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Research Papers

J. Dyn. Sys., Meas., Control. 2016;138(5):051001-051001-8. doi:10.1115/1.4032687.

Neural networks are powerful tools for black box system identification. However, their main drawback is the large number of parameters usually required to deal with complex systems. Classically, the model's parameters minimize a L2-norm-based criterion. However, when using strongly corrupted data, namely, outliers, the L2-norm-based estimation algorithms become ineffective. In order to deal with outliers and the model's complexity, the main contribution of this paper is to propose a robust system identification methodology providing neuromodels with a convenient balance between simplicity and accuracy. The estimation robustness is ensured by means of the Huberian function. Simplicity and accuracy are achieved by a dedicated neural network design based on a recurrent three-layer architecture and an efficient model order reduction procedure proposed in a previous work (Romero-Ugalde et al., 2013, “Neural Network Design and Model Reduction Approach for Black Box Nonlinear System Identification With Reduced Number of Parameters,” Neurocomputing, 101, pp. 170–180). Validation is done using real data, measured on a piezoelectric actuator, containing strong natural outliers in the output data due to its microdisplacements. Comparisons with others black box system identification methods, including a previous work (Corbier and Carmona, 2015, “Extension of the Tuning Constant in the Huber's Function for Robust Modeling of Piezoelectric Systems,” Int. J. Adapt. Control Signal Process., 29(8), pp. 1008–1023) where a pseudolinear model was used to identify the same piezoelectric system, show the relevance of the proposed robust estimation method leading balanced simplicity-accuracy neuromodels.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2016;138(5):051002-051002-23. doi:10.1115/1.4032742.

Recent demands on improved system efficiency and reduced system emissions have driven improvements in hydraulic system architectures as well as system supervisory control strategies employed in mobile multi-actuator machinery. Valve-controlled (VC) architectures have been in use for several decades and have seen moderate improvements in terms of system efficiency. Further, throttle-less concepts such as displacement-controlled (DC) actuation have been recently proposed and successfully demonstrated efficiency improvements in numerous prototypes (wheel-loaders, excavators, and skid-steer loaders) of different sizes. The combination of electric or hydraulic hybrid systems for energy recovery (for a single actuator) with VC actuation for the rest of the actuators has also been recently deployed by original equipment manufacturers (OEMs) on some excavator models. The combination of DC actuation together with a series hydraulic hybrid actuator for the swing drive has been previously proposed and implemented as part of this work, on a mini-excavator. This combination of highly efficient DC actuation with hydraulic hybrid configuration allows drastic engine downsizing and efficiency improvements of more than 50% compared to modern-day VC-actuated systems. With a conservative, suboptimal supervisory control, it was previously demonstrated that over 50% energy savings with a 50% downsized engine over the standard load-sensing (LS) architecture for a 5-t excavator application. The problem of achieving maximum system efficiency through near-optimal supervisory control (or system power management) is a theoretically challenging problem, and has been tackled for the first time in this work for DC hydraulic hybrid machines, through a two-part publication. In Part I, the theoretical aspects of this problem are outlined, supported by simulations of the theoretically optimal supervisory control as well as an implementable, near-optimal rule-based supervisory control strategy that included a detailed system model of the DC hybrid hydraulic excavator. In Part II, the world's first prototype DC hydraulic hybrid excavator is detailed, together with machine implementation of the novel supervisory control strategy proposed in Part I. The main contributions of Part I are summarized below. Dynamic programming (DP) was employed to solve the optimal supervisory problem, and benchmark implementable strategies. Importantly, the patterns in optimal state trajectories and control histories obtained from DP were analyzed and identified for different working cycles, and a common pattern was found for engine speed and DC unit displacements across different working cycles. A rule-based strategy was employed to achieve near-optimal system efficiency, with the design of the strategy guided by optimal patterns. It was found that the strategy replicates optimal system behavior with the same rule for controlling engine speed for different cycles, but different rules for the primary unit (of the series-hybrid swing drive) for different cycles. Thus, in terms of practical implementation of a rule-based approach, the operator is to be provided with a family of controllers from which one can be chosen so as to have near-optimal system behavior under all kinds of cyclical operation.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2016;138(5):051003-051003-12. doi:10.1115/1.4032743.

The problem of achieving maximum system efficiency through near-optimal supervisory control (or system power management) in mobile off-highway machines is a theoretically challenging problem. It has been tackled for the first time in this work for displacement-controlled (DC) hydraulic hybrid multi-actuator machines such as excavators, through a two-part publication. In Part I, the theoretical aspects of this problem were outlined, supported by simulations of the theoretically optimal supervisory control (relying on dynamic programming) as well as a novel, implementable rule-based supervisory control strategy (designed to replicate theoretically optimal results). In Part II of the publication, the world's first prototype hydraulic hybrid excavator using throttle-less DC actuation is described, together with machine implementation of the novel supervisory control strategy proposed in Part I. The design choice, or set of component sizes implemented on the prototype, was driven by an optimal sizing study that was previously done. Measurement results from implementation of two different supervisory control strategies are also presented and discussed—the first, a conservative, suboptimal strategy that commanded a constant engine speed and proved that drastic engine downsizing can be performed in excavator and similar applications. The second strategy implemented was the novel, near-optimal rule-based strategy (or the “minimum-speed” strategy) proposed in Part I that exploited all available system degrees-of-freedom, by commanding the minimum-required engine speeds (to meet DC actuator flow requirements) at every instant in time. While the actual engine was not downsized on the prototype excavator, both the single-point and minimum-speed strategies showed that for the aggressive, digging cycles that such machines are typically used for, the DC hydraulic hybrid architecture enables engine operation at or near 50% of maximum engine power without loss of productivity. As described in Part I, actually downsizing the engine by 50% with use of the near-optimal, minimum-speed strategy will enable significant gains in efficiency (in terms of grams of fuel consumed) over standard valve-controlled architectures (55%) as well as DC nonhybrid architectures (25%) in cyclical operation.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2016;138(5):051004-051004-15. doi:10.1115/1.4032745.

A new set of linearized differential equations governing relative motion of inner-formation satellite system (IFSS) is derived with the effects of J2 as well as atmospheric drag. The IFSS consists of the “inner satellite” and the “outer satellite,” this special configuration formation endows its some advantages to map the gravity field of earth. For long-term IFSS in elliptical orbit, the high-fidelity set of linearized equations is more convenient than the nonlinear equations for designing formation control system or navigation algorithms. In addition, to avoid the collision between the inner satellite and the outer satellite, the minimum sliding mode error feedback control (MSMEFC) is adopted to perform a real-time control on the outer satellite in the presence of uncertain perturbations from the system and space. The robustness and steady-state error of MSMEFC are also discussed to show its theoretical advantages than traditional sliding mode control (SMC). Finally, numerical simulations are performed to check the fidelity of the proposed equations. Moreover, the efficacy of the MSMEFC is performed to control the IFSS with high precision.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2016;138(5):051005-051005-20. doi:10.1115/1.4032461.

Time delay is a common phenomenon in robotic systems due to computational requirements and communication properties between or within high-level and low-level controllers as well as the physical constraints of the actuator and sensor. It is widely believed that delays are harmful for robotic systems in terms of stability and performance; however, we propose a different view that the time delay of the system may in some cases benefit system stability and performance. Therefore, in this paper, we discuss the influences of the displacement-feedback delay (single delay) and both displacement and velocity feedback delays (double delays) on robotic actuator systems by using the cluster treatment of characteristic roots (CTCR) methodology. Hence, we can ascertain the exact stability interval for single-delay systems and the rigorous stability region for double-delay systems. The influences of controller gains and the filtering frequency on the stability of the system are discussed. Based on the stability information coupled with the dominant root distribution, we propose one nonconventional rule which suggests increasing time delay to certain time windows to obtain the optimal system performance. The computation results are also verified on an actuator testbed.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2016;138(5):051006-051006-7. doi:10.1115/1.4032505.

There is a constant interest in the performance capabilities of active suspensions without the associated shortcomings of degraded fuel economy. To this effect, electrodynamic dampers are currently being researched as a means to approach the performance of a fully active suspension with minimal or no energy consumption. This paper investigates the regenerative capabilities of these dampers during fully active operation for a range of controller types—emphasizing road holding, ride, and energy regeneration. A model of an electrodynamic suspension is developed using bond graphs. Two model predictive controllers (MPCs) are constructed: standard and frequency-weighted MPCs. The resulting controlled system is subjected to International Organization for Standardization (ISO) roads A–D and the results are presented. For all of the standard MPC weightings, the suspension was able to recover more energy than is required to run the suspension actively. All of the results for optimal energy regeneration occurred on the standard Pareto tradeoff curve for ride comfort and road holding. Frequency weighting the controller increased suspension performance while also regenerating 3–12% more energy than the standard MPC.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2016;138(5):051007-051007-9. doi:10.1115/1.4032747.

This paper considers observer design problem of singularly perturbed systems (SPSs) with multirate sampled and delayed measurements. The outputs are classified into two sets which are measured at different sampling rates and subject to transmission delays. The error system is modeled as a continuous-time SPS with a slow-varying delay and a fast-varying delay. A new Lyapunov functional taking the delay properties into account is constructed. Based on the Lyapunov–Krasovskii functional, sufficient conditions for stability of the error system are proposed by which an observer design method is proposed. A realistic example is used to illustrate the obtained results.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Dyn. Sys., Meas., Control. 2016;138(5):054501-054501-7. doi:10.1115/1.4032744.

In this paper, a novel algorithm for indirect tire failure indication is described. The estimation method is based on measuring changes in the lateral dynamics behavior resulting from certain types of tire failure modes including excessive deflation or significant thread loss in a combination of tires. Given the fact that both failures will notably affect the lateral dynamics behavior, quantifying these changes constitutes the basis of the estimation method. In achieving this, multiple models and switching method are utilized based on lateral dynamics models of the vehicle that are parametrized to account for the uncertainty in tire pressure levels. The results are demonstrated using representative numerical simulations.

Topics: Pressure , Vehicles , Tires
Commentary by Dr. Valentin Fuster

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