Research Papers

J. Dyn. Sys., Meas., Control. 2017;140(6):061001-061001-15. doi:10.1115/1.4038267.

The Kalman filter has a long history of use in input deconvolution where it is desired to estimate structured inputs or disturbances to a plant from noisy output measurements. However, little attention has been given to the convergence properties of the deconvolved signal, in particular the conditions needed to estimate inputs and disturbances with zero bias. The paper draws on ideas from linear systems theory to understand the convergence properties of the Kalman filter when used for input deconvolution. The main result of the paper is to show that, in general, unbiased estimation of inputs using a Kalman filter requires both an exact model of the plant and an internal model of the input signal. We show that for unbiased estimation, an identified subblock of the Kalman filter that we term the plant model input generator (PMIG) must span all possible inputs to the plant and that the robustness of the estimator with respect to errors in model parameters depends on the eigenstructure of this subblock. We give estimates of the bias on the estimated inputs/disturbances when the model is in error. The results of this paper provide insightful guidance in the design of Kalman filters for input deconvolution.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061002-061002-11. doi:10.1115/1.4038492.

In this study, a control system was designed to control the robot's movement (The Mitsubishi RM-501 robot manipulator) based on the quantum neural network (QNN). A proposed method was used to solve the inverse kinematics in order to determine the angles values for the arm's joints when it follows through any path. The suggested method is the QNN algorithm. The forward kinematics was derived according to Devavit–Hartenberg representation. The dynamics model for the arm was modeled based on Lagrange method. The dynamic model is considered to be a very important step in the world of robots. In this study, two methods were used to improve the system response. In the first method, the dynamic model was used with the traditional proportional–integral–derivative (PID) controller to find its parameters (Kp, Ki, Kd) by using Ziegler Nichols method. In the second method, the PID parameters were selected depending on QNN without the need to a mathematical model of the robot manipulator. The results show a better response to the system when replacing the traditional PID controller with the suggested controller.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061003-061003-11. doi:10.1115/1.4038488.

Fractional uncertainties are involved in many practical systems. Currently, there is a lack of research results about such general class of nonlinear systems in the context of learning control. This paper presents a Lyapunov-synthesis approach to repetitive learning control (RLC) being unified due to the use of the direct parametrization and adaptive bounding techniques. To effectively handle fractional uncertainties, the estimation method for such uncertainties is elaborated to facilitate the controller design and convergence analysis. Its novelty lies in the less requirement for the knowledge about the system undertaken. Unsaturated- and saturated-learning algorithms are, respectively, characterized by which both the boundedness of the variables in the closed-loop system undertaken and the asymptotical convergence of the tracking error are established. Experimental results are provided to verify the effectiveness of the presented learning control.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061004-061004-13. doi:10.1115/1.4038489.

The lateral excessive sway motion caused by pedestrian traffic has attracted great public attention in the past decades years. However, the theories about exploring the effect of pedestrian on the lateral dynamic properties of structure are scarce. The new contribution of this paper is that a new pedestrian-structure system is proposed for exploring the effect of human on structural dynamic properties based on a sway assumption. Study shows that pedestrian deteriorates the natural frequency of structure and improves structural damping. The influence tendencies of pedestrian on structure can be supported by measurements. The further parametric study shows that the changes of human dynamic parameters have some evident impacts on structural dynamic performances. For example, the increase of leg damping can trigger an improvement of structural damping capacity. In addition, the walking step frequency closing structural harmonic natural frequency can incur the worst response. The increase of step width deteriorates lateral vibration and structural frequency but can slightly improve structural damping. One of essential reasons influencing structural lateral dynamic properties is the dynamic human system including body mass, damping, stiffness, and its motion behavior such as step frequency. This theory is proposed to analyze how pedestrian alters the lateral dynamic performances on those sensitive structures such as the footbridges or stadium bleachers. For example, how the variation of step width influences the change of natural frequency of structure?

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061005-061005-10. doi:10.1115/1.4038388.

Drillstring vibration can cause fatigue failure of the drill pipe, premature wear of the bit, and a decreased drilling efficiency; therefore, it is important to accurately model the drillstring and bottomhole assembly (BHA) dynamics for vibration suppression. The dynamic analysis of directional drilling is more important, considering its wide application and the advantage of increasing drilling and production efficiencies; however, the problem is complex because the large bending can bring nonlinearities to drillstring vibration and the interaction with the wellbore can occur along the entire drillstring. To help manage this problem, this paper discusses a dynamic finite element method (FEM) model to characterize directional drilling dynamics by linearizing the problem along the well's central axis. Additionally, the rig force and drillstring/wellbore interaction are modeled as a boundary condition to simulate realistic drilling scenarios. The proposed modeling framework is verified using comparisons with analytical solutions and literatures. The utility of the proposed model is demonstrated by analyzing the dynamics of a typical directional drillstring.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061006-061006-11. doi:10.1115/1.4038536.

Switch-mode hydraulic control is a compact and theoretically efficient alternative to throttling valve control or variable displacement pump control. However, a significant source of energy loss in switch-mode circuits is due to throttling during valve transitions. Hydraulic soft switching was previously proposed as a method of reducing the throttling energy loss, by absorbing, in a small variable volume chamber, the flow that would normally be throttled across the transitioning high-speed valve. An active locking mechanism was previously proposed that overcomes the main challenge with soft switching, which is a lock mechanism that releases quickly and with precise timing. This prior work demonstrated a reduction in energy losses by 66% compared to a control circuit. In this paper, a numerical model is developed for a switch-mode virtually variable displacement pump (VVDP) circuit, utilizing the proposed soft switch. The model is then used as a means of designing a proof of concept prototype to validate the model. The prototype design includes methods for controlling the soft switch spring preload, travel distance, piston displacement required to unlock the soft switch, valve command duty cycle, switching cycle period, and load pressure. Testing demonstrated that the soft switch circuit performed as expected in a baseline condition. The operating region for this prototype was found to be quite narrow. However, the model does a good job of predicting the displacement of the soft switch.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061007-061007-6. doi:10.1115/1.4038504.

Farming and agriculture is an area that may benefit from improved use of automation in order to increase working hours and improve food quality and safety. In this paper, a commercial robot was purchased and modified, and crop row navigational software was developed to allow the ground-based robot to autonomously navigate a crop row setting. A proportional–integral–derivative (PID) controller and a fuzzy logic controller were developed to compare the efficacy of each controller based on which controller navigated the crop row more reliably. Results of the testing indicate that both controllers perform well, with some differences depending on the scenario.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061008-061008-9. doi:10.1115/1.4038537.

A challenge in realizing switch-mode hydraulic circuits is the need for a high-speed valve with fast transition time and high switching frequency. The work presented includes the design and modeling of a suitable valve and experimental demonstration of the prototype in a hydraulic boost converter. The design consists of two spools driven by crank-sliders, designed for 120 Hz maximum switching frequency at a flow rate of 22.7 lpm. The fully open throttling loss is designed for <2% of the rated pressure of 34.5 MPa. The transition time is less than 5% (0.42 ms at 120 Hz) of the total cycle and the duty cycle is adjustable from 0 to 1. Leakage and viscous friction losses in the design are less than 2% of the rated hydraulic energy per cycle. The experimental results agreed well with the model resulting in a 3% variation in transition time. The use of the high-speed valve in a pressure boosts converter demonstrated boost ratio capabilities of 1.08–2.06.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061009-061009-9. doi:10.1115/1.4038243.

Condition monitoring and fault diagnostics in rotorcraft have significant effect on improving safety level and reducing operational and maintenance costs. In this paper, a new method is proposed for fault detection and diagnoses of AH-64D (Apache helicopter) tail rotor drive-shaft problems. The proposed method depends on decomposing signal into different frequency ranges using mother wavelet. The most informative part of the vibration signal is then determined by calculating Shannon entropy of each part. Bispectrum is calculated for this part to investigate quadratic nonlinearities in this segment. Then, search algorithm is used to extract minimum number of indicative features from the bispectrum, which are then fed to classification algorithms. In order to quantitatively evaluate the proposed method, six classification algorithms are compared against each other such as fine K-nearest neighbor (KNN), cubic KNN, quadratic discriminant analysis, linear support vector machine (SVM), Gaussian SVM, and neural network. Comparison criteria include accuracy, precision, sensitivity, F score, true alarm, recall, and error classification accuracy (ECA). The proposed method is verified using real-world vibration data collected from a dedicated AH-64D helicopter tail rotor drive train (TRDT) research test bed. The proposed algorithm proves its ability in finding minimum number of indicative features and classifying the shaft faults with superior performance.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061010-061010-7. doi:10.1115/1.4038649.

This paper addresses the problem of leader-following consensus control of general linear multi-agent systems (MASs) with diverse time-varying input delays under the integral quadratic constraint (IQC) framework. A novel exact-memory distributed output-feedback delay controller structure is proposed, which utilizes not only relative estimation state information from neighboring agents but also local real-time information of time delays and the associated dynamic IQC-induced states from the agent itself for feedback control. As a result, the distributed consensus problem can be decomposed into H stabilization subproblems for a set of independent linear fractional transformation (LFT) systems, whose dimensions are equal to that of a single agent plant plus the associated local IQC dynamics. New delay control synthesis conditions for each subproblem are fully characterized as linear matrix inequalities (LMIs). A numerical example is used to demonstrate the proposed approach.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061011-061011-12. doi:10.1115/1.4038534.

This paper presents a model for predicting the optimal magnet placement in magnetic cilia devices that achieve individual control via localization of the driving magnetic field. In this configuration, each cilium is controlled by a magnetic field source which is limited in spatial extent, and the cilia are spaced sufficiently far apart that the control remains uncoupled. An implementation is presented using an electromagnetic field source to attain large-deformation actuation (transverse deflections of 47% of the length). The large deformations are achieved by exploiting the nonlinear response of a flexible cantilever in a nonuniform magnetic field. However, the same nonlinearities also pose a modeling challenge: the overall performance is sensitive to the location of the electromagnet and the location that produces the largest deflections is nonlinearly dependent on the strength of the magnetic field. The nonlinear displacement of the cilium is predicted using a finite element model of the coupled magnetic–structural equations for static inputs at varying field strengths and magnet positions. The deflection at the model-predicted optimal placement is within 5% of the experiment-predicted optimal placement. Moreover, actuator placement using a model that does not include the nonlinearities is estimated to result in performance loss of about 50% peak deflection. This result emphasizes the importance of capturing nonlinearities in the system design.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061012-061012-7. doi:10.1115/1.4038493.

When a parallel-plate electrostatic actuator (ESA) is driven by a voltage source, pull-in instability limits the range of displacement to one-third of the gap between plates. In this paper, a nonlinear active disturbance rejection controller (NADRC) is originally developed on the ESA. Our control objectives are stabilizing and increasing the displacement of an ESA to 99.99% of its full gap. Most of the reported controllers in literature are based on linearized models of the ESAs and depend on detailed model information of them. However, the ESA is inherently nonlinear and has model uncertainties due to the imperfections of microfabrication and packaging. The NADRC consists of a nonlinear extended state observer (NESO) and a feedback controller. The NESO is used to estimate system states and unknown nonlinear dynamics for the ESA. Therefore, it does not require accurate model. We simulate the NADRC on a nonlinear ESA in the presences of external disturbance, system uncertainties, and noise. The simulation results verify the effectiveness of the controller by successfully extending the travel range of ESA beyond pull-in point. They also demonstrate that the controller is robust against both disturbance and parameter variations, and has low sensitivity to measurement noise. Furthermore, the stability for the control system with NADRC is theoretically proved.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061013-061013-11. doi:10.1115/1.4038491.

This paper concerns the problems of stability and robust model reference tracking control for a class of switched nonlinear systems with input delay under asynchronous switching. By proposing a new Lyapunov–Krasovskii functional, and using free-weighting matrices and average dwell-time (ADT) technique, new input-to-state stability (ISS) conditions are derived in terms of linear matrix inequalities (LMIs) under a certain delay bound. Then, robust model reference tracking control problem is studied based on the proposed Lyapunov–Krasovskii functional; Finally a kind of state feedback control law which guarantees robust model reference tracking performance is proposed. Illustrative examples are presented to demonstrate the efficacy and feasibility of results.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):061014-061014-8. doi:10.1115/1.4038654.

In this paper, we derive an expression for the loss of optimal performance (compared to the corresponding linear-quadratic optimal performance with the instantaneous full-state feedback) when the continuous-time finite-horizon linear-quadratic optimal controller uses the estimates of the state variables obtained via a reduced-order observer. It was shown that the loss of optimal performance value can be found by solving the differential Lyapunov equation whose dimensions are equal to dimensions of the reduced-order observer. A proton exchange membrane fuel cell example is included to demonstrate the loss of optimal performance as a function of the final time. It can be seen from the simulation results that the loss of optimal performance value can be very large. The loss of optimal performance value can be drastically reduced by using the proposed least-square formulas for the choice of the reduced-order observer initial conditions.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(6):061015-061015-12. doi:10.1115/1.4039210.

We propose a novel modeling, estimation, and control framework for homogeneous charge compression ignition (HCCI) engines, which, by utilizing direct in-cylinder pressure sensing, can detect, and react to, the wide spectrum of combustion, thereby allowing for the prevention or even recovery from partial burn or misfire, while significantly improving the stability of transition control. For this, we first develop a discrete-time cyclic control-oriented model of the HCCI process, for which we completely replace the Arrhenius integral by quantities based on the in-cylinder pressure sensing. We then propose a nonlinear state feedback control based on the exact feedback linearization and the switching linear quadratic regulators (LQRs), and also present how the state and other quantities necessary for this control can be estimated by using the in-cylinder pressure sensing. We also provide a new modeling approach for heat transfer, which, through principal component analysis (PCA), can systematically allow us to choose most significant variables, thereby substantially improving control and estimation precision. Simulation studies using a continuous-time detailed HCCI engine model built on matlab/simulink and Cantera Toolbox are also performed to demonstrate the efficacy of our proposed framework for the scenarios of engine load transition and partial burn recovery with the enlarged regions-of-attraction with less stringent actuation limitation also shown.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(6):061016-061016-8. doi:10.1115/1.4039212.

This paper presents an improved speed estimator for a permanent magnet synchronous motor (PMSM). It focuses on hybrid electric vehicles (HEVs). The speed estimator is based on reactive power model reference adaptive system (Q-MRAS). The MRAS parameters are tuned using particle swarm optimization (PSO) algorithms. The proposed method has been experimentally verified with a 100 kW, 5000 rpm PMSM, and a good agreement between the measured speed and the estimated speed is found. It is shown that the proposed method is able to handle the transition into the flux weakening mode without any problem.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(6):061017-061017-11. doi:10.1115/1.4039216.

This paper proposes an energy management strategy for a hybrid electric vehicle (HEV) with a turbocharged diesel engine. By introducing turbocharger to the HEV powertrain, air path dynamics of engine becomes extremely complex and critical to engine torque response during transient processes. Traditional strategy that adopts steady-state-map based engine model may not work properly in this situation as a result of its incapability of accurately capturing torque response. Thus, in this paper, a physical-law based air path model is utilized to simulate turbo “lag” phenomenon and predict air charge in cylinder. Meanwhile, engine torque boundaries are obtained on the basis of predicted air charge. A receding horizon structure is then implemented in optimal supervisory controller to generate torque split strategy for the HEV. Simulations are conducted for three cases: the first one is rule-based torque-split energy management strategy without optimization; the second one is online optimal control strategy using map-based engine model; and the third one is online optimal control strategy combining air path loop model. The comparison of the results shows that the proposed third method has the best fuel economy of all and demonstrates considerable improvements of fuel saving on the other two methods.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Dyn. Sys., Meas., Control. 2017;140(6):064501-064501-7. doi:10.1115/1.4038389.

We put forward the motor active flexible suspension and investigate its dynamic effects on the high-speed train bogie. The linear and nonlinear hunting stability are analyzed using a simplified eight degrees-of-freedom bogie dynamics with partial state feedback control. The active control can improve the function of dynamic vibration absorber of the motor flexible suspension in a wide frequency range, thus increasing the hunting stability of the bogie at high speed. Three different feedback state configurations are compared and the corresponding optimal motor suspension parameters are analyzed with the multi-objective optimal method. In addition, the existence of the time delay in the control system and its impact on the bogie hunting stability are also investigated. The results show that the three control cases can effectively improve the system stability, and the optimal motor suspension parameters in different cases are different. The direct state feedback control can reduce corresponding feed state's vibration amplitude. Suppressing the frame's vibration can significantly improve the running stability of bogie. However, suppressing the motor's displacement and velocity feedback are equivalent to increasing the motor lateral natural vibration frequency and damping, separately. The time delay over 10 ms in control system reduces significantly the system stability. At last, the effect of preset value for getting control gains on the system linear and nonlinear critical speed is studied.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(6):064502-064502-7. doi:10.1115/1.4038652.

This paper presents the development of a robotic finger driven by nonconventional actuators, consisting of thin shape memory alloy (SMA) wires. In order to monitor and control the angles formed by each phalanx, a specific system for capturing and interpreting digital images was implemented. By image processing, this system is capable to determine the angles without the need for installation of phalanx rotation sensors, leading to weight and volume reduction of the prototype. For this artificial vision system, a simple camera with a fuzzy logic control technique was used, which was very effective in monitoring the position of the robotic finger.

Commentary by Dr. Valentin Fuster

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