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Research Papers

J. Dyn. Sys., Meas., Control. 2017;140(5):051001-051001-9. doi:10.1115/1.4038171.

Error compensation technology is used for improving accuracy and reducing costs. Dynamic error compensation techniques of coordinate measuring machine (CMM) are still under study; the major problem is a lack of suitable models, which would be able to correctly and simply relate the dynamic errors with the structural and operational parameters. To avoid the complexity of local dynamic deformation measurement and modeling, a comprehensive calibration method is employed. Experimental research reveals specific qualities of dynamic Abbe errors; the results exceed the scope of ISO 10360-2 calibration method, showing the ISO 10360-2 dynamic error evaluation deficiencies. For calibrating the dynamic Abbe errors, the differential measurement method is presented based on the measurements of the internal and external dimensions. Referring probe tip radius correction, the dynamic Abbe errors compensation method is proposed for CMM end-users and is easy to use.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051002-051002-10. doi:10.1115/1.4037836.

Many industrial and laboratory applications which make use of electric machines require noninterruption operation, even in the presence of faults, such as power generation and electric vehicles. Under fault scenarios, the performance of the system is expected to degrade and control techniques may be helpful to overcome this issue. Within this context, phase faults are obviously undesired, as may lead the machine to stop operating. Switched reluctance machines (SRM), due to its inherit characteristics, are naturally tolerant to phase faults, despite the loss of performance. Most of the techniques used to improve the performance of SRMs in fault situations are related to the switching feed converter. Regarding this issue, instead of presenting an alternative converter topology, this work alternatively proposes a control approach which significantly reduces the phase faults effects on the speed of the motor. Furthermore, the high-frequency noise is attenuated when compared to the classical proportional–integral (PI) controller, commonly applied to control such sort of motors. The proposed SRM-adaptive feedforward control (AFC) controller is able to recover the speed of operation faster than a classical approach, when a feedforward action is not taken into account.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051003-051003-13. doi:10.1115/1.4038374.

This paper extends the framework of Lyapunov–Krasovskii functional to address the problem of exponential stabilization for a class of linearly distributed parameter systems (DPSs) with continuous differentiable time-varying delay and a spatiotemporal control input, where the system model is described by parabolic partial differential-difference equations (PDdEs) subject to homogeneous Neumann or Dirichlet boundary conditions. By constructing an appropriate Lyapunov–Krasovskii functional candidate and using some inequality techniques (e.g., spatial integral form of Jensen's inequalities and vector-valued Wirtinger's inequalities), some delay-dependent exponential stabilization conditions are derived, and presented in terms of standard linear matrix inequalities (LMIs). These stabilization conditions are applicable to both slow-varying and fast-varying time delay cases. The detailed and rigorous proof of the closed-loop exponential stability is also provided in this paper. Moreover, the main results of this paper are reduced to the constant time delay case and extended to the stochastic time-varying delay case, and also extended to address the problem of exponential stabilization for linear parabolic PDdE systems with a temporal control input. The numerical simulation results of two examples show the effectiveness and merit of the main results.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051004-051004-7. doi:10.1115/1.4038112.

An approach of optimal control is developed for predicting the behavior of sucker-rod pumping systems. Our method provides the error correction in prediction, and accurately generates polished rod and intermediate-depth work dynagraphs under any bottom-hole pump condition of vertical oil wells. From the prediction perspective, any normal or abnormal pumping condition of vertical oil wells can be simulated by our method. Our method can replace the conventional prediction methods and are definitely able to predict the complex pumping conditions which the conventional prediction methods cannot predict due to their technical constraints. The prediction results from our method will be of great values to improve the design, selection, installation, and operation of sucker-rod pumping systems. From the diagnostic point of view, a complete databank of surface work dynagraphs corresponding to all the downhole pump conditions of vertical oil wells can be generated by our method and can be used as an expert knowledge system for diagnostic of the sucker-rod pumping systems in the operation situations that only the surface work dynagraphs but not the pump dynagraphs are available. Our method is also a good tool to conveniently generate surface work dynagraphs for pump diagnostic emulators.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051005-051005-9. doi:10.1115/1.4038299.

The efficiency of the spark ignition (SI) engine degrades while working at part loads. It can be optimally dealt with a slightly different thermodynamic cycle termed as an Atkinson cycle. It can be implemented in the conventional SI engines by incorporating advanced mechanisms as variable valve timing (VVT) and variable compression ratio (VCR). In this research, a control framework for the Atkinson cycle engine with flexible intake valve load control strategy is designed and developed. The control framework based on the extended mean value engine model (EMVEM) of the Atkinson cycle engine is evaluated in the view of fuel economy at the medium and higher load operating conditions for the standard new European driving cycle (NEDC), federal urban driving schedule (FUDS), and federal highway driving schedule (FHDS) cycles. In this context, the authors have already proposed a control-oriented EMVEM model of the Atkinson cycle engine with variable intake valve actuation. To demonstrate the potential benefits of the VCR Atkinson cycle VVT engine, for the various driving cycles, in the presence of auxiliary loads and uncertain road loads, its EMVEM model is simulated by using a controller having similar specifications as that of the conventional gasoline engine. The simulation results point toward the significant reduction in engine part load losses and improvement in the thermal efficiency. Consequently, considerable enhancement in the fuel economy of the VCR Atkinson cycle VVT engine is achieved over conventional Otto cycle engine during the NEDC, FUDS, and FHDS cycles.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051006-051006-9. doi:10.1115/1.4038094.

This paper addresses the finite time attitude tracking for rigid spacecraft with inertia uncertainties and external disturbances. First, a new nonsingular terminal sliding mode (NTSM) surface is proposed for singularity elimination. Second, a robust controller based on NTSM is designed to solve the attitude tracking problem. It is proved that the new NTSM can converge to zero within finite time, and the attitude tracking errors converge to an arbitrary small bound centered on equilibrium point within finite time and then go to equilibrium point asymptotically. The appealing features of the proposed control are fast convergence, high precision, strong robustness, and easy implementation. Simulations verify the effectiveness of the proposed approach.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051007-051007-10. doi:10.1115/1.4038490.

Motivated by the reduction of overall wind power cost, considerable research effort has been focused on enhancing both efficiency and reliability of wind turbines. Maximizing wind energy capture while mitigating fatigue loads has been one of the main goals for control design. Recent developments in remote wind speed measurement systems (e.g., light detection and ranging (LIDAR)) have paved the way for implementing advanced control algorithms in the wind energy industry. In this paper, an LIDAR-assisted economic model predictive control (MPC) framework with a real-time adaptive approach is presented to achieve the aforementioned goal. First, the formulation of a convex optimal control problem is introduced, with linear dynamics and convex constraints that can be solved globally. Then, an adaptive approach is proposed to reject the effects of model-plant mismatches. The performance of the developed control algorithm is compared to that of a standard wind turbine controller, which is widely used as a benchmark for evaluating new control designs. Simulation results show that the developed controller can reduce the tower fatigue load with minimal impact on energy capture. For model-plant mismatches, the adaptive controller can drive the wind turbine to its optimal operating conditions while satisfying the optimal control objectives.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051008-051008-11. doi:10.1115/1.4038268.

This paper focuses on the development of a model-based feedback controller to realize high versatility of fully actuated planar bipedal robotic walking. To conveniently define both symmetric and asymmetric walking patterns, we propose to use the left and the right legs for gait characterization. In addition to walking pattern tracking error, a biped's position tracking error in Cartesian space is included in the output function in order to enable high-level task planning and control such as multi-agent coordination. A feedback controller based on input–output linearization and proportional–derivative control is then synthesized to realize exponential tracking of the desired walking pattern as well as the desired global position trajectory. Sufficient stability conditions of the hybrid time-varying closed-loop system are developed based on the construction of multiple Lyapunov functions. In motion planning, a new method of walking pattern design is introduced, which decouples the planning of global motion and walking pattern. Finally, simulation results on a fully actuated planar biped show the effectiveness of the proposed walking strategy.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051009-051009-12. doi:10.1115/1.4037839.

This paper deals with the distributed fault detection and isolation problem of uncertain, nonlinear large-scale systems. The proposed method targets applications where the computation requirements of a full-order failure-sensitive filter would be prohibitively demanding. The original process is subdivided into low-order interconnected subsystems with, possibly, overlapping states. A network of diagnostic units is deployed to monitor, in a distributed manner, the low-order subsystems. Each diagnostic unit has access to a local and noisy measurement of its assigned subsystem's state, and to processed statistical information from its neighboring nodes. The diagnostic algorithm outputs a filtered estimate of the system's state and a measure of statistical confidence for every fault mode. The layout of the distributed failure-sensitive filter achieves significant overall complexity reduction and design flexibility in both the computational and communication requirements of the monitoring network. Simulation results demonstrate the efficiency of the proposed approach.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051010-051010-17. doi:10.1115/1.4038095.

Road adhesion coefficient is an important parameter in vehicle active safety control system. Many researchers estimate road adhesion coefficient by total tire self-aligning torque (SAT, also called front-axle aligning torque), which obtains the average road adhesion coefficient of front wheels, thus leading large estimation error. In this paper, a novel estimation of road adhesion coefficient based on single tire SAT, which is obtained by tire aligning torque distribution, is brought forward. Due to the use of SAT, the proposed estimation method is available in steering only condition. The main idea of the proposed method is that road adhesion coefficient is estimated by single tire SAT instead of total tire SAT. The single tire SAT is closer to real tire torque state, and it can be obtained by aligning torque distribution, which makes use of the ratio for the aligning torque of front-left wheel and front-right wheel. Tire sideslip angle used in torque distribution is estimated by unscented Kalman filter (UKF). Two coefficients, including front-left and front-right tire-road friction coefficients, are estimated by iteration algorithm form single tire SAT. The final road adhesion coefficient is determined by a coefficient identification rule, which is designed to determine which tire-road friction coefficient as the final road adhesion coefficient. Both simulations and tests that use gyroscope/lateral accelerometer/global position system (GPS)/strain gauge are conducted, to validate the proposed methodology that can provide accurate road adhesion coefficient to vehicle active safety control.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051011-051011-9. doi:10.1115/1.4038096.

This paper studies the multiple timescale behavior that is induced by dynamic coupling between continuous-time and discrete-time systems, and that arises naturally in distributed networked systems. An order reduction method is proposed that establishes a mathematically rigorous separation principle between the fast evolution of the continuous-time dynamics and the slow updates of the discrete-time dynamics. Quantitative conditions on the discrete update rate are then derived that ensure the stability of the coupled dynamics based on the behavior of the isolated systems. The results are illustrated for a distributed network of satellites whose attitudes evolve continuously while communicating intermittently over the network.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):051012-051012-15. doi:10.1115/1.4038165.

A model following adaptive sliding mode tracking control (MFASMTC) with the adjustable control gain based on a disturbance observer (DOB) for the mechanical system is proposed in this paper. The control gains of the proposed controller are automatically adjusted to compensate the unknown time-varying disturbances by the DOB. First, the unknown variables and uncertainties are lumped as the disturbance terms and the system dynamic model consist of the nominal matrix and disturbances vector. The desired model and sliding mode controller (SMC) are integrated by using the Lyapunov function candidate to obtain the general model following sliding mode tracking control (MFSMTC) with the fixed control gain. To stabilize and compensate the unknown time-varying disturbances for the control system, a DOB is combined with the MFSMTC to obtain the MFASMTC to automatically adjust the control gains. The mass-spring-damper system and two-link manipulator robot system are both used as examples system to demonstrate the proposed control scheme, respectively. The comparisons between MFSMTC with the fixed control gain and MFASMTC with the adjustable control gain based on a DOB are performed in this paper. From the simulation results, the proposed MFASMTC with the adjustable control gain based on a DOB demonstrates the stable and robust control performance for the unknown uncertainties and external disturbances. The proposed control method also can be applied to the other mechanical systems with the desired model to find the desired model following adaptive sliding mode tracking control.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Dyn. Sys., Meas., Control. 2017;140(5):054501-054501-4. doi:10.1115/1.4038373.

In this study, the design of a smooth robust velocity observer for a class of uncertain nonlinear mechatronic systems is presented. The proposed velocity observer does not require a priori knowledge of the upper bounds of the uncertain system dynamics and introduces time-varying observer gains for uncertainty compensation. Practical stability of the velocity observation error is ensured via Lyapunov-type stability analysis. Experimental results obtained from Phantom Omni haptic device are presented to illustrate the performance of the proposed velocity observer.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2017;140(5):054502-054502-8. doi:10.1115/1.4037834.

The problem of designing robust and noise-insensitive proportional–integral (PI) controllers for pressure-sensor-based combustion-timing control was studied through simulation. Different primary reference fuels (PRF) and operating conditions were studied. The simulations were done using a physics-based, control-oriented model with an empirical ignition-delay correlation. It was found that the controllable region in between the zero-gain region for early injection timings and the misfire region for late injection timings is strongly PRF dependent. As a result, it was necessary to adjust intake temperature to compensate for the difference in fuel reactivity prior to the controller design. With adjusted intake temperature, PRF-dependent negative-temperature coefficient (NTC) behavior gave different system characteristics for the different fuels. The PI controller design was accomplished by solving the optimization problem of maximizing disturbance rejection and tracking performance subject to constraints on robustness and measurement-noise sensitivity. Optimal controller gains were found to be limited by the high system gain at late combustion timings and high-load conditions; furthermore, the measurement-noise sensitivity was found to be higher at the low-load operating points where the ignition delay is more sensitive to variations in load and intake conditions. The controller-gain restrictions were found to vary for the different PRFs; the optimal gains for higher PRFs were lower due to a higher system gain, whereas the measurement-noise sensitivity was found to be higher for lower PRFs.

Commentary by Dr. Valentin Fuster

Design Innovation Paper

J. Dyn. Sys., Meas., Control. 2017;140(5):055001-055001-10. doi:10.1115/1.4037840.

A correct estimation of both direction and intensity of wind velocity is fundamental for controlling an autonomous sail-boat. This kind of estimation has to be performed in a harsh environment considering the direct exposition of the sensor to salt, fog, and to any variable weather conditions. An important feature is represented by the sensor size, which has to be small compared to the drone size. Costs have to be optimized with respect to the overall small budget involved in the construction of the drone. Finally, extensive use on drones or in large sensor networks should be greatly advantaged by an easy substitutability in the case of accidental damage or system loss, an eventuality which is difficult to be completely avoided for large scale, prolonged monitoring activities. In this work authors propose a low cost ultrasonic planar anemometer with a very interesting price to performance ratio which is obtained by introducing a simple, original and innovative Arduino based architecture. Preliminary design and the results of calibration will be described, followed by testing activities performed on a low-speed large section wind tunnel, available at University of Florence supported by simple but effective computational fluid dynamic (CFD) simulations.

Commentary by Dr. Valentin Fuster

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