2014 IEEE Intelligent Vehicles Symposium Proceedings 2014
DOI: 10.1109/ivs.2014.6856620
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Adaptive Internal Model Control for Air-Fuel Ratio regulation

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Cited by 6 publications
(7 citation statements)
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“…where b 1 , b 2 are unknown but bounded constants. Therefore, the feedback fuelling controller design for the system (14) is described as an adaptive stabilization problem of the delayed input system (16) with uncertainty (17). With the help of the adaptive stabilization technique, 33 an adaptive feedback fuelling controller of the system (14) can be obtained by constructing a proper Lyapunov-Krasovskii functional, adopting an adaptive factor and employing the LMI technique.…”
Section: Predictive Feedforward Injection Controlmentioning
confidence: 99%
See 1 more Smart Citation
“…where b 1 , b 2 are unknown but bounded constants. Therefore, the feedback fuelling controller design for the system (14) is described as an adaptive stabilization problem of the delayed input system (16) with uncertainty (17). With the help of the adaptive stabilization technique, 33 an adaptive feedback fuelling controller of the system (14) can be obtained by constructing a proper Lyapunov-Krasovskii functional, adopting an adaptive factor and employing the LMI technique.…”
Section: Predictive Feedforward Injection Controlmentioning
confidence: 99%
“…However, the measurement time delay caused by the location of the UEGO sensor, consisting of combustion cycle delay and exhaust mixing transport delay, becomes an obstacle to the achievable performance by the feedback fuelling control. Various A/F control strategies have been developed to tackle the time delay from the fuel injectors to the A/F output, for example, sliding mode control, 10–14 internal model control, 1518 gain-scheduling/linear parameter varying (LPV) control, 1923 model predictive control, 24 the Smith predictor method, 25,26 , the estimate or predict-based method 2729 and control approaches to systems with input time-delay. 30,31 However, there still exist challenges to more sophisticated and efficient solutions to accurate cylinder air charge estimation and suitable A/F feedback control strategy for online computation and implementation in a real engine regardless of nonlinearities, time-delay and uncertain parameters in engine dynamics.…”
Section: Introductionmentioning
confidence: 99%
“…Linear parameter-varying control [8,9], sliding mode control [10,11], and a Smith predictor [12] were introduced to improve the AFR regulation performance. As it is hard to describe the exact AFR path dynamic with certain models and parameters, using adaptive control [1,12,13] for the AFR regulation aroused interest regarding the control issue. A new method of AFR calculation was carried out in Reference [14] using fast response CO and CO 2 sensors.…”
Section: Introductionmentioning
confidence: 99%
“…Besides, Chen et al [5] proposed a linear quadratic optimal tracking controller based on the adaptively estimated biofuel content to track the desired AFR for a lean burn SI engine. Further, in [6, 7], an adaptive internal model control for AFR control was proposed to adapt the unknown time constant of the system plant with a time‐varying delay (that makes the AFR system a parameter dependent system), and uncertain disturbances. Recently, Khajorntraidet et al [8] proposed an adaptive algorithm with Smith predictor to estimate the time delay in port injection engines.…”
Section: Introductionmentioning
confidence: 99%