Research Papers

J. Dyn. Sys., Meas., Control. 2018;141(1):011001-011001-7. doi:10.1115/1.4041008.

In this study, a continuous robust-adaptive operational space controller that ensures asymptotic end-effector tracking, despite the uncertainties in robot dynamics and on the velocity level kinematics of the robot, is proposed. Specifically, a smooth robust controller is applied to compensate the parametric uncertainties related to the robot dynamics while an adaptive update algorithm is used to deal with the kinematic uncertainties. Rather than formulating the tracking problem in the joint space, as most of the previous works on the field have done, the controller formulation is presented in the operational space of the robot where the actual task is performed. Additionally, the robust part of the proposed controller is continuous ensuring the asymptotic tracking and relatively smooth controller effort. The stability of the overall system and boundedness of the closed loop signals are ensured via Lyapunov based arguments. Experimental results are presented to illustrate the feasibility and performance of the proposed method.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011002-011002-10. doi:10.1115/1.4040970.

Three algorithms that improve the performance of the asymptotically optimal Rapidly exploring Random Tree (RRT*) are presented in this paper. First, we introduce the Goal Tree (GT) algorithm for motion planning in dynamic environments where unexpected obstacles appear sporadically. The GT reuses the previous RRT* by pruning the affected area and then extending the tree by drawing samples from a shadow set. The shadow is the subset of the free configuration space containing all configurations that have geodesics ending at the goal and are in conflict with the new obstacle. Smaller, well defined, sampling regions are considered for Euclidean metric spaces and Dubins' vehicles. Next, the Focused-Refinement (FR) algorithm, which samples with some probability around the first path found by an RRT*, is defined. The third improvement is the Grandparent-Connection (GP) algorithm, which attempts to connect an added vertex directly to its grandparent vertex instead of parent. The GT and GP algorithms are both proven to be asymptotically optimal. Finally, the three algorithms are simulated and compared for a Euclidean metric robot, a Dubins' vehicle, and a seven degrees-of-freedom manipulator.

Topics: Algorithms , Vehicles
Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011003-011003-12. doi:10.1115/1.4040920.

In this work, we suggest a novel solution to a very specific problem—calculating the pose (position and attitude) of a micro-aerial vehicle (MAV) operating inside corridors and in front of windows. The proposed method makes use of a single image captured by a front facing camera, of specific features whose three-dimensional (3D) model is partially known. No prior knowledge regarding the size of the corridor or the window is needed, nor is the ratio between their width and height. The position is calculated up to an unknown scale using a gain scheduled iterative algorithm. In order to compensate for the unknown scale, an adaptive controller that ensures consistent closed loop behavior is suggested. The attitude calculation can be used as is, or the results can be fused with angular velocity sensors to achieve better estimation. In this paper, the algorithm is presented and the approach is demonstrated with simulations and experiments.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011004-011004-10. doi:10.1115/1.4041062.

This paper presents the design and dynamic model for a novel prototype pneumatic boost converter, a device developed to be an energetic equivalent to the electrical boost converter. The design of the system selects pneumatic components that are energetically equivalent to the components used in the analogous system in the electrical domain. A dynamic model for the pneumatic boost converter that describes the rapidly fluctuating pressures and volumes is developed. Movement within the system and mass flow through orifices connecting control volumes are also modeled. A prototype was developed to reclaim air at 653 kPa (80 psig) and experimental pressure data were collected at the inlet and outlet of the system. These experimental data are used to validate the dynamic model by comparing experimental and simulated pressures. The experimental data are also used to calculate the total energy reclaimed by the pneumatic boost converter as well as the system efficiency.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011005-011005-12. doi:10.1115/1.4041011.

Selective catalytic reduction (SCR) system has been proven to be an effective technology for the removal of NOx emitted from marine diesel engines. In order to comply with stringent International Maritime Organization (IMO) Tier III NOx emission regulations, a number of engine manufacturers have developed their own SCR systems. This paper focuses on modeling of an SCR reactor and developing model-based urea dosing control strategy. A mathematical model of SCR reactors has been established. Model-based control strategy relies on the three-state and one-state reactor models established to accomplish urea dosing algorithm and is promising in limiting excessive NH3 slip. The SCR reactor model is further used in a simulation for the purpose of developing model-based urea dosing control strategies. The simulation results show that the NO sliding mode control requires a massive prestudy of the NOx reduction capability of the catalyst in order to set an appropriate control objective for each operating condition. However, this calibration work can be omitted in the optimal control and NH3 sliding mode control, which mitigates the workload of the controller design. The optimal control strategy presents a satisfied control performance in limiting NH3 slip during transient state engine operating conditions.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011006-011006-18. doi:10.1115/1.4041012.

Axial piston pumps with port valves are widely used in applications that require high pressure and high power. In the present research, a new type of double-swash-plate hydraulic axial piston pump (DSPHAPP) with port valves is presented. The structure and working principle of the pump are discussed, and the balance characteristics of the pump are analyzed. A mathematical model of the pump flow distribution mechanism considering the leakage is established, based on which the effects of centrifugal forces acting on the port valves, working pressure, and rotational speed on the flow distribution characteristics are studied. A new method of varying the displacement of the pump that changes the phase relation of the two swash plates is proposed, and the principle and regulating characteristics of the variable method are studied. A detailed analysis of the forces and moments acting on the cylinder and the bearing reaction forces is presented. Finally, the relationship between volumetric efficiency and working pressure, and rotational speed and variable angle, is presented. It is revealed through an analysis that the working principle of the pump is feasible, and that the variable method can meet the requirements of varying the displacement of the pump. The characteristics of static balance and dynamic balance of the double-swashplate pump have the advantage of reducing vibration and noise. The research results also show that the reasonable matching of the working pressure and rotational speed can increase the pump's working performance to its optimum level.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011007-011007-11. doi:10.1115/1.4040969.

Control of on–off valves for linear flow characteristics is a challenging design problem due to nonlinearity of valve mechanism and fluidic properties under various operating conditions. In this study, averaging pulse width modulation (PWM) is proposed as a control valve signal by implementing PWM with predetermined duty period so that overflow at the open position and underflow at the closed position are divided proportionately around desired mean flow rates during entire cycle periods. Multichannels in a parallel pattern are implemented to yield linear flow characteristics with higher resolution than a single channel. With pressure and temperature measurements, the volumetric flow rate is determined by an empirical model of flow characteristics across flow control valves at given operating conditions. The experimental results on achieving the desired volumetric flow rate of air under actual flow conditions without a flow meter are presented for viability of the proposed methodology in practical uses.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011008-011008-8. doi:10.1115/1.4041202.

This paper studies the consensus problem of networked multi-agent systems (NMASs). Distributed delays are considered in the agent dynamics, and we propose a new type of impulsive consensus protocols that also takes into account of distributed delays. A novel method is developed to estimate the relation between the agent states at the impulsive instants and the distributed-delayed agent states, which helps to use the Razumikhin-type stability result to investigate the consensus of NMASs with distributed-delayed impulses. Sufficient conditions are established to guarantee that the network consensus can be reached via the proposed consensus protocols with fixed and switching topologies, respectively. Numerical simulations are also provided to demonstrate our theoretical results.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011009-011009-10. doi:10.1115/1.4040436.

In this paper, an output feedback sliding mode position controller/estimator scheme is proposed to control an single input single output (SISO) system subject to bounded nonlinearities and parametric uncertainties. Various works have been published addressing the theoretical effectiveness of the third-order sliding mode control (3-SMC) in terms of chattering alleviation and controller robustness. However, the application of 3-SMC with a feedback estimator to a flight actuators has not been treated explicitly. This is due to the fact that the accurate full state estimation is required since SMCs performance can be severely degraded by measurement or estimation noise. Aerodynamic control surface actuators in air vehicles mostly employ linear position controllers to achieve guidance and stability. The main focus of the paper is to experimentally demonstrate the stability and positioning performance of a third-order SMC applied to a class of system with high relative degree and bounded parametric uncertainties. The performance of the closed-loop system is also compared with a lower level SMC and classical controller to show the effectiveness of the algorithm. Realization of the proposed algorithm from an application perspective is the main target of this paper and it demonstrates that a shorter settling time and higher control action attenuation can be achieved with the proposed strategy.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011010-011010-8. doi:10.1115/1.4041201.

To enhance the performance of vehicle rollover detection and prevention, this paper proposes a novel control strategy integrating the mass-center-position (MCP) metric and the active rollover preventer (ARPer) system. The applied MCP metric can provide completed rollover information without saturation in the case of tire lift-off. Based on the continuous roll motion detection provided by the MCP metric, the proposed ARPer system can generate corrective control efforts independent to tire–road interactions. Moreover, the capability of the ARPer system is investigated for the given vehicle physical spatial constraints. A hierarchical control architecture is also designed for tracking desired accelerations derived from the MCP metric and allocating control efforts to the ARPer system and the active front steering (AFS) control. Cosimulations between CarSim® and MATLAB/SIMULINK with a fishhook maneuver are conducted to verify the control performance. The results show that the vehicle with the assistance of the ARPer system can successfully achieve better performance of vehicle rollover prevention, compared with an uncontrolled vehicle and an AFS-controlled vehicle.

Topics: Vehicles , Tires
Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011011-011011-10. doi:10.1115/1.4041297.

This paper presents an extremum seeking controller for photovoltaic maximum power point tracking (MPPT). The controller belongs to the broad family of “perturb and observe” algorithms, where the terminal voltage of a photovoltaic system is adjusted to maximize its output power. One critical challenge with these algorithms is that it can be difficult to distinguish between changes in photovoltaic power resulting from changes in irradiation versus the control input. With regard to this challenge, we develop an extremum seeking algorithm that uses least-squares estimation to explicitly separate the effect of the control input from the effect of time-varying disturbances. While the use of least-squares estimation in the context of extremum seeking is not new, our separation of time-varying effects is. In addition, our formulation retains much of the structure of traditional extremum seeking, thereby allowing us to perform a stability analysis comparable to the existing literature. This stability analysis assumes the time-varying disturbance to be slow, but we test the controller beyond this limit in simulation for photovoltaic MPPT. We compare our controller to two benchmarks (a similar controller that does not separate time-varying effects and a traditional extremum seeking controller), and our controller outperforms both.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011012-011012-10. doi:10.1115/1.4041298.

It is shown that brushless direct current (DC) motors (BLDCMs), which have found many useful applications in motion control areas, display chaotic behaviors. To avoid undesirable inherent oscillations of such DC motors, a control strategy should be adopted in the applications. So, the control problem of applied chaotic power systems is taken into account in this paper. Some important aspects of the design and implementation are considered to reach a suitable controller for the applications. In this regard, it is assumed that the system is fluctuated by unknown uncertainties and environmental noises. Additionally, a part of the system dynamics is supposed to be unknown in advance and the effects of nonlinear input saturation are fully taken into account. Then, a one input nonsmooth adaptive sliding mode controller is realized to handle the aforementioned issues. The proposed controller does not require any knowledge about the bounds of the system uncertainties and external fluctuations as well as about the parameters of the input saturation. The finite time convergence and robustness of the driven control scheme are mathematically proved and numerically illustrated using matlab simulations for DC motors.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011013-011013-10. doi:10.1115/1.4041357.

This paper deals with the design of fixed-structure controllers for two-input two-output (TITO) systems using frequency-domain data. In standard control approaches, a plant model is first derived, then a suitable controller is designed to meet some user-specified performance specifications. Basically, there are two common ways for obtaining mathematical models: white-box modeling and black-box modeling. In both approaches, it is difficult to obtain a simple and accurate model that completely describes the system dynamics. As a result, errors associated with the plant modeling may result in degradation of the desired closed-loop performance. Moreover, the intermediate step of plant modeling introduced for the controller design is a time-consuming task. Hence, the concept of data-based control design is introduced as a possible alternative to model-based approaches. This promising methodology allows us to avoid the under-modeling problem and to significantly reduce the time and workload for the user. Most existing data-based control approaches are developed for single-input single-output (SISO) systems. Nevertheless, a large class of real systems involve several manipulated and output variables. To this end, we attempt here to develop an approach to design controllers for TITO systems using frequency-domain data. In such a method, a set of frequency-domain data is utilized to find an adequate decoupler and to tune a diagonal controller that meets some desired closed-loop performance measures. Two simulation examples are presented to illustrate and demonstrate the efficacy of the proposed method.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011014-011014-11. doi:10.1115/1.4041353.

This paper is aimed to propose a multiloop control scheme for fractional order multi-input multi-output (FO-MIMO) systems. It is an extension of the FO-multiloop controller design method developed for integer order multivariable systems to FO-MIMO ones. The interactions among the control loops are considered as disturbances and a two degrees-of-freedom (2DOF) paradigm is used to deal with the process outputs performance and the interactions reduction effect, separately. The proposed controller design method is simple, in relation with the desired closed-loop specifications and a tuning parameter. It presents an interest in controlling complex MIMO systems since fractional order models (FO-models) represent some real processes better than integer order ones and high order systems can be approximated by FO-models. Two examples are considered and compared with other existing methods to evaluate the proposed controller.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011015-011015-11. doi:10.1115/1.4041359.

Thermal protection strategies are employed to protect in-wheel-motors (IWM). Vehicle motions and stability can be affected by such motor thermal protections because they typically reduce the motor output torque to lower motor temperature and protect motor from thermal damage. This paper proposes a fault-tolerant control (FTC) method and a fault-prevention control (FPC) method for vehicle motion control considering motor thermal protection. The FTC method aims to stabilize vehicle motion when motor thermal protection is triggered. A control allocation (CA) algorithm using motor temperature measurement is developed for the FTC method. The output torque constraints can be actively adjusted with motor temperature to include thermal protection strategy in the controller design. When future vehicle trajectories are available, a model predictive control (MPC) FPC algorithm is created to regulate the control efforts in advance to avoid overheating the IWMs that triggers the thermal protection strategy. The proposed methods are validated in CarSim® simulations and the results show that both the FTC and FPC methods can reduce the vehicle yaw rate tracking errors when IWMs are subject to thermal protection strategy.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2018;141(1):011016-011016-9. doi:10.1115/1.4041354.

Lean NOx trap (LNT) is one of the most effective after-treatment technologies used to reduce NOx emissions of diesel engines. One relevant problem in this context is LNT regeneration timing control. This problem is indeed difficult due to the fact that LNTs are highly nonlinear systems, involving complex physical/chemical processes, that are hard to model. In this paper, a novel approach for regeneration timing of LNTs is proposed, allowing us to overcome these issues. This approach, named data-driven model predictive control (D2-MPC), does not require a physical model of the engine/trap system but is based on low-complexity polynomial prediction models, directly identified from data. The regeneration timing is computed through an optimization algorithm, which uses the identified models to predict the LNT behavior. Two D2-MPC strategies are proposed, and tested in a co-simulation study, where the plant is represented by a detailed LNT model, built using the well-known commercial tool AMEsim, and the controller is implemented in matlab/simulink.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Dyn. Sys., Meas., Control. 2018;141(1):014501-014501-7. doi:10.1115/1.4040210.

A critical issue in design and operation of combustors in gas turbine engines is mitigation of thermoacoustic instabilities, because such instabilities may cause severe damage to the mechanical structure of the combustor. Hence, it is important to quantitatively assimilate the knowledge of the system conditions that would potentially lead to these instabilities. This technical brief proposes a dynamic data-driven technique for design of combustion systems by taking stability of pressure oscillations into consideration. Given appropriate experimental data at selected operating conditions, the proposed design methodology determines a mapping from a set of operating conditions to a set of quantified stability conditions for pressure oscillations. This mapping is then used as an extrapolation tool for predicting the system stability for other conditions for which experiments have not been conducted. Salient properties of the proposed design methodology are: (1) It is dynamic in the sense that no fixed model structure needs to be assumed, and a suboptimal model (under specified user-selected constraints) is identified for each operating condition. An information-theoretic measure is then used for performance comparison among different models of varying structures and/or parameters and (2) It quantifies a (statistical) confidence level in the estimate of system stability for an unobserved operating condition by using a Bayesian nonparametric technique. The proposed design methodology has been validated with experimental data of pressure time-series, acquired from a laboratory-scale lean-premixed swirl-stabilized combustor.

Commentary by Dr. Valentin Fuster

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