LPV identification of a turbocharged diesel engine

Salcedo, J. V.; Martínez, M.

doi:10.1016/j.apnum.2007.09.005

Cited by 23 publications

(24 citation statements)

References 18 publications

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“…proposed [8][9][10][11][12][13], but the issues with un-modeled dynamics remain to be resolved. Disturbance observer based control [14,15] and rate-based control [16] were adopted as the counter measures.…”

Section: Introductionmentioning

confidence: 99%

Dynamic feed-forward control aided with active disturbance rejection for boost pressure and mass air flow control of diesel engines

Song

Xie

Yang

et al. 2014

Proceedings of the 33rd Chinese Control Conference

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In this paper, a novel control solution is proposed and validated, for the decoupling control of variable geometry turbine (VGT) and exhaust gas recirculation (EGR) system in diesel engines. The cross-coupling and dynamics variation are lumped together as total disturbance, estimated and cancelled in real time by active disturbance rejection control (ADRC). The static and dynamic feed-forward controllers were added to further enhance the disturbance rejection. This proposed solution is compared with the existing PID solution in simulation based on a well-established model, demonstrating its superiority in response speed, robustness, and simplicity in parameters tuning.

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Section: Introductionmentioning

confidence: 99%

Dynamic feed-forward control aided with active disturbance rejection for boost pressure and mass air flow control of diesel engines

Song

Xie

Yang

et al. 2014

Proceedings of the 33rd Chinese Control Conference

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show abstract

“…Reference [3] proposes a methodology of identifying LPV models for nonlinear systems and the proposed methodology was applied to nonlinear turbocharged diesel engines. In reference [4] a data-based grey-box LPV model was developed and the gain-scheduling H ∞ controller was designed. The LPV control technique was also used in [5] to compensate the time delay of the air-fuel ratio control loop for a lean burn SI engine.…”

Section: Introductionmentioning

confidence: 99%

LPV model identification of an EVVT system

Yang

Zhang

Song

et al. 2015

2015 American Control Conference (ACC)

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In this paper, a family of discrete-time system models of an Electric Variable Valve Timing (EVVT) actuator for internal combustion engines under different operational conditions were obtained through the closed-loop system identification, where the complicated EVVT actuating system was treated as a black box. Since it is almost impossible to hold the EVVT cam phasing system at the desired operational condition under open-loop control, closed-loop system identification was adopted. Closed-loop EVVT system models were obtained using the PRBS q-Markov Cover system identification, and with the known closed-loop controller the open-loop system models can be obtained under the given system operational condition such as engine speed, oil viscosity, and battery voltage. The LPV (Linear Parameter Varying) system model was formed based on the obtained family of open-loop discrete-time EVVT models, and the resulting LPV model was further validated by the experimental data. The obtained LPV model is intended to be used for designing the gain-scheduling LPV controllers using the LMI (Linear Matrix Inequality) convex optimization.

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“…[8] proposes a control-oriented identification framework that relies on solution of a set of Linear Matrix Inequalities. [9] discusses an approach where linear local models in a Next, an LPV model with linear fractional dependency on the measured variables is fitted with the condition of containing all the linear models identified in the previous step (differential inclusion). The fit is carried out using nonlinear least squares algorithms.…”

Section: Introductionmentioning

confidence: 99%

LPV identification of a heat distribution system

Trangbaek

Bendtsen

2010

2010 IEEE International Conference on Control Applications

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This paper deals with incremental system identification of district heating systems to improve control performance. As long as various parameters, e.g. valve settings, are kept fixed, the dynamics of district heating systems can be approximated well by linear models; however, the dynamics change significantly when these parameters change. For this reason, we attempt to identify the system using linear parameter varying models. We demonstrate how the so-called "Hansen Scheme," for linear time-invariant systems, can be employed for incremental identification of linear parameter varying systems as well. The approach is tested on a laboratory setup emulating a district heating system, where local controllers regulate pumps connected to a common supply. Experiments show that crosscouplings in the system can indeed be identified in closed-loop operation.

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LPV identification of a turbocharged diesel engine

Cited by 23 publications

References 18 publications

Dynamic feed-forward control aided with active disturbance rejection for boost pressure and mass air flow control of diesel engines

Dynamic feed-forward control aided with active disturbance rejection for boost pressure and mass air flow control of diesel engines

LPV model identification of an EVVT system

LPV identification of a heat distribution system

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