Research Papers

J. Dyn. Sys., Meas., Control. 2018;140(7):071001-071001-7. doi:10.1115/1.4038647.

We present two alternative methods for fault detection and isolation (FDI) with redundant Microelectromechanical system (MEMS) inertial measurement units (IMUs) in inertial navigation systems (INS) based on nonlinear observers (NLOs). The first alternative is based on the parity space method, while the second is expanded with quaternion-based averaging and FDI. Both alternatives are implemented and validated using data gathered in a full-scale experiment on an offshore vessel. Data from three identical MEMS IMUs and the vessel's own industrial sensors are used to verify the methods' FDI capabilities. The results reveal that when it comes to FDI of the IMUs' angular rate sensors, there are differences between the two methods. The navigation algorithm based on quaternion weighting is essentially unaffected by the failure of an angular rate sensor, while the parity-space-method-based alternative experiences a perturbation.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071002-071002-9. doi:10.1115/1.4038658.

Energetic macroscopic representation (EMR) is an effective graphical modeling tool for multiphysical systems, and EMR model clearly illustrates the power flow and interaction between different subcomponents. This paper presents the modeling and control of a novel linear-driven electro-hydrostatic actuator (LEHA) with EMR method. The LEHA is a novel electro-hydrostatic actuation system, and the hydraulic cylinder in LEHA is driven by a novel collaborative rectification pump (CRP), which incorporates two miniature cylinders and two spool valves. EMR model clearly illustrated the powertrain in LEHA and interaction between each components. Based on EMR model, a maximum control structure (MCS) is easily deduced using the action and reaction principle, and then the practicable controller deduced from MCS shows satisfying performance in the simulation.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071003-071003-13. doi:10.1115/1.4038657.

This paper proposed a full vehicle state estimation and developed an integrated chassis control by coordinating electronic stability control (ESC) and torque vectoring differential (TVD) systems to improve vehicle handling and stability in all conditions without any interference. For this purpose, an integrated TVD/ESC chassis system has been modeled in Matlab/Simulink and applied into the vehicle dynamics model of the 2003 Ford Expedition in carsim software. TVD is used to improve handling in routine and steady-state driving conditions and ESC is mainly used as the stability controller for emergency maneuvers or when the TVD cannot improve vehicle handling. By the ββ˙ phase plane, vehicle stable region is determined. Inside the reference region, the handling performance and outside the region the vehicle stability has been in question. In order to control the integrated chassis system, a unified controller with three control layers based on fuzzy control strategy, ββ˙ phase plane, longitudinal slip, and road friction coefficient of each tire is designed in Matlab/Simulink. To detect the control parameters, a state estimator is developed based on unscented Kalman filter (UKF). Bees algorithm (BA) is employed to optimize the fuzzy controller. The performance and robustness of the integrated chassis system and designed controller were conformed through routine and extensive simulations. The simulation results via a co-simulation of MATLAB/Simulink and CarSim indicated that the designed integrated ESC/TVD chassis control system could effectively improve handling and stability in all conditions without any interference between subsystems.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071004-071004-11. doi:10.1115/1.4038651.

An online fast path following control algorithm subject to contouring error tolerance and other prototypical constraints, analogous to a racing car within track boundaries, is presented. A receding horizon quadratic programming (QP) for real-time implementation on electromechanical systems is proposed. A key feature of the algorithm is that the challenging constrained minimal-time optimization is approximated by minimizing the distance between an unattainable target and actual location when moving along the contour, mimicking pursuing rabbit lures in greyhound racing. Modeling errors and other uncertainties in implementation are compensated for by observer state feedback, which provides real-time updates of initial states for every receding horizon optimization. Applying the proposed online method, the requirement of an accurate model from conventional offline trajectory planning methods is relaxed. The proposed method is demonstrated by experimental results from a 1 kHz sampling rate implementation on a multi-axis nanolithographic position system.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071005-071005-12. doi:10.1115/1.4038650.

This paper presents the experimental validation and dynamic similarity analysis for a lab-scale version of an airborne wind energy (AWE) system executing closed-loop motion control. Execution of crosswind flight patterns, achieved in this work through the asymmetric motion of three tethers, enables dramatic increases in energy generation compared with stationary operation. Achievement of crosswind flight in the lab-scale experimental framework described herein allows for rapid, inexpensive, and dynamically scalable characterization of new control algorithms without recourse to expensive full-scale prototyping. We first present the experimental setup, then derive dynamic scaling relationships necessary for the lab-scale behavior to match the full-scale behavior. We then validate dynamic equivalence of crosswind flight over a range of different scale models of the Altaeros Buoyant airborne turbine (BAT). This work is the first example of successful lab-scale control and measurement of crosswind motion for an AWE system across a range of flow speeds and system scales. The results demonstrate that crosswind flight can achieve significantly more power production than stationary operation, while also validating dynamic scaling laws under closed-loop control.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071006-071006-10. doi:10.1115/1.4038656.

Temperature is one of the essential parameter in a fermentation process, which affects the thermal movement of cells. The temperature range for such processes is very tight and must be maintained precisely for efficient operation. Therefore, in this work combination of fractional calculus and two degrees-of-freedom proportional–integral–derivative (2DOF-PID) controller is proposed for desired temperature control of bioreactor. The 2DOF-PID controller incorporates an extra control loop, whereas fractional operator offers additional tractability for alteration in system dynamics. In order to achieve efficient execution of the control strategies, design parameters are optimized with the help of nondominated sorted genetic algorithm-II (NSGA-II) and Cuckoo search algorithm (CSA). NSGA-II-tuned controllers perform better than the CSA-tuned controllers. Further, the results show that the proposed controller regulates the temperature of bioreactor in a more robust and efficient manner in comparison to other designed controllers.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071007-071007-8. doi:10.1115/1.4038714.

In this paper, a new initial rotor angle position estimation method for the sensorless high-speed brushless direct current (DC) motor (HS-BLDCM) is proposed. Two groups of special three-phase conduction current pulse signals are injected into the three phases of the motor, and the mathematical formulation for the initial angle position estimation is illustrated. The initial rotor position is expressed as a function of the line voltage, the phase current derivative, and the average value of d–q frame stator inductance. Particularly, the independent parameters of the initial rotor angle position are eliminated in the mathematical model. The cooperative simulation results based on Maxwell and Simplorer and the experimental results demonstrate that the proposed method is effective with the estimation error less than 0.2 deg electrical in simulation and 5 deg electrical in experiment.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071008-071008-10. doi:10.1115/1.4038715.

Mechanical insufflation-exsufflation (MI-E) secretion clearance system is usually utilized to help patients to clear secretion. In this paper, to obtain the essential dynamic characteristics of volume-controlled (VC) MI-E secretion clearance system with double lungs, a dimensionless model of the MI-E secretion clearance system is derived. Furthermore, for the validation of the mathematical model, a prototype VC MI-E secretion clearance system is proposed. Finally, to reveal the impact of key parameters on VC MI-E secretion clearance system, a dimensionless orthogonal experiment with four factors and five levels was processed. And then, coupling effects of two lungs on VC MI-E secretion clearance system were illustrated. This paper can be referred to in treatment of secretion clearance with VC secretion clearance system.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071009-071009-12. doi:10.1115/1.4038800.

For linear dynamic systems with uncertain parameters, design of controllers which drive a system from an initial condition to a desired final state, limited by state constraints during the transition is a nontrivial problem. This paper presents a methodology to design a state constrained controller, which is robust to time invariant uncertain variables. Polynomial chaos (PC) expansion, a spectral expansion, is used to parameterize the uncertain variables permitting the evolution of the uncertain states to be written as a polynomial function of the uncertain variables. The coefficients of the truncated PC expansion are determined using the Galerkin projection resulting in a set of deterministic equations. A transformation of PC polynomial space to the Bernstein polynomial space permits determination of bounds on the evolving states of interest. Linear programming (LP) is then used on the deterministic set of equations with constraints on the bounds of the states to determine the controller. Numerical examples are used to illustrate the benefit of the proposed technique for the design of a rest-to-rest controller subject to deformation constraints and which are robust to uncertainties in the stiffness coefficient for the benchmark spring-mass-damper system.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071010-071010-9. doi:10.1115/1.4038636.

One very effective approach to suppress hysteresis from the piezoelectric actuator is to use the charge control across the associated capacitance. The charge driver often uses an additional capacitor connected to the piezo-actuator in series for the charge sense feedback control. When this charge sense is used with a voltage drive for the charge control, the applied voltage will include two parts. The one is the voltage drop across the useful electro-mechanical part and effectively converted to the driving force, whereas the other part indicates the equivalent voltage drop due to the hysteresis. In our research, we noticed that it is possible to use a simple estimator as the hysteresis voltage observer and use it to precompensate for the voltage drop. Comparing to the conventional hysteresis suppression achieved by the closed-loop positional control, we show significant improvement of the control performance. For dynamic applications, we also proposed a combination of the Preisach model with the hysteresis estimator to better suppress the nonlinear behavior. A series of experiments were conducted to demonstrate the performance improvement of the proposed compensator. A 10 nm and 25 nm maximum tracking error can be maintained while tracking a staircase reference and a 30 Hz sinusoidal signal, respectively.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071011-071011-9. doi:10.1115/1.4038905.

A new framework for route guidance, as part of a path decision support tool, for off-road driving scenarios is presented in this paper. The algorithm accesses information gathered prior to and during a mission which are stored as layers of a central map. The algorithm incorporates a priori knowledge of the low resolution soil and elevation information and real-time high-resolution information from on-board sensors. The challenge of high computational cost to find the optimal path over a large-scale high-resolution map is mitigated by the proposed hierarchical path planning algorithm. A dynamic programming (DP) method generates the globally optimal path approximation based on low-resolution information. The optimal cost-to-go from each grid cell to the destination is calculated by back-stepping from the target and stored. A model predictive control algorithm (MPC) operates locally on the vehicle to find the optimal path over a moving radial horizon. The MPC algorithm uses the stored global optimal cost-to-go map in addition to high resolution and locally available information. Efficacy of the developed algorithm is demonstrated in scenarios simulating static and moving obstacles avoidance, path finding in condition-time-variant environments, eluding adversarial line of sight detection, and connected fleet cooperation.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071012-071012-10. doi:10.1115/1.4038859.

The increasingly complex oil and gas wellbore condition and the need of drilling in more challenging downhole environments motivate rising research on the drilling control system based on real-time state feedback or measurements from the bottom of the wellbore. However, due to the complex downhole condition and cost-viability, mud pulse telemetry is normally used in this industry to transmit the downhole measurements to the surface, which can cause a large data communication delay as a result of its low bandwidth and slow mud pulse transmission. Since the major drilling control is on the surface, an observer is required to estimate the real-time states of the drilling dynamics as well as the downhole condition, based on the delayed downhole measurement. In this study, we first construct a drilling system dynamics model with coupled axial and torsional dynamics. Then, with the existence of a large output measurement delay, two chain-observer design strategies are introduced for the case of slowly varying control inputs and that of fast-varying control inputs, respectively. The effectiveness of the proposed observer design methods is shown through numerical results.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071013-071013-12. doi:10.1115/1.4039099.

The Dubins traveling salesman problem (DTSP) has generated significant interest over the last decade due to its occurrence in several civil and military surveillance applications. This problem requires finding a curvature constrained shortest path for a vehicle visiting a set of target locations. Currently, there is no algorithm that can find an optimal solution to the DTSP. In addition, relaxing the motion constraints and solving the resulting Euclidean traveling salesman problem (ETSP) provide the only lower bound available for the DTSP. However, in many problem instances, the lower bound computed by solving the ETSP is far below the cost of the feasible solutions obtained by some well-known algorithms for the DTSP. This paper addresses this fundamental issue and presents the first systematic procedure for developing tight lower bounds for the DTSP.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071014-071014-10. doi:10.1115/1.4039151.

The problem of robust output tracking is studied for a class of uncertain nonlinear systems in the presence of structure uncertainties, external disturbances, and unknown time-varying virtual control coefficients. In this study, it is supposed that the upper bounds of external disturbances and that the upper and lower bounds of unknown time-varying virtual control coefficients are unknown. By employing a simple structure neural network (NN), the unknown structure uncertainties are approximated. A class of backstepping approach-based adaptive robust controllers is synthesized for such uncertain nonlinear systems. By making use of Lyapunov functional approach, it is also shown that the proposed adaptive robust backstepping output tracking controller can guarantee the tracking error between the system output and the desired reference signal to converge asymptotically to zero. Finally, two numerical examples are given to demonstrate the effectiveness of the proposed controller.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071015-071015-8. doi:10.1115/1.4039152.

This paper proposes an application of the switching gain-scheduled (S-GS) proportional–integral–derivative (PID) control technique to the electronic throttle control (ETC) problem in automotive engines. For the S-GS PID controller design, a published linear parameter-varying (LPV) model of the electronic throttle valve (ETV) is adopted whose dynamics change with both the throttle valve velocity variation and the battery voltage fluctuation. The designed controller consists of multiple GS PID controllers assigned to local subregions defined for varying throttle valve velocity and battery voltage. Hysteresis switching logic is employed for switching between local GS PID controllers based on the operating point. The S-GS PID controller design problem is formulated as a nonconvex optimization problem and tackled by solving its convex subproblems iteratively. Experimental results demonstrate overall superiority of the S-GS PID controller to conventional controllers in reference tracking performance of the throttle valve under various scenarios.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071016-071016-9. doi:10.1115/1.4039469.

The wheel-rail contact strongly influences the dynamics of the railway vehicles. This interaction is affected by several conditioning factors such as vehicle speed, wear, and adhesion level, and, moreover, it is nonlinear. As a consequence, the modeling and the observation of this kind of phenomenon are complex tasks but, at the same time, they constitute a fundamental step for the estimation of the adhesion level or for the vehicle condition monitoring. This paper presents a novel technique for the real time estimation of the wheel-rail contact forces that allows an a priori no knowledge of this kind of mechanism because a random walk model (RWM) approach is adopted and integrated in a complete model based estimator for railway vehicle.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071017-071017-10. doi:10.1115/1.4039283.

We present time-optimal trajectories for a steered agent with constraints on speed, lateral acceleration, and turning rate for the problem of reaching a point on the plane in minimum time with free terminal heading angle. Both open-loop and state-feedback forms of optimal controls are derived through application of Pontryagin's minimum principle. We apply our results for the single agent to solve a multi-agent coverage problem in which each agent has constraints on speed, lateral acceleration, and turning rate.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071018-071018-7. doi:10.1115/1.4039282.

The objectives of this research are to explore the inertial-torque characteristics of an inline, internal combustion engine with connecting-rod joints that are evenly spaced about the centerline of the crankshaft, and to evaluate the goodness of a mass approximation that is customarily used in machine design textbooks. In this research, the number of pistons within the internal combustion engine is varied from 1 to 8. In order to generalize the results, the inertial-torque equations are nondimensionalized and shown to depend upon only four nondimensional groups, all related to the mass and geometry properties of the connecting rod. As shown in this research, the inertial-torque imbalance is greatest for an engine with two pistons, and that a dramatic reduction in the torque imbalance may be obtained for engine designs that use four or more pistons. It is also shown in this paper that the customary mass approximations for the connecting rod may be used to simplify the analysis for all engine designs without a significant loss of modeling accuracy.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):071019-071019-11. doi:10.1115/1.4039280.

This paper proposes a sensor fusion algorithm to determine the motor torque for power-assist electric bicycles. Instead of using torque sensors to directly measure the pedaling torque, outputs from a wheel encoder and a six-axis inertial measurement unit (IMU) are processed by the fusion algorithm to estimate the slope angle of the road and the longitudinal acceleration of the bicycle for conducting mass compensation, gravity compensation, and friction compensation. The compensations allow the ride of the electric bicycle on hills to be as effortless as the ride of a plain bicycle on the level ground regardless of the weight increase by the battery and the motor. The sensor fusion algorithm is basically an observer constructed on the kinematic model which describes the time-varying characteristics of the gravity vector observed from a frame moving with the bicycle. By exploiting the structure of the observer model, convergence of the estimation errors can be easily achieved by selecting two constant, subgain matrices in spite of the time-varying characteristics of the model. The validity of the sensor fusion is verified by both numerical simulations and experiments on a prototype bicycle.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Dyn. Sys., Meas., Control. 2018;140(7):074501-074501-9. doi:10.1115/1.4038860.

This paper presents a solution to the optimal control problem of a three degrees-of-freedom (3DOF) wave energy converter (WEC). The three modes are the heave, pitch, and surge. The dynamic model is characterized by a coupling between the pitch and surge modes, while the heave is decoupled. The heave, however, excites the pitch motion through nonlinear parametric excitation in the pitch mode. This paper uses Fourier series (FS) as basis functions to approximate the states and the control. A simplified model is first used where the parametric excitation term is neglected and a closed-form solution for the optimal control is developed. For the parametrically excited case, a sequential quadratic programming approach is implemented to solve for the optimal control numerically. Numerical results show that the harvested energy from three modes is greater than three times the harvested energy from the heave mode alone. Moreover, the harvested energy using a control that accounts for the parametric excitation is significantly higher than the energy harvested when neglecting this nonlinear parametric excitation term.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;140(7):074502-074502-7. doi:10.1115/1.4039470.

During severe accidents in a nuclear power plant, in-vessel cooling may be required to mitigate the risk of vessel failure in the event of core meltdown and subsequent corium contamination. This cooling technique, known as in-vessel retention (IVR), entails flooding the reactor cavity with water. If the temperatures are sufficiently high, IVR may cause downward facing boiling (DFB) on the outer surface of the reactor pressure vessel (RPV), which gives rise to two-phase thermal-hydraulic phenomena. The regimes in DFB may range from film boiling to nucleate boiling, where the efficiency of cooling varies immensely between these two. In the DFB geometry under consideration (i.e., a hemispherical vessel), the collected signals/images are heavily contaminated by unavoidable noise and spurious disturbances, which hinder the extraction of pertinent information, such as film thickness and the boiling cycle. This paper proposes a wavelet-based filtering of sensor measurements for denoising of the nonstationary signals with the future objective of estimating the thickness of vapor films in real time, as needed for process monitoring and control. The proposed concept has been validated with experimental data recorded from a pool boiling apparatus for physics-based understanding of the associated phenomena.

Commentary by Dr. Valentin Fuster


J. Dyn. Sys., Meas., Control. 2018;140(7):077001-077001-1. doi:10.1115/1.4039017.

The following correction (Ninevah University) is to be noted with the affiliation instead of (University of Mosul).

Commentary by Dr. Valentin Fuster

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