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Research Papers

J. Dyn. Sys., Meas., Control. 2018;140(8):081001-081001-10. doi:10.1115/1.4039154.

When laying down a long slender beam from a near-vertical orientation, to a horizontal position on a flat surface, the payload may slip and move suddenly in unintended and unpredictable ways. This occurs during crane operations when the movements of the overhead trolley and lowering of the hoist cable are not properly coordinated. The payload's unintended sliding can potentially cause damage and injure people. This paper presents static and dynamic analyses of slender-beam payload lay-down operations that establish a structured method to predict the safe conditions for lay-down operations. Also, a new method to measure the friction coefficient of surface-to-line contact is proposed. Lay-down experiments are carried out to verify the theoretical predictions.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081002-081002-8. doi:10.1115/1.4039155.

Balancing plays a major role in performance improvement of robotic manipulators. From an optimization point of view, some balancing parameters can be modified to decrease motion cost. Recently introduced, this concept is called optimal balancing: an umbrella term for static balancing and other balancing methods. In this method, the best combination of balancing and trajectory planning is sought. In this note, repetitive full cycle motion of robot manipulators including different subtasks is considered. The basic idea arises from the fact that, upon changing dynamic equations of a robotic manipulator or cost functions in subtasks, the entire cycle of motion must be reconsidered in an optimal balancing problem. The possibility of cost reduction for a closed contour in potential fields is shown by some simulations done for a PUMA-like robot. Also, the obtained results show 34.8% cost reduction compared to that of static balancing.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081003-081003-9. doi:10.1115/1.4039156.

This paper addresses a pursuer tracking problem where the pursuer's acceleration is given by a proportional navigation (PN) guidance law with a time-varying navigation ratio which varies with the relative range between the pursuer and its target. Based on a motion model that exactly describes the relative motion and the PN guidance law, a novel filter for tracking such a pursuer is designed using interactive multiple model (IMM) algorithm and unscented Kalman filtering (UKF) technique. This filter is able to accurately estimate the relative range, relative velocity, and the acceleration of pursuer even if the pursuer adopts a PN guidance law with time-varying navigation ratio. The proposed tracking method is evaluated in extensive Monte Carlo simulations. It is shown that accurate estimation results have been obtained, and the model probabilities in the IMM UKF filter are consistent with real situations.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081004-081004-7. doi:10.1115/1.4039153.

A feedback control strategy is presented for improving the transient response of the ubiquitous mass-spring-damper (MSD) system; the closed-loop system has a small settling time with no overshoot for a step input. This type of response is ideal for MSD systems subjected to a unilateral constraint such as radio-frequency micro-electro-mechanical-system (RF MEMS) switches, which are required to close in a short period of time without bouncing. The control strategy switches the stiffness of the MSD between its nominal value and a negative value, resulting in a hybrid dynamical system. A phase portrait analysis of the hybrid system is carried out to establish the asymptotic stability property of the equilibrium and quantify the transient response. Simulation results are presented using parameter values of a real RF MEMS switch from the literature. As compared to open-loop strategies that are currently used, the proposed feedback control strategy promises to provide comparable switch-closing times with robust performance and eliminate bouncing.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081005-081005-9. doi:10.1115/1.4039084.

In the recent years, industries have been working on the online condition monitoring of systems and components in order to definitely abandon the time-based maintenance and switch efficiently to a condition-based maintenance. Therefore, the research field related to prognostics and health management (PHM) has been gaining more and more importance. In the field of hydraulic pumps and motors, the overall efficiency is an important parameter to monitor and the thermodynamic method has historically been proposed for the online evaluation of this parameter for hydraulic machines without external drainage. Indeed, for this kind of machines, the thermodynamic method allows the evaluation of the overall efficiency by measuring only the temperatures and the pressures at the suction and the delivery ports, thus avoiding the use of cumbersome and expensive sensors, such as flow meters and torque sensors. This paper investigates the use of the thermodynamic method for hydraulic machines with external drainage. The case study of a swash-plate type axial-piston pump is considered. In this first part of the project, the objective was to validate the proposed thermodynamic method by comparing its results with the ones obtained through the mechanical, therefore an extensive experimental activity was carried out and two flow meters were used to measure the drainage and the delivery flow rates. The pump was tested in different operating conditions and the uncertainty related to the overall efficiency was calculated accurately in order to compare the two approaches properly.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081006-081006-10. doi:10.1115/1.4039186.

This paper compares the effectiveness of the proposed hybrid metaheuristic algorithms for a class of unstable systems with time delay to that of the existing ones. The local search and global methods of optimization are combined to yield more effective hybrid metaheuristic algorithms. These algorithms are used to tune the proportional–integral–derivative (PID) controllers, satisfying the robust stabilizing vector gain margin (VGM). Six global heuristic algorithms namely ant colony optimization (ACO), particle swarm optimization (PSO), biogeography-based optimization (BBO), population-based incremental learning (PBIL), evolution strategy (ES), and stud genetic algorithms (StudGA) are combined with the local search property of derivative free optimization methods such as simplex derivative based pattern search (SDPS) and implicit filtering (IMF) to yield hybrid metaheuristic algorithms. The efficacy of the proposed control schemes in terms of various time domain specifications and stabilizing VGM are compared with some existing methods for unstable process with time delay (UPTD) systems. The performance of the proposed control schemes particularly in the context of uncertainty in the plant is demonstrated using a case study. The efficacy of the proposed control scheme is illustrated with a nontransfer function based multibody vehicle autosteer control design problem.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081007-081007-9. doi:10.1115/1.4039187.

In this paper, a novel active yaw stabilizer (AYS) system is proposed for improving vehicle lateral stability control. The introduced AYS, inspired by the recent in-wheel motor (IWM) technology, has two degrees-of-freedom with independent self-rotating and orbiting movements. The dynamic model of the AYS is first developed. The capability of the AYS is then investigated to show its maximum generation of corrective lateral forces and yaw moments, given a limited vehicle space. Utilizing the high-level Lyapunov-based control design and the low-level control allocation design, a hierarchical control architecture is established to integrate the AYS control with active front steering (AFS) and direct yaw moment control (DYC). To demonstrate the advantages of the AYS, generating corrective lateral force and yaw moment without relying on tire–road interaction, double lane change maneuvers are studied on road with various tire–road friction coefficients. Co-simulation results, integrating CarSim® and MATLAB/Simulink®, successfully verify that the vehicle with the assistance of the AYS system has better lateral dynamics stabilizing performance, compared with cases in which only AFS or DYC is applied.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081008-081008-13. doi:10.1115/1.4039190.

Control of wind-induced flutter of a bridge deck is studied using static output feedback. Servomotor-actuated winglets provide the control forces. Deck and winglets are modeled as flat plates and their aerodynamic interaction is neglected. Self-excited wind forces acting on deck and winglets are modeled using the Scanlan–Tomko model, with flat plate flutter derivatives (FDs) obtained from Theodorsen functions. Rogers rational function approximation (RFA) is used for time domain representation of wind forces in order to simplify the stability and control analyses. Control input to servomotors is based on direct feedback of vertical and torsional displacements of deck. Feedback gains that are constant, or varying with wind speed, are considered. Winglet rotations being restricted, flutter and divergence behavior is studied using system eigenvalues as well as responses. Results show that variable gain output feedback (VGOF) control using servomotor driven winglets is very effective. It provides the maximum increase in critical speed and maximum attenuation of response, followed by control with gain scheduling, with the former requiring less input power. Control with constant gain is least effective. Control of deck rotation generally appears to improve with wind speed.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081009-081009-10. doi:10.1115/1.4039183.

This paper investigates the problem of robust finite time extended passive reliable filtering for Takagi–Sugeno (T–S) fuzzy systems with randomly occurring uncertainties, missing measurements, and time-varying delays. Moreover, two stochastic variables satisfying the Bernoulli random distribution are introduced to characterize the phenomenon of the randomly occurring uncertainties and missing measurements. By skillfully choosing a proper Lyapunov–Krasovskii functional (LKF), a new set of sufficient conditions in terms of linear matrix inequalities (LMI) is derived to ensure that the filtering error system is robustly stochastically finite time bounded (SFTB) with a desired extended passive performance index. Based on the obtained sufficient conditions, an explicit expression for the desired filter can be computed. Finally, two numerical examples are provided to show the effectiveness of the proposed filter design technique.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081010-081010-9. doi:10.1115/1.4039184.

Gear-shift control is essential in automated manual transmission (AMT) systems, because it has a significant influence on comfort of vehicle and lifespan of AMT. Gear engagement process is the most important part of gear-shift process, and it has multistage and nonlinear characteristics, which make it difficult to realize smooth and fast control. This paper proposes a position and force switching control scheme for gear engagement. At the beginning and the end of gear engagement process, the combination sleeve is supposed to reach the desired position quickly with a small resistance for which a position controller is designed by using sliding mode control (SMC) method. A force controller is designed for the midsynchronizing stage, because the combination sleeve is blocked at this stage until the synchronization is finished. Simulations and experiments are carried out to show that gear-shift quality is improved and gear-shift shock is reduced greatly by the proposed method.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081011-081011-7. doi:10.1115/1.4039195.

A novel first principle based control oriented model of a gasoline engine is proposed which also carries diagnostic capabilities. Unlike existing control oriented models, the formulated model reflects dynamics of the faultless as well as faulty engine with high fidelity. In the proposed model, the torque production subsystem is obtained by integration of further two subsystems that is model of a single cylinder torque producing mechanism and an analytical gasoline engine cylinder pressure model. Model of a single cylinder torque producing mechanism is derived using constrained equation of motion (EOM) in Lagrangian mechanics. While cylinder pressure is evaluated using a closed form parametric analytical gasoline engine cylinder pressure model. Novel attributes of the proposed model include minimal usage of empirical relations and relatively wider region of model validity. Additionally, the model provides model based description of crankshaft angular speed fluctuations and tension in the rigid bodies. Capacity of the model to describe the system dynamics under fault conditions is elaborated with case study of an intermittent misfire condition. Model attains new capabilities based on the said novel attributes. The model is successfully validated against experimental data.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081012-081012-10. doi:10.1115/1.4039205.

Transducers for spatial plantar force measurements have numerous applications in biomechanics, rehabilitation medicine, and gait analysis. In this work, the design of a novel, tri-axial transducer for plantar force measurements was presented. The proposed design could resolve both the normal and the shear forces applied at the foot's sole. The novelty of the design consisted in using a rotating bump to translate the external loads into axial compressive forces which could be measured effectively by conventional pressure sensors. For the prototype presented, multilayer polydimethylsiloxane (PDMS) thin-film capacitive stacks were manufactured and used as sensing units, although in principle the design could be extended to various types of sensors. A quasi-static analytic solution to describe the behavior of the transducer was also derived and used to optimize the design. To characterize the performance of the transducer, a 3 cm diameter, 1 cm tall prototype was manufactured and tested under various combination of shear and normal loading scenarios. The tests confirmed the ability of the transducer to generate strong capacitive signals and measure both the magnitude and direction of the normal and shear loads in the dynamic range of interest.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081013-081013-12. doi:10.1115/1.4039086.

This paper presents a new multimodel controller design approach incorporating stability and performance criteria. The gap metric is employed to measure the distance between local models. An efficient method based on state feedback strategy is introduced to improve the maximum stability margin of the local models. The proposed method avoids local model redundancy, simplifies the multimodel controller structure, and supports employing of many linear control techniques, while does not rely on a priori experience to choose the gridding threshold value. To evaluate the proposed method, three benchmark nonlinear systems are studied. Simulation results demonstrate that the method provides the closed-loop stability and performance via a simple multimodel structure in comparison with the opponents.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081014-081014-11. doi:10.1115/1.4039204.

This paper proposes advancement in the fault diagnosis of induction motors (IMs) based on the wavelet packet transform (WPT) and the support vector machine (SVM). The aim of this work is to develop and perform the fault diagnosis of IMs at intermediate operating conditions (i.e., the speed and the load) to take care of situations where the data are limited or difficult to obtain at required speeds and loads. In order to check the capability of proposed fault diagnosis, ten different IM fault (mechanical and electrical) conditions are considered simultaneously. In order to obtain the useful information from raw time series data that can characterize each of the fault classes at various operating conditions, the wavelet packet is applied to decompose the data of vibration and current signals from the experimental test rig. Fault features are then obtained using the decomposed data and further used for the diagnosis. In this work, five different wavelet functions (i.e., the Haar, Daubechies, Symlet, Coiflet, and Discrete Meyer) are considered in order to analyze the impact of different wavelets on the IM fault diagnosis. The proposed fault diagnosis has been initially attempted for the same speed and load cases and then extended innovatively to the intermediate speed and load cases. In order to check the robustness of the proposed methodology, the diagnosis is performed for a wide range of motor operating conditions. The results show the feasibility of the proposed fault diagnosis for the successful detection and isolation of various faults of IM, even with limited data or information at some motor operating conditions.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081015-081015-11. doi:10.1115/1.4039157.

Youla parametrization is a well-established technique in deriving single-input single-output (SISO) and, to a lesser extent, multiple-input multiple-ouput (MIMO) controllers (Youla, D., Bongiorno, J. J., Jr., and Lu, C., 1974, “Singleloop Feedback-Stabilization of Linear Multivariable Dynamical Plants,” Automatica, 10(2), pp. 159–173). However, the utility of this methodology in estimation design, specifically in the framework of controller output observer (COO) (Ozkan, B., Margolis, D., and Pengov, M., 2008, “The Controller Output Observer: Estimation of Vehicle Tire Cornering and Normal Forces,” ASME J. Dyn. Syst., Meas., Control, 130(6), p. 061002), is not established. The fundamental question to be answered is as follows: is it possible to design a deterministic estimation technique using Youla paramertization with the same robust performance, or better, than well-established stochastic estimation techniques such as Kalman filtering? To prove this point, at this stage, a comparative analysis between Youla parametrization in estimation and Kalman filtering is performed through simulations only. In this paper, we provide an overview of Youla parametrization for both control and estimation design. We develop a deterministic SISO and MIMO Youla estimation technique in the framework of COO, and we investigate the utility of this method for two applications in the automotive domain.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081016-081016-8. doi:10.1115/1.4039278.

Rectangular containers are used for numerous liquid transports in many industrial applications. However, unwanted slosh in the container degrades safe and reliable operations. A three-dimensional (3D) nonlinear slosh model in a more clear way is presented, which benefits simulations of the nonlinear slosh dynamics. In addition, a new method is designed for suppressing the nonlinear slosh by filtering the driving commands. Comparison between the new method and a previously present method is also explored. Many simulations are conducted to analyze the sloshing dynamics and the effectiveness of the new method. Experimental results obtained from a moving rectangular container validate the dynamic effects and the effectiveness of the method.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081017-081017-12. doi:10.1115/1.4039287.

In this paper, online policy iteration reinforcement learning (RL) algorithm is proposed for motion control of four wheeled omni-directional robots. The algorithm solves the linear quadratic tracking (LQT) problem in an online manner using real-time measurement data of the robot. This property enables the tracking controller to compensate the alterations of dynamics of the robot's model and environment. The online policy iteration based tracking method is employed as low level controller. On the other side, a proportional derivative (PD) scheme is performed as supervisory planning system (high level controller). In this study, the followed paths of online and offline policy iteration algorithms are compared in a rectangular trajectory in the presence of slippage drawback and motor heat. Simulation and implementation results of the methods demonstrate the effectiveness of the online algorithm compared to offline one in reducing the command trajectory tracking error and robot's path deviations. Besides, the proposed online controller shows a considerable ability in learning appropriate control policy on different types of surfaces. The novelty of this paper is proposition of a simple-structure learning based adaptive optimal scheme that tracks the desired path, optimizes the energy consumption, and solves the uncertainty problem in omni-directional wheeled robots.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081018-081018-7. doi:10.1115/1.4039364.

In this paper, the problem of state constraints control is investigated for a class of output constrained flexible manipulator system with varying payload. The dynamic behavior of the flexible manipulator is represented by partial differential equations. To prevent states of the flexible manipulator system from violating the constraints, a barrier Lyapunov function which grows to infinity whenever its arguments approach to some limits is employed. Then, based on the barrier Lyapunov function, boundary control laws are given. To solve the problem of varying payload, an adaptive boundary controller is developed. Furthermore, based on the theory of barrier Lyapunov function and the adaptive algorithm, state constraints and output control under vibration condition can be achieved. The stability of the closed-loop system is carried out by the Lyapunov stability theory. Numerical simulations are given to illustrate the performance of the closed-loop system.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):081019-081019-15. doi:10.1115/1.4039366.

In this paper, we introduce two robust adaptive controllers for the human shank motion tracking problem that is inherent in neuromuscular electrical stimulation (NMES) systems. The control laws adaptively compensate for the unknown parameters that appear nonlinearly in the musculoskeletal dynamics while providing robustness to additive disturbance torques. The adaptive schemes exploit the Lipschitzian and/or the concave/convex parameterizations of the model functions. The resulting control laws are continuous and guarantee practical tracking for the shank angular position. The performance of the two robust adaptive controllers is demonstrated via simulations.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Dyn. Sys., Meas., Control. 2018;140(8):084501-084501-7. doi:10.1115/1.4039033.

A transient milling stability analysis method is presented based on linear dynamics. Milling stability is usually analyzed based on asymptotic stability methods, such as the Floquet theory and the Nyquist stability criterion. These theories define stability that can return to equilibrium in an infinite time horizon under any initial condition. However, as a matter of fact, most dynamic processes in milling operations occur on a finite time scale. The transient vibration can be caused by some disturbance in practical milling process. Heavy transient vibrations were observed in existing works, though the machining parameters were selected in the stability zone determined by the asymptotic stability method. The strong transient vibrations will severely decrease the machining surface quality, especially for small workpieces in which the majority of machining process is executed in a short period of time. The analysis method of the transient milling stability is seldom studied, and only some experiments and conjectures can be found. Here the transient milling stability is defined as transient energy growth in a finite time horizon, and the prediction method of transient stability is proposed based on linear dynamics. The eigenvalues and non-normal eigenvectors of the Floquet transition matrix are all used to predict the transient milling stability, while only eigenvalues are employed in the traditional asymptotic stability analysis method. The transient stability is finally analyzed by taking the maximum vibration energy growth and the maximum duration time of transient energy growth in a finite time for optimal selection of processing parameters.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(8):084502-084502-6. doi:10.1115/1.4039281.

This paper makes use of long short-term memory (LSTM) neural networks for forecasting probability distributions of time series in terms of discrete symbols that are quantized from real-valued data. The developed framework formulates the forecasting problem into a probabilistic paradigm as hΘ: X × Y → [0, 1] such that yYhΘ(x,y)=1, where X is the finite-dimensional state space, Y is the symbol alphabet, and Θ is the set of model parameters. The proposed method is different from standard formulations (e.g., autoregressive moving average (ARMA)) of time series modeling. The main advantage of formulating the problem in the symbolic setting is that density predictions are obtained without any significantly restrictive assumptions (e.g., second-order statistics). The efficacy of the proposed method has been demonstrated by forecasting probability distributions on chaotic time series data collected from a laboratory-scale experimental apparatus. Three neural architectures are compared, each with 100 different combinations of symbol-alphabet size and forecast length, resulting in a comprehensive evaluation of their relative performances.

Commentary by Dr. Valentin Fuster

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