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Research Papers

J. Dyn. Sys., Meas., Control. 2017;140(1):011001-011001-12. doi:10.1115/1.4037133.

Compressible fluid flow modeling for inclined lines is a challenging phenomenon due to the nonlinearity of the governing equations and the spatial–temporal dependency of the fluid density. In this paper, the transmission line analytical model is applied to the determination of inclined compressible fluid flow's dynamics. To establish this model, an exact transcendent solution is developed by solving the Navier–Stokes equation in the Laplace domain. A transfer function approximation, allowing the fluid flow transients determination, is recovered from the exact solution using residual calculations. The error resulting from the polynomial fraction approximation of the transfer functions is circumvented through frequency response corrections for the approximation to meet the exact function steady-state behavior. The effect of gravity and fluid compressibility on the fluid flow dynamics as well as the interplay between those two factors are illustrated through the pressure and flow rate's frequency and time responses.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011002-011002-8. doi:10.1115/1.4037266.

This paper presents a lateral motion stability control method for an electric vehicle (EV) driven by four in-wheel motors subject to time-variable high speeds and uncertain disturbances caused by severe road conditions, siding wind forces, and different tire pressures. In order to tackle the uncertain disturbances, an almost disturbance decoupling method (ADD) using sampled-data output feedback control which is more suitable for computer implementation is proposed based on the domination approach. The proposed controller can attenuate the disturbances' effect on the output to an arbitrary degree of accuracy. Simulation results under different speeds by matlab show the effectiveness of the control method.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011003-011003-9. doi:10.1115/1.4037265.

Vibration suppression is of fundamental importance to the performance of industrial robot manipulators. Cost constraints, however, limit the design options of servo and sensing systems. The resulting low drive-train stiffness and lack of direct load-side measurement make it difficult to reduce the vibration of the robot's end-effector and hinder the application of robot manipulators to many demanding industrial applications. This paper proposes a few ideas of iterative learning control (ILC) for vibration suppression of industrial robot manipulators. Compared to the state-of-the-art techniques such as the dual-stage ILC method and the two-part Gaussian process regression (GPR) method, the proposed method adopts a two degrees-of-freedom (2DOF) structure and gives a very lean formulation as well as improved effects. Moreover, in regards to the system variations brought by the nonlinear dynamics of robot manipulators, two robust formulations are developed and analyzed. The proposed methods are explained using simulation studies and validated using an actual industrial robot manipulator.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011004-011004-10. doi:10.1115/1.4037014.

This research presents an iterative framework for optimizing the plant and controller for complex systems by fusing expensive but valuable experiments with cheap yet less accurate simulations. At each iteration, G-optimal design is used to generate experiments and simulations within a prescribed design space that is shrunken in size after each successful iteration. The shrinking of the design space is determined through statistical characterization of a response surface model, and further shrinking is achieved at successive iterations through a numerical model correction factor that is driven by the results of experiments. An initial validation of this iterative design optimization framework was performed on an airborne wind energy (AWE) system, where tethers and an aerostat are used in place of a tower to elevate the turbine to high altitudes. Using a unique lab-scale setup for the experiments, the aforementioned iterative methodology was used to optimize the center of mass location and pitch angle set point for the airborne wind energy system. The optimum configuration yielded a substantial improvement in system responses as compared to a numerically optimized configuration. The framework was recently extended to include four variables (horizontal and vertical stabilizer areas, center of mass location, and pitch angle set point).

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011005-011005-10. doi:10.1115/1.4037286.

This paper presents a novel linear parameter-varying (LPV) model of an electro-hydraulic variable valve actuator (EHVVA) for internal combustion engines that is capable of continuously varying valve timing with dual-lift. The dual-lift is realized mechanically through a hydraulic lift control sleeve; valve opening (VO) terminal and closing seating velocities are regulated using a top or bottom snubber; and opening and closing timings, as well as lift profile area, are controlled by the valve actuation timing and hydraulic supply pressure. First, nonlinear mathematical system model is developed based on the Newton's law, orifice flow equation, and fluid constitutive law, where the fluid dynamics of the actuation solenoid valve, actuation piston, passages, and orifices, that influence the engine valve profile, are considered in detail. Second, to have an LPV control-oriented model, the order of nonlinear model is reduced and subsequently transformed into an LPV model with minimal deviation by carefully considering the system nonlinearities, time delay, and time-varying parameters. Calibration and validation experiments for both nonlinear and LPV models were performed on the test bench under different operational conditions. The key time-varying parameters, the time constant of the actuation piston top pressure and the discharge coefficient, are highly nonlinear as functions of temperature-sensitive fluid viscosity and are determined using the test data through the least-squares optimization. With the identified and calibrated model parameters, simulation results of both nonlinear and LPV models are in good agreement with the experimental ones under different operational conditions.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011006-011006-11. doi:10.1115/1.4037269.

In this paper, a simple model-free controller for electrically driven robot manipulators is presented using function approximation techniques (FAT) such as Legendre polynomials (LP) and Fourier series (FS). According to the orthogonal functions theorem, LP and FS can approximate nonlinear functions with an arbitrary small approximation error. From this point of view, they are similar to fuzzy systems and can be used as controller to approximate the ideal control law. In comparison with fuzzy systems and neural networks, LP and FS are simpler and less computational. Moreover, there are very few tuning parameters in LP and FS. Consequently, the proposed controller is less computational in comparison with fuzzy and neural controllers. The case study is an articulated robot manipulator driven by permanent magnet direct current (DC) motors. Simulation results verify the effectiveness of the proposed control approach and its superiority over neuro-fuzzy controllers.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011007-011007-11. doi:10.1115/1.4037283.

The kinematic model of an infinitely variable transmission (IVT) is introduced, and the nonlinear differential equation for the dynamic model of the IVT system with a permanent magnetic direct current (DC) motor and a magnetic brake is derived. To make the average of the input speed converge to a desired constant for any input power and output load, an integral time-delay feedback control combined with an open-loop control is used to adjust the speed ratio of the IVT. The speed ratio for the open-loop control is obtained by a modified incremental harmonic balance (IHB) method. Existence and convergence of a periodic solution are proved under a condition for parameters of the IVT system, and uniqueness of the periodic solution is proved by converting the nonlinear differential equation to a new differential equation that is Lipchitz in the dependent variable and piecewise continuous in the independent variable. A time-delay variable that is an approximation of the average of the input speed is used as the feedback to control the changing rate of the speed ratio. The IVT system with the time-delay control variable can be converted to a distributed-parameter system. Thus, the spectral Tau method is used to design the time-delay feedback control so that the IVT system is locally exponentially stable. The static error from the open-loop control is eliminated; the feedback control variable with time-delay is smoother than that without time-delay, which yields a lower control effort and more robust control design, since the time-delay variable that acts as a low-pass filter reduces the effect of the instantaneous change of the IVT system.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011008-011008-7. doi:10.1115/1.4037330.

Robust control often requires some adaptive approach in evaluating systems dynamics to handle parameters variations and external disturbances. Therefore, an error due to dynamics approximation is inevitably added to uncertainties already present in the model. This issue is addressed in this paper, through the combination of two robust techniques, Hinf and synergetic control. These latter are used to ensure reducing tracking error in the overall closed-loop system while guaranteeing stability via Lyapunov synthesis. With the aim of handling parameters variations, an indirect adaptive fuzzy scheme is used to elaborate system model. Simulation studies are conducted to assess the proposed approach on two practical systems, and the results are compared to a sliding mode proportional integral (PI)-based technique. It is to be noted that a large class of systems depicted as control affine systems will be considered in this paper. An induction motor and an inverted pendulum representing, respectively, a linear and a nonlinear system are utilized in this study showing improvement due to the suggested approach, in overall performance over its sliding mode control counterpart.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011009-011009-7. doi:10.1115/1.4037285.

In this paper, a simple feedback linearization method is used to improve the tracking performance of a linear hydraulic-actuator. This research uses an open-centered four-way valve to control the displacement of the hydraulic actuator, based upon an input command from the operator. In this research, the operator is modeled as a first-order system with a bandwidth frequency of 2 Hz. The feedback linearization method is used to adjust the operator input based on the measurement of fluid pressure on only one side of the actuator and the pump pressure that supplies the valve. No other sensing is needed. Using this approach, the R-squared value for tracking a sinusoidal displacement of the actuator and the bandwidth frequency of the actuator are increased. Furthermore, it is shown that the feedback linearization method reduces and nearly eliminates the load dependence of the tracking response, which means that operators should have less difficulty learning how to operate the machine over a wide range of conditions, and the overall productivity of the machine should go up. In summary, the elegance of this model is found in the fact that it is very simple to implement and that the alterations in output performance are greatly enhanced.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011010-011010-6. doi:10.1115/1.4037332.

In this paper, the problem of fault diagnosis in distributed parameter systems (DPS) is investigated. The behavior of DPS is best described by partial differential equation (PDE) models. In contrast to transforming the DPS into a finite set of ordinary differential equations (ODE) prior to the design of control or fault detection schemes by using significant approximations, thus reducing the accuracy and reliability of the overall system, in this paper, the PDE representation of the system is directly utilized to construct a fault detection observer. A fault is detected by comparing the detection residual, which is the difference between measured and estimated outputs, with a predefined detection threshold. Once the fault is detected, an adaptive approximator is activated to learn the fault function. The estimated fault parameters are then compared with their failure thresholds to provide an estimate of the remaining useful life of the system. The scheme is verified in simulations on a heat system which is described by parabolic PDEs.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011011-011011-10. doi:10.1115/1.4037331.

This paper presents a novel filter with low computational demand to address the problem of orientation estimation of a robotic platform. This is conventionally addressed by extended Kalman filtering (EKF) of measurements from a sensor suit which mainly includes accelerometers, gyroscopes, and a digital compass. Low cost robotic platforms demand simpler and computationally more efficient methods to address this filtering problem. Hence, nonlinear observers with constant gains have emerged to assume this role. The nonlinear complementary filter (NCF) is a popular choice in this domain which does not require covariance matrix propagation and associated computational overhead in its filtering algorithm. However, the gain tuning procedure of the complementary filter is not optimal, where it is often hand picked by trial and error. This process is counter intuitive to system noise based tuning capability offered by a stochastic filter like the Kalman filter. This paper proposes the right invariant formulation of the complementary filter, which preserves Kalman like system noise based gain tuning capability for the filter. The resulting filter exhibits efficient operation in elementary embedded hardware, intuitive system noise based gain tuning capability and accurate attitude estimation. The performance of the filter is validated using numerical simulations and by experimentally implementing the filter on an ARDrone 2.0 micro aerial vehicle (MAV) platform.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011012-011012-6. doi:10.1115/1.4037389.

Finite-time control problem of linear time-varying systems with input constraints is considered in this paper. Successive ellipsoidal approximations are used to estimate the state evolution of linear time-varying systems during a certain finite-time interval. An algorithm to design a controller based on approximations of state evolution is proposed. According to the proposed algorithm, the speed of state approaching equilibrium is optimized piecewisely using admissible control. The controller gain can be obtained by solving several quasi-convex optimization problems, which makes the design process computationally tractable. Simulation results show that the proposed controller can quickly reduce state deviation without violating input constraints.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011013-011013-15. doi:10.1115/1.4037390.

An accurate estimation of the intake oxygen concentration (IOC) is a prerequisite to develop the optimal control strategy because it directly affects the combustion and emissions. Since the IOC is determined based on the mass conservation law in the intake manifold, estimating the mass flow rate of the exhaust gas recirculation (EGR) is most critical. However, to estimate the EGR mass flow rate, the conventional orifice valve model causes extrapolation error or inaccurate estimation results under transient operating conditions. In order to improve the estimation performance, this study proposes a correction algorithm for estimating IOC. A dynamic correction state is determined for the orifice valve model. In addition, the intake pressure dynamics is also derived based on the energy conservation law in the intake manifold. Using these dynamic models, a nonlinear parameter varying model is determined, and an extended Kalman filter (EKF) is applied to derive the value of correction state. Furthermore, unmeasurable physical states of the nonlinear parameter varying model are estimated from an air system model that only requires the engine-equipped sensors of mass production engines. The correction algorithm is validated through the engine experiments that clearly demonstrate high accuracy of the IOC estimation during transient conditions, which may apply for the vehicle application.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):011014-011014-15. doi:10.1115/1.4037296.

A novel application of the adaptive fuzzy sliding-mode control (AFSMC) to the case of an antilock braking system (ABS) is proposed in this paper. ABS is a system in vehicles that allows the wheels to maintain tractive contact with the road and avoid uncontrolled skidding. By using ABS, the stopping distances on dry and slippery surfaces are expected to decrease. The maximum braking force is a nonlinear function of the slip ratios of the wheels, which is sensitive to the vehicle weight and road condition. In this research, a simple low-order model of the braking dynamics is considered and unmodeled dynamics are taken as uncertainties. The robust AFSMC method is used to regulate the wheel slip ratio toward the desired value. The proposed controller employs pulse width modulation (PWM) to generate the braking torque. There is no need to use any reference measured data or experimental knowledge of relevant experts to design the controller. A clear advantage is that the designed controller does not rely on the nonlinear tire–road friction model. The second Lyapunov theorem is employed to prove the closed-loop asymptotic stability. In the simulations, the multibody dynamics method is used for modeling the longitudinal motion of SAIPA X100 and X200 vehicle platforms. Furthermore, the actuation and the switching dynamics of the braking system are taken into account. Resulting performance is compared to the conventional sliding-mode and feedback linearization methods. Analysis of the simulation results reveals the effectiveness of proposed AFSMC method.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Dyn. Sys., Meas., Control. 2017;140(1):014501-014501-8. doi:10.1115/1.4037298.

In this paper, the application of an input disturbance observer (IDO)-based control, based on a simple input observer previously proposed and used for engine control, is demonstrated in two case studies. The first case study is longitudinal aircraft control with unmodeled aerodynamic nonlinearities satisfying matching conditions. The second case study is the control of an inverted pendulum on a cart which corroborates the ease of integration of IDO-based control into more complex controllers in situations when the matching condition is not satisfied. Improved robustness is demonstrated on an experimental system including changing the pendulum weight which is shown to have no effect on the overall control performance. In both case studies, if the IDO is not applied, the control performance is poor and leads to unstable operation.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(1):014502-014502-5. doi:10.1115/1.4037387.

In this paper, the problem of icing detection is considered for wind turbines (WTs) operating in medium speed wind region (region 2) and subject to a control law tracking the maximum delivery point of the power coefficient characteristic. Based on a robust observer of the rotor angular acceleration, rotor inertia is estimated in order to detect its eventual increase due to icing. Moreover, the observed value of rotor inertia can be potentially used for updating the controller parameters or to stop the turbine when icing is too severe. The proposed approach has been tested by intensive MatLab® simulations using the National Renewable Energy Laboratory 5 MW WT model.

Commentary by Dr. Valentin Fuster

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