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IN THIS ISSUE

### Research Papers

J. Dyn. Sys., Meas., Control. 2010;132(2):021001-021001-8. doi:10.1115/1.4000651.

Benchmark problems have been used to evaluate the performance of a variety of robust control design methodologies by many control engineers over the past 2 decades. A benchmark is a simple but meaningful problem to highlight the advantages and disadvantages of different control strategies. This paper verifies the performance of a new control strategy, which is called combined feedforward and feedback control with shaped input (CFFS), through a benchmark problem applied to a two-mass-spring system. CFFS, which consists of feedback and feedforward controllers and shaped input, can achieve high performance with a simple controller design. This control strategy has several unique characteristics. First, the shaped input is designed to extract energy from the flexible modes, which means that a simpler feedback control design based on a rigid-body model can be used. In addition, only a single frequency must be attenuated to reduce residual vibration of both masses. Second, only the dynamics between control force and the first mass need to be considered in designing both feedback and feedforward controllers. The proposed control strategy is applied to a benchmark problem and its performance is compared with that obtained using two alternative control strategies.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021002-021002-10. doi:10.1115/1.4000661.

This paper proposes two techniques for reducing the number of uncertain parameters in order to simplify robust controller design and to reduce conservatism inherent in robust controllers. The system is assumed to have a known structure with parametric uncertainties that represent plant dynamics variation. An original set of parameters is estimated by nonlinear least-squares (NLS) optimization using noisy frequency response functions. Utilizing the property of asymptotic normality for NLS estimates, the original parameter set can be reparameterized by an affine function of the smaller number of uncorrelated parameters. The correlation among uncertain parameters is detected by the principal component analysis in one technique and optimization with a bilinear matrix inequality in the other. Numerical examples illustrate the usefulness of the proposed techniques.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021003-021003-12. doi:10.1115/1.4000662.

Clutch shift control is critical for the performance and fuel economy of automotive transmissions, including both automatic and hybrid transmissions. Among all the factors that influence clutch shift control, clutch fill and clutch engagement are crucial to realize a fast and smooth clutch shift. When the clutch is not engaged, the fluid held by the centrifugal force inside of the clutch chamber, which introduces additional pressure that will affect the subsequent clutch fill and engagement processes, should be released. To realize this function, a ball capsule system is introduced and mounted on the clutch chamber. When the clutch chamber is ready to be filled for engagement, the ball capsule needs to close quickly and remain closed until the clutch is disengaged. It is also desirable to have an appropriate closing velocity for the ball capsule to minimize noise and wear. In this paper, the ball capsule dynamics is modeled, in which the derivation of the ball capsule throttling area is considered novel and critical because of its asymmetrical nature. Through this, the ball capsule’s intrinsic positive feedback structure is also revealed, which is considered to be the key to realize a fast response. Moreover, through the system dynamics analysis, the slope angle of the capsule is found to be an effective control parameter for system performance and robustness. To this end, the optimal shape of the capsule is designed using dynamic programming to achieve the desired performance.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021004-021004-7. doi:10.1115/1.4000813.

The aim of this research paper is to systematically present an optimal control of a dc servomotor for the airflow measurement in both the magnitude and the direction. During measuring airflow, the dc servomotor drives a paddle around the rotor axis in a field. The torsional load of the dc servomotor is caused from resistance of the airflow over the moving paddle normal to the flow. The variations on the torsional load in one revolution of rotation can be characterized from the magnitude and direction of the airflow. In other words, the magnitude and direction of airflow cause a periodic function of the torsional load with respect to the angular position of the paddle. By using Fourier analysis, it is found that the magnitude and direction of the airflow can be determined from the coefficients of the Fourier series. Typically, the torsional load of the dc servomotor, unlike the rotor speed, cannot be measured by the built-in device. In this work, it is determined by applying the extended Luenberger observer method. A state-feedback controller with the observer based on $H2$ control design is implemented to regulate the dc servomotor. The experimental results on the measurement of airflow show the viability of the proposed methodology.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021005-021005-10. doi:10.1115/1.4000835.

This paper proposes controller design methods, specially for track-following control of the magnetic read/write head in a hard disk drive (HDD). The servo system to be considered is a general dual-stage multisensing system, which encompasses most of the track-following configurations encountered in the HDD industry, including the traditional single-stage system. For the general system, a robust track-following problem is formulated as a time-varying version of the robust $H2$ synthesis problem. Both dynamic and real parametric uncertainties, which are typical model uncertainties in track-following control, are taken into account in the formulation. Three optimal robust controller design techniques with different robustness guarantees are applied to solve the synthesis problem. These are mixed $H2/H∞$, mixed $H2/μ$, and robust $H2$ syntheses. Advantages and disadvantages of each method are presented. Multirate control, which is inherent to control problems in HDDs, is obtained by reducing multirate problems into linear time-invariant ones, for which there are many useful theories and algorithms available. Most of the techniques proposed in this paper heavily rely on efficient numerical tools for solving linear matrix inequalities.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021006-021006-12. doi:10.1115/1.4000652.

Within the frame of industrial automation, the mechanical power related to pneumatic actuator systems involves air flows along with mechanical component, such as valves, connecting tubes, cylinder chambers and possible linkages in order to finally actuate a specific objective. Gas dynamic of the air flowing into connecting ducts plays a fundamental role in the description of the global dynamic phenomena of these systems. Several studies deal with the dynamics of such pneumatic systems but through streamlined analysis where the influence of pressure-waves propagating in ducts is neglected or poorly described. The related models are even more complex when finite volumes are placed at the ends of connecting lines. In this paper, two different mathematical models describing transient pressure-waves propagating through lines closed by finite volumes are presented. The investigation regards pressure and velocity ranges normally operating in industrial pneumatic systems. Besides the value of new system modeling of different complexity, these models are compared from an analytical and numerical point of view; advantages, disadvantages, weakness, abilities, and inabilities are highlighted and, finally, the relevant analysis is corroborated through experimental validations of wave propagating pressure at fixed positions of ducts. This study results both in the presentation of models of practical interest, as well as in an attempt to provide an elucidation on the need to resort to an accurate model rather than a streamlined one with respect to the geometric and/or operative characteristics of industrial pneumatic systems.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021007-021007-10. doi:10.1115/1.4000816.

This paper presents a detailed model of a novel electropneumatic valve actuator for both engine intake and exhaust valves. The valve actuator’s main function is to provide variable valve timing and variable lift capabilities in an internal combustion engine. The pneumatic actuation is used to open the valve and the hydraulic latch mechanism is used to hold the valve open and to reduce valve seating velocity. This combination of pneumatic and hydraulic mechanisms allows the system to operate under low pressure with an energy saving mode. It extracts the full pneumatic energy to open the valve and use the hydraulic latch that consumes almost no energy to hold the valve open. A system dynamics analysis is provided and followed by mathematical modeling. This dynamic model is based on Newton’s law, mass conservation, and thermodynamic principles. The air compressibility and liquid compressibility in the hydraulic latch are modeled, and the discontinuous nonlinearity of the compressible flow due to choking is carefully considered. Provision is made for the nonlinear motion of the mechanical components due to the physical constraints. Validation experiments were performed on a Ford 4.6 l four-valve V8 engine head with different air supply pressures and different solenoid pulse inputs. The simulation responses agreed with the experimental results at different engine speeds and supply air pressures.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021008-021008-7. doi:10.1115/1.4000654.

In this paper, two fractional-order linear controllers are proposed to stabilize unstable equilibrium points of a chaotic fractional-order system. The first controller is based on the dynamic output feedback control idea and requires detectability of the linearized model of the fractional-order system on the equilibrium point. The second controller is a dynamic state feedback controller and requires observability of the linearized model. In both considered cases, the stabilizability of the model is assumed. The number of inner states in the second controller is one and therefore its structure is much simpler than the first controller. To illustrate the applicability, these controllers are applied to control chaos in the fractional-order Chen system. Numerical simulations results are presented to evaluate the performance of the proposed controllers.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021009-021009-8. doi:10.1115/1.4000663.

The main issue in a surveillance environment is the target tracking. The most important concern in this problem is the association of the various measurements with the existing target tracks. The fuzzy c-means data association (FCMDA) algorithm, based on the fuzzy c-means (FCM) algorithm, is an efficient solution for the problem of measurement to track association in a multisensor multitarget environment. It has a high accuracy in measurement to track association when targets are far from each other. However, its accuracy remains low when targets are close to one another. The FCMDA algorithm performance is usually lost in this environment, especially when measurement noise is high. In the FCMDA algorithm, the association between measurements and tracks is determined using an optimal membership function derived from the FCM algorithm for the fixed predicted state of targets. The prediction of the target state deviates from its correct value based on updating the tracker/filter with the wrong associated measurement. Consequently, the wrong association can take place using a deviated prediction of target state in the FCMDA algorithm. In this paper, to overcome this shortcoming of the FCMDA algorithm, the predicted state of every target in a surveillance environment is compensated for the effect of wrong associated measurement by an adaptive neurofuzzy inference system (ANFIS). An ANFIS has both the advantages of expert knowledge of a fuzzy inference system and the learning capability of neural networks. So a trained ANFIS is able to compensate the effect of a wrong associated measurement on the prediction of target state. Using the compensated prediction of target state in the FCMDA algorithm can always save the performance of the FCMDA algorithm and extend its domain of usage in practical applications. The simulation results demonstrate that considerable improvements in terms of accuracy and performance are achieved by using the compensated prediction of target state in the FCMDA algorithm.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021010-021010-12. doi:10.1115/1.4000036.

Incorporating homogeneous charge compression ignition (HCCI) into combustion engines for better fuel economy and lower emission requires understanding the dynamics influencing the combustion timing in HCCI engines. A control oriented model to dynamically predict cycle-to-cycle combustion timing of a HCCI engine is developed. The model is designed to work with parameters that are easy to measure and to have low computation time with sufficient accuracy for control applications. The model is a full-cycle model and consists of a residual gas model, a modified knock integral model, fuel burn rate model, and thermodynamic models. In addition, semi-empirical correlations are used to predict the gas exchange process, generated work and completeness of combustion. The developed model incorporates the thermal coupling dynamics caused by the residual gases from one cycle to the next cycle. The model is parameterized by over 5700 simulations from a detailed thermokinetic model and experimental data obtained from a single-cylinder engine. Cross-validation of the model with both steady-state and transient HCCI experiments for four different primary reference fuel blends is detailed. With seven model inputs, the combustion timing of over 150 different HCCI points is predicted to within an average error of less than 1.5 deg of crank angle. A narrow window of combustion timing is found to provide stable and efficient HCCI operation.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021011-021011-6. doi:10.1115/1.4000811.

This paper presents the design and implementation of a positioning system with a dc servomotor and ball-screw mechanism used to realize high-precision positioning over a wide travel range with nanometer level positioning error and near zero overshoot. Instead of the popular dual-model control strategy and friction compensation, a high-gain proportional-integral-derivative controller is used to realize a single-step point-to-point positioning. The controller parameters are obtained by placing closed-loop poles according to the macrodynamics of a ball-screw mechanism only to avoid identification of microdynamics and friction modeling. In order to suppress the overshoot caused by actuator saturation in long-stroke positioning, a trajectory planning method is applied to calculate the input of the closed-loop system. Experimental and simulation results demonstrate that single-step precision positioning responses to different size commands are achieved without producing any large overshoot. In point-to-point positioning from 100 mm down to 10 nm, the positioning error is within 2 nm and the response dynamics is satisfactory.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021012-021012-15. doi:10.1115/1.4000812.

The paper is devoted to the robust stability problem of linear time invariant feedback control systems with actuator saturation, especially in those cases with potentially large parametric uncertainty. The main motivation of the work has been twofold: First, most of the existing robust antiwindup techniques use a conservative plant uncertainty description, and second, previous quantitative feedback theory (QFT) results for control systems with actuator saturation are not suitable to achieve robust stability specifications when the control system is saturated. Traditionally, in the literature, this type of problems has been solved in terms of linear matrix inequalities (LMIs), using less structured uncertainty descriptions as given by the QFT templates. The problem is formulated for single input single output systems in an input-output (I/O) stability sense, and is approached by using a generic three degrees of freedom control structure. In this work, a QFT-based design method is proposed in order to solve the robust stability problem of antiwindup design methods. The main limitation is that the plant has poles in the closed left half plane, and at most, has one integrator. The work investigates robust adaptations of the Zames–Falb stability multipliers result, and it may be generalized to any compensation scheme that admits a decomposition as a feedback interconnection of linear and nonlinear blocks (Lur’e type system), being antiwindup systems as a particular case. In addition, an example will be shown, making explicit the advantages of the proposed method in relation to previous approaches.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):021013-021013-9. doi:10.1115/1.4000817.

The problem of fuzzy data association for target tracking in a cluttered environment is discussed in this paper. In data association filters based on fuzzy clustering, the association probabilities of tracking filters are reconstructed by utilizing the fuzzy membership degree of the measurement belonging to the target. Clearly in these filters, the fuzzy clustering method has an important role; better approach causes better precision in target tracking. Recently, by using the information theory, the maximum entropy fuzzy data association filter (MEF-DAF), as a fast and efficient algorithm, is introduced in literature. In this paper, by modification of a fuzzy clustering objective function, which is prepared for using in target tracking, a modified maximum entropy fuzzy data association filter (MMEF-DAF) is proposed. The MMEF-DAF has a better performance in case of single and multiple target tracking than MEF-DAF, and the other known algorithms such as probabilistic data association filter and the hybrid fuzzy data association filter. Using Monte Carlo simulations, the superiority of the proposed algorithm in comparison with the previous ones is demonstrated. Simply, less computational cost and suitability for real-time applications are the main advantages of the proposed algorithm.

Commentary by Dr. Valentin Fuster

### Technical Briefs

J. Dyn. Sys., Meas., Control. 2010;132(2):024501-024501-7. doi:10.1115/1.4000814.

The first step in designing a control system for a rigid body is to understand its dynamics. Underwater vehicle dynamics may be complex and difficult to model, mainly due to difficulties in observing and measuring actual underwater vehicle hydrodynamics response. This paper is concerned with structure selection of nonlinear polynomials in a Volterra polynomial basis function neural network and recursive parameter estimation of the selected model, in order to obtain a model of a variable mass underwater vehicle with six degrees of freedom using an input-output data set. The simulation results reveal the efficiency of the approach.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):024502-024502-6. doi:10.1115/1.4000815.

This paper presents a methodology for design of mobile vehicles, mounted with underactuated manipulators operating in a horizontal plane, such that the combined system is differentially flat. A challenging question of how to perform point-to-point motions in the state space of such a highly nonlinear system, in spite of the absence of some actuators in the arm, is answered in this paper. We show that, by appropriate inertia distribution of the links and addition of torsion springs at the joints, a range of underactuated designs is possible, where the underactuated mobile manipulator system is differentially flat. The differential flatness property allows one to efficiently solve the problem of trajectory planning and feedback controller design for point-to-point motions in the state space. The proposed method is illustrated by the example of a mobile vehicle with an underactuated three-link manipulator.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):024503-024503-4. doi:10.1115/1.4000659.

This paper provides two computationally effective fusion estimation algorithms. The first algorithm is based on Cholesky factorization of a cross-covariance block matrix. This algorithm has low computational complexity and is equivalent to the standard composite fusion estimation algorithm as well. The second algorithm is based on a special approximation scheme for local cross-covariances. Such approximation is useful to compute matrix weights for fusion estimation in a multidimensional-multisensor environment. Subsequent computational analysis of the proposed fusion algorithms is presented with corresponding examples showing the low computational complexities of the new fusion estimation algorithms.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):024504-024504-6. doi:10.1115/1.4000819.

Advanced internal combustion engine technologies have afforded an increase in the number of controllable variables and the ability to optimize engine operation. Values for these variables are determined during engine calibration by means of a tabular static correlation between the controllable variables and the corresponding steady-state engine operating points to achieve desirable engine performance, for example, in fuel economy, pollutant emissions, and engine acceleration. In engine use, table values are interpolated to match actual operating points. State-of-the-art calibration methods cannot guarantee continuously the optimal engine operation for the entire operating domain, especially in transient cases encountered in the driving styles of different drivers. This article presents brief theory and algorithmic implementation that make the engine an autonomous intelligent system capable of learning the required values of controllable variables in real time while operating a vehicle. The engine controller progressively perceives the driver’s driving style and eventually learns to operate in a manner that optimizes specified performance criteria. A gasoline engine model, which learns to optimize fuel economy with respect to spark ignition timing, demonstrates the approach.

Commentary by Dr. Valentin Fuster
J. Dyn. Sys., Meas., Control. 2010;132(2):024505-024505-5. doi:10.1115/1.4000820.

Two problems encountered in precision manufacturing are friction and flexibility. With regard to friction, pulse-width control has been shown to be exceptionally effective for rigid systems; however, when used to control flexible systems residual vibrations often result, limiting speed and precision. In previous work, a pulse-width controller was developed that uses two pulses in sequence such that the second pulse minimizes vibration induced by the first. This controller used a brute-force numerical process and obtained solutions similar to optimal zero vibration techniques. Additionally, trends in numerical solutions were identified that approached limiting values for short pulse durations. In the present paper, a theoretical foundation for these limiting values is derived. This derivation shows that for short maneuvers approximate analytical expressions for pulse-widths and their application times are easily obtained. These analytical expressions are used as the basis of a pulse-width controller that is shown to effectively minimize residual vibration in simulations and experiments.

Commentary by Dr. Valentin Fuster