doi:10.1115/1.4037655.

The longitudinal platoon control problem is considered under a leader and predecessor following scheme with a novel velocity-dependent spacing policy. With this spacing policy, the steady-state intervehicle distances increase with increasing cruise velocity and more so for vehicles that are closer to the leader. Since significant changes might be encountered in intervehicle distances during the travel due to the variations in the velocity of the leader, the problem is studied together with a more accurate modeling of aerodynamic effects within a platoon formation. Based on a standard feedback linearization approach, a dynamic output feedback synthesis problem is formulated with two $H∞$ performance objectives. One of the performance objectives is linked to the string stability of the platoon formation, while the other can be shaped in a way to maintain small spacing errors without aggressive vehicle maneuvers. A synthesis procedure is then outlined based on linear matrix inequality optimization (LMI). The new control scheme is investigated for a three-vehicle platoon by using an advanced aerodynamic model developed based on extensive fluid dynamic simulations. It is observed in this investigation that a desirable platoon operation can be achieved even with a simple aerodynamic model, provided that the controller is designed in a way to ensure good disturbance attenuation. Nevertheless, an accurate modeling of aerodynamic disturbances might be needed especially for the first vehicle after the leader when the cruising velocity varies over a wide range.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(4):041007-041007-12. doi:10.1115/1.4037651.

The main intention of this study is to develop a sampled-data $H∞$ fuzzy controller design to analyze the stability of coupled ordinary differential equation (ODE)–partial differential equation (PDE) systems, where the nonlinear coupled system is expressed by Takagi–Sugeno (T–S) fuzzy models. The coupled ODE–PDE system in this paper constitutes an n–dimensional nonlinear subsystem of ODEs and a scalar linear parabolic subsystem of PDE. Then, in regard to the T–S model representation, Lyapunov technique is utilized to model a sampled-data $H∞$ fuzzy controller to stabilize the contemplated coupled systems and to attain a desired $H∞$ disturbance attenuation performance. The formulated time-dependent Lyapunov functional makes full use of the accessible information about the actual sampling pattern. The outcome of the sampled-data $H∞$ fuzzy control problem is expressed as linear matrix inequality (LMI) optimization problem which can be solved effectively by using any of the available softwares. Finally, hypersonic rocket car model is furnished with simulation results to exhibit the efficacy of the proposed theoretical results.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(4):041008-041008-10. doi:10.1115/1.4037734.

In the protective glass manufacturing industry for cell phones, placing glass pieces into the slots of the grinder requires submillimeter accuracy which only can be achieved by human workers, leading to a bottle neck in the production line. To address such issue, industrial robot equipped with vision sensors is proposed to support human workers. The high placing performance is achieved by a two step approach. In the first step, an eye-to-hand camera is installed to detect the glass piece and slot with robust vision, which can put the glass piece close to the slot and ensures a primary precision. In the second step, a closed-loop controller based on visual servo is adopted to guide the glass piece into the slot with dual eye-in-hand cameras. However, vision sensor suffers from a very low frame rate and slow image processing speed resulting in a very slow placing performance. In addition, the placing performance is substantially limited by the system parameter uncertainty. To compensate for these limitations, a dual-rate unscented Kalman filter (UKF) with dual-estimation is adopted for sensor data filtering and online parameter identification without requiring any linear parameterization of the model. Experimental results are presented to confirm the effectiveness of the proposed approach.

Commentary by Dr. Valentin Fuster

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