Integrated System ID and Control Design for an IC Engine Variable Valve Timing System

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
Zhen Ren ◽  
Guoming G. Zhu
Keyword(s):  
System Identification ◽  
Closed Loop ◽  
Test Bench ◽  
Open Loop ◽  
Integrated System ◽  
Variable Valve Timing ◽  
Valve Timing ◽  
Closed Loop System ◽  
Variable Valve ◽  
And Control

This paper applies integrated system modeling and control design process to a continuously variable valve timing (VVT) actuator system that has different control input and cam position feedback sample rates. Due to high cam shaft torque disturbance and high actuator open-loop gain, it is also difficult to maintain the cam phase at the desired constant level with an open-loop controller for system identification. As a result, multirate closed-loop system identification becomes necessary. For this study, a multirate closed-loop system identification method, pseudo-random binary signal q-Markov Cover, was used for obtaining linearized system models of the nonlinear physical system at different engine operational conditions; and output covariance constraint (OCC) controller, an H2 controller, was designed based upon the identified nominal model and evaluated on the VVT test bench. Performance of the designed OCC controller was compared with that of the well-tuned baseline proportional-integral (PI) controller on the test bench. Results show that the OCC controller uses less control effort and has significant lower overshoot than those of PI ones.

Integrated System Identification and Control Design for an IC Engine Variable Valve Timing System

2010 ◽  
Author(s):  
Zhen Ren ◽  
Guoming G. Zhu
Keyword(s):  
System Identification ◽  
Closed Loop ◽  
Test Bench ◽  
Open Loop ◽  
Integrated System ◽  
Variable Valve Timing ◽  
Valve Timing ◽  
Closed Loop System ◽  
Variable Valve ◽  
And Control

This paper applies integrated system modeling and control design process to a continuously variable valve timing (VVT) actuator system that has different control input and cam position feedback sample rates. Due to high cam shaft torque disturbance and high actuator open-loop gain, it is fairly difficult to maintain the cam phase at the desired constant level with an open-loop controller. As a result, multirate closed-loop system identification is a necessity. For this study, multirate closed-loop system identification, PRBS q-Markov Cover, was used for obtaining linearized system models at different engine operational conditions; and the output covariance constraint (OCC) controller, an H2 controller, was designed based upon the identified model and evaluated on the VVT test bench. Performances of the designed OCC controller was compared with those of the baseline PI controller on the test bench. Results show that the OCC controller uses less control effort and has less overshoot than those of PI ones.

Experimental Study on an Electric Variable Valve Timing Actuator: Linear Parameter Varying Modeling and Control

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Ali Khudhair Al-Jiboory ◽  
Guoming G. Zhu ◽  
Shupeng Zhang
Keyword(s):  
System Identification ◽  
Engine Speed ◽  
Gain Scheduling ◽  
Variable Valve Timing ◽  
Linear Parameter ◽  
Valve Timing ◽  
Battery Voltage ◽  
Linear Parameter Varying ◽  
Variable Valve ◽  
And Control

This paper presents experimental investigation results of an electric variable valve timing (EVVT) actuator using linear parameter varying (LPV) system identification and control. For the LPV system identification, a number of local system identification tests were carried out to obtain a family of linear time-invariant (LTI) models at fixed engine speed and battery voltage. Using engine speed and battery voltage as time-varying scheduling parameters, the family of local LTI models is translated into a single LPV model. Then, a robust gain-scheduling (RGS) dynamic output-feedback (DOF) controller with guaranteed H∞ performance was synthesized and validated experimentally. In contrast to the vast majority of gain-scheduling literature, scheduling parameters are assumed to be polluted by measurement noises and the engine speed and battery voltage are modeled as noisy scheduling parameters. Experimental and simulation results show the effectiveness of the developed approach.

Pseudo-random binary sequence closed-loop system identification error with integration control

2009 ◽  
Vol 223 (6) ◽  
pp. 877-884 ◽  
Author(s):  
Z Ren ◽  
G G Zhu
Keyword(s):  
System Identification ◽  
Closed Loop ◽  
Binary Sequence ◽  
Open Loop ◽  
Loop System ◽  
Loop Model ◽  
Closed Loop System ◽  
Identification Error ◽  
Closed Loop Identification ◽  
Integral Controller

This paper studies the closed-loop system identification (ID) error when a dynamic integral controller is used. Pseudo-random binary sequence (PRBS) q-Markov covariance equivalent realization (Cover) is used to identify the closed-loop model, and the open-loop model is obtained based upon the identified closed-loop model. Accurate open-loop models were obtained using PRBS q-Markov Cover system ID directly. For closed-loop system ID, accurate open-loop identified models were obtained with a proportional controller, but when a dynamic controller was used, low-frequency system ID error was found. This study suggests that extra caution is required when a dynamic integral controller is used for closed-loop system identification. The closed-loop identification framework also has significant effects on closed-loop identification error. Both first- and second-order examples are provided in this paper.

Modeling and Control of an Automotive All-Wheel Drive Clutch as a Piecewise Affine System

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Shiming Duan ◽  
Jun Ni ◽  
A. Galip Ulsoy
Keyword(s):  
Closed Loop ◽  
Open Loop ◽  
Lyapunov Theory ◽  
Loop System ◽  
Linear Matrix ◽  
Closed Loop System ◽  
Modeling And Control ◽  
Piecewise Affine ◽  
Wheel Drive ◽  
And Control

Piecewise affine (PWA) systems belong to a subclass of switched systems and provide good flexibility and traceability for modeling a variety of nonlinear systems. In this paper, application of the PWA system framework to the modeling and control of an automotive all-wheel drive (AWD) clutch system is presented. The open-loop system is first modeled as a PWA system, followed by the design of a piecewise linear (i.e., switched) feedback controller. The stability of the closed-loop system, including model uncertainty and time delays, is examined using linear matrix inequalities based on Lyapunov theory. Finally, the responses of the closed-loop system under step and sine reference signals and temperature disturbance signals are simulated to illustrate the effectiveness of the design.

Comparison of Open Loop and Closed Loop System Identification of a UAV

2018 ◽  
Author(s):  
Orkun Simsek ◽  
Ayse Ilden Bayrak ◽  
Sinem Karatoprak ◽  
Atilla Dogan
Keyword(s):  
System Identification ◽  
Closed Loop ◽  
Open Loop ◽  
Loop System ◽  
Closed Loop System

Closed-Loop System Identification Based on Data Correlation

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Hassene Jammoussi ◽  
Matthew Franchek ◽  
Karolos Grigoriadis ◽  
Martin Books
Keyword(s):  
System Identification ◽  
Instrumental Variables ◽  
Closed Loop ◽  
Linear Time ◽  
Open Loop ◽  
Loop System ◽  
Loop Model ◽  
Closed Loop System ◽  
Engine Operation ◽  
Single Input Single Output

A closed-loop system identification method is developed to estimate the parameters of a single input single output (SISO) linear time invariant system (LTI) operating within a feedback loop. The method uses the reference command in addition to the input–output data and establishes a correlation framework to structure the system. The correlation-based method is capable of delivering consistent estimates provided that the specific conditions on the signals are met. The method parallels the instrumental variables four step algorithm (IV4) and is comprised of three steps. First a model is estimated using cross correlation calculations between the reference input signal and the control and measured output signals. In the second step, a prefilter is identified to reduce estimation bias. In the final step, the prefilter, the instrumental variables and the measured signals are employed to estimate the final model. A consistency proof is provided for the proposed estimation process. The method is demonstrated on two examples. The first uses data collected from a diesel engine operation, and an open-loop model relating fueling to engine speed is sought. The identification process is complicated by the presence of nonmeasurable external torque disturbances and stochastic sensor noise. The second example uses data obtained from a time domain simulation of a closed-loop system where high levels of nonmeasured noise and disturbances were considered and a comparison with existing methods is made.

A Cam-Based Electro-Hydraulic Variable Valve Timing System for Pneumatic Hybrid Engines

2009 ◽  
Author(s):  
Mohammad Pournazeri ◽  
Amir Fazeli ◽  
Amir Khajepour
Keyword(s):  
Valve Train ◽  
Variable Valve Timing ◽  
Valve Timing ◽  
System A ◽  
Timing System ◽  
Valve Opening ◽  
And Performance ◽  
High Flexibility ◽  
Variable Valve ◽  
And Control

In this work, a new type of cam-based variable valve timing system has been proposed based on the “lost motion” principle. Using this mechanism, the problems with the valve transition time and control complexity which are still serious concerns for camless valve train systems are solved. This mechanism not only allows the engine to work at different modes of operation as an air hybrid engine but also enables it for continuous torque management. In this system, the control methodology utilizes a cam position feedback to control the valve opening timing. A combination of hydraulic and mechanical systems was utilized to offer high flexibility and robustness in the engine valve control system. A zero dimensional analysis is also conducted to evaluate the functionality and performance of the proposed system.

Algorithm for Closed Loop System Identification Based on Data Correlation

2008 ◽  
Author(s):  
H. Jammoussi ◽  
M. A. Franchek ◽  
K. Grigoriadis ◽  
M. Books
Keyword(s):  
System Identification ◽  
Instrumental Variables ◽  
Closed Loop ◽  
Open Loop ◽  
Loop System ◽  
Loop Model ◽  
Closed Loop System ◽  
Final Model ◽  
Cross Covariance ◽  
Step Algorithm

A closed loop system identification method is developed in which estimation bias from sensor noise and external disturbances is minimized. The method, based on the instrumental variables four step algorithm (IV4), uses three steps. The first step estimates a model using cross covariance calculations between the reference input signal and the control and measured output signals. The second step employs the prefilter identification process from the IV4 process. The third and final step uses the prefilter, the instrumental variables and the reference, control and output signals to estimate the final model. The method is demonstrated on a diesel engine where an open loop model relating fueling to engine speed is sought. The identification example is complicated by the presence of nonmeasurable external torque disturbances due to vehicle accessories.

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