Model Based Control of a Diesel Engine

2010 ◽  
Author(s):  
H. Jammoussi ◽  
M. A. Franchek ◽  
K. Grigoriadis ◽  
M. Books
Keyword(s):  
Diesel Engine ◽  
Transfer Function ◽  
Closed Loop ◽  
Model Identification ◽  
Open Loop ◽  
Loop System ◽  
Engine Model ◽  
Acceleration Feedback ◽  
Performance Specifications ◽  
Step Algorithm

Proposed in this paper is an automated framework for calibration of diesel engine governors. The process involves two basic parts, online engine model identification followed by governor gain design. A previously developed Instrumental Variable 3 Step Algorithm for closed loop system identification is used to estimate the engine model. The identified model is then used in two different governor calibration approaches. The first approach employs a typical governor structure involving acceleration feedback. It will be shown that this governor structure reduces to a classical two degree-of-freedom design. The second approach is based on a procedure in which a desired open-loop transfer function (target transfer function) is shaped such that the same performance specifications as for the first design are satisfied. The control design methods are applied for an off-highway diesel engine with a disengaged transmission. In-field data collected from the engine operating closed-loop is used to identify a model for the open-loop system and the controller gains are then determined. The loop shaping method is then applied to the identified model to design a feedback controller and a prefilter. The efficacy of both loops in terms of tracking performance and noise rejection has been demonstrated through a time domain simulation of both closed-loop step responses.

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.

Structure Flexibility Impacts on Robust Active Vibration Isolation Using Mixed Sensitivity Optimization

2006 ◽  
Vol 129 (2) ◽  
pp. 179-192 ◽  
Author(s):  
Claes Olsson
Keyword(s):  
Transfer Function ◽  
Vibration Isolation ◽  
Force Feedback ◽  
Order Reduction ◽  
Open Loop ◽  
Loop System ◽  
Total Force ◽  
Loop Transfer Function ◽  
Acceleration Feedback ◽  
Active Vibration

Active vibration isolation from an arbitrarily, structurally complex receiver is considered with respect to the impacts of structure flexibility on the open- and closed-loop system characteristics. Specifically, the generally weak influence of flexibility on the open-loop transfer function in the case of total force feedback, in contrast to acceleration feedback, is investigated. The open-loop system characteristics are analyzed based on open-loop transfer function expressions obtained using modal expansion and on modal model order reduction techniques. To closely demonstrate and illustrate the impacts of flexibility on the closed-loop system performance and stability, a problem of automotive engine vibration isolation from a flexible subframe is presented where the neglected dynamics are represented as an output multiplicative model perturbation. A physical explanation as to why the contribution of flexibility to the open-loop transfer function could be neglected in the case of total force feedback in contrast to acceleration feedback is given. Factors for an individual eigenmode to not significantly contribute to the total force output are presented where the deviation of the mode direction relative to the actuator force direction is pointed out as a key one in addition to modal mass and damping coefficient. In this context, the inherent differences between model order reduction by modal and by balanced truncation are being stressed. For the specific automotive vibration isolation application considered, the degradation of robust performance and stability is shown to be insignificant when obtaining a low-order controller by using total force feedback and neglecting flexibility in the design phase.

Computationally Efficient Whole-Engine Model of a Cummins 2007 Turbocharged Diesel Engine

2009 ◽  
Vol 132 (2) ◽  
Author(s):  
Anup M. Kulkarni ◽  
Gregory M. Shaver ◽  
Sriram S. Popuri ◽  
Tim R. Frazier ◽  
Donald W. Stanton
Keyword(s):  
Diesel Engine ◽  
Flow Rate ◽  
Closed Loop ◽  
Engine Performance ◽  
Open Loop ◽  
Operating Conditions ◽  
Nox Emissions ◽  
Computationally Efficient ◽  
Turbocharged Diesel Engine ◽  
Engine Model

This paper describes an accurate, flexible, and computationally efficient whole engine model incorporating a multizone, quasidimension combustion submodel for a 6.7-l six-cylinder turbocharged diesel engine with cooled exhaust gas recirculation (EGR), cooled air, and multiple fuel injections. The engine performance and NOx emissions predicative capability of the model is demonstrated at 22 engine operating conditions. The only model inputs are physical engine control module “control actions,” including injection rates, injection timings, EGR valve position, and variable geometry turbocharger rack position. The model is run using both “open” and “closed” loop control strategies for air/EGR path control, in both cases achieving very good correlation with experimental data. Model outputs include in-cylinder pressure and heat release, torque, combustion timing, brake specific fuel consumption, EGR flow rate, air flow rate, exhaust and intake pressure, and NOx emissions. The model predicts engine performance and emissions with average absolute errors within 5% and 18%, respectively, of true values with “open-loop” air/EGR control, and within 5% and 11% with “closed-loop” air/EGR control. In addition, accurate prediction of the coupling of the in-cylinder combustion and emission-production processes with the boosted, cooled air/EGR gas dynamics is a key characteristic of the model.

Multi-Stage System Identification of a Gas Turbine

2017 ◽  
Author(s):  
Amit Pandey ◽  
Maurício de Oliveira ◽  
Chad M. Holcomb
Keyword(s):  
Gas Turbine ◽  
Closed Loop ◽  
Open Loop ◽  
Loop System ◽  
Closed Loop Control ◽  
Input Output ◽  
Open Loop System ◽  
Loop Control ◽  
Multi Stage ◽  
Identification Techniques

Several techniques have recently been proposed to identify open-loop system models from input-output data obtained while the plant is operating under closed-loop control. So called multi-stage identification techniques are particularly useful in industrial applications where obtaining input-output information in the absence of closed-loop control is often difficult. These open-loop system models can then be employed in the design of more sophisticated closed-loop controllers. This paper introduces a methodology to identify linear open-loop models of gas turbine engines using a multi-stage identification procedure. The procedure utilizes closed-loop data to identify a closed-loop sensitivity function in the first stage and extracts the open-loop plant model in the second stage. The closed-loop data can be obtained by any sufficiently informative experiment from a plant in operation or simulation. We present simulation results here. This is the logical process to follow since using experimentation is often prohibitively expensive and unpractical. Both identification stages use standard open-loop identification techniques. We then propose a series of techniques to validate the accuracy of the identified models against first principles simulations in both the time and frequency domains. Finally, the potential to use these models for control design is discussed.

Application of Anytime Control to an Inherently Unstable Physical System

2015 ◽  
Author(s):  
Wayne Maxwell ◽  
Al Ferri ◽  
Bonnie Ferri
Keyword(s):  
Closed Loop ◽  
Initial Conditions ◽  
Transient Behavior ◽  
Open Loop ◽  
Loop System ◽  
Closed Loop System ◽  
Pendulum System ◽  
Inverted Pendulum System ◽  
Lqr Controller ◽  
Two Stages

This paper extends the use of closed-loop anytime control to systems that are inherently unstable in the open-loop. Previous work has shown that anytime control is very effective in compensating for occasional missed deadlines in the computer processor. When misses occur, the control law is truncated or partially executed. However, the previous work assumed that the open-loop system was stable. In this paper, the anytime strategy is applied to an inverted pendulum system. An LQR controller with estimated state feedback is designed and decomposed into two stages. Both stages are implemented most of the time, but in a small percentage of time, only the first stage is applied, with the resulting closed-loop system being unstable for short periods of time. The statistical performance of the closed-loop system is studied using Monte-Carlo simulations. It is seen that, on average, the closed-loop performance is very close to that of the full-order controller as long as the miss rate is relatively small. However, the variance of the response shows much higher dependence on the miss rate, suggesting that the response becomes more unpredictable. At a critical value of miss rate, the closed-loop system is unstable. The critical miss rate found through simulation is seen to correlate well with the results of a deterministic stability analysis. The statistics on the settling time are also studied, and shown to grow longer as the miss rate increases. The transient behavior of the system is studied for a range of initial conditions.

Stability boundary analysis of highly flexible aircraft with control saturation and structural flexibility

2020 ◽  
Vol 234 (6) ◽  
pp. 1195-1208
Author(s):  
Liang Xu ◽  
Yuping Lu ◽  
Boyi Chen ◽  
Haidong Shen ◽  
Zhen He
Keyword(s):  
Closed Loop ◽  
Stability Boundary ◽  
Open Loop ◽  
Loop System ◽  
Control Signal ◽  
Stable Region ◽  
Structural Flexibility ◽  
Flexible Aircraft ◽  
Control Saturation ◽  
Loop Stability

In this work, a method has been presented to analyze the influence of control saturation and structural flexibility on the stable radius of highly flexible aircraft. A dynamic model of aircraft is constructed followed by the analysis of kinetic characteristics. In this paper, the closed-loop stability boundary of highly flexible aircraft with open-loop instability is studied. The amplitude limit and bandwidth limit of the control signal are considered in the closed-loop stability boundary calculation. Our analysis shows that the boundary is related to the left eigenvector corresponding to the unstable poles and the amplitude constraint of the control signals. Stability of the boundary of feedback control system further reduces the limitation of the bandwidth of actuators. Focused on the phugoid instability of highly flexible aircraft, computational formulation of the closed-loop stable boundary is achieved. The Monte Carlo analysis has been employed to validate the stable region, under the LQR controller. Both the theory and simulations have nice correlations with each other which verify the stability of the closed-loop system, restricted by the open-loop system, and the influence of control signal bandwidth constraints.

Closed-Loop Turbulence Control: Progress and Challenges

2015 ◽  
Vol 67 (5) ◽  
Author(s):  
Steven L. Brunton ◽  
Bernd R. Noack
Keyword(s):  
Closed Loop ◽  
Response Times ◽  
Aerodynamic Drag ◽  
Model Identification ◽  
Open Loop ◽  
Mixing Enhancement ◽  
Strong Nonlinearity ◽  
Open Problems ◽  
Loop Control ◽  
Turbulence Control

Closed-loop turbulence control is a critical enabler of aerodynamic drag reduction, lift increase, mixing enhancement, and noise reduction. Current and future applications have epic proportion: cars, trucks, trains, airplanes, wind turbines, medical devices, combustion, chemical reactors, just to name a few. Methods to adaptively adjust open-loop parameters are continually improving toward shorter response times. However, control design for in-time response is challenged by strong nonlinearity, high-dimensionality, and time-delays. Recent advances in the field of model identification and system reduction, coupled with advances in control theory (robust, adaptive, and nonlinear) are driving significant progress in adaptive and in-time closed-loop control of fluid turbulence. In this review, we provide an overview of critical theoretical developments, highlighted by compelling experimental success stories. We also point to challenging open problems and propose potentially disruptive technologies of machine learning and compressive sensing.

scholarly journals Control of Flexible Manipulator Systems

1996 ◽  
Vol 210 (2) ◽  
pp. 113-130 ◽  
Author(s):  
M O Tokhi ◽  
A K M Azad
Keyword(s):  
Closed Loop ◽  
Control Strategies ◽  
Open Loop ◽  
Flexible Manipulator ◽  
Closed Loop Control ◽  
Loop Control ◽  
Acceleration Feedback ◽  
Low Pass ◽  
Input Torque ◽  
Collocated Control

This paper presents an investigation into the development of open-loop and closed-loop control strategies for flexible manipulator systems. Shaped torque inputs, including Gaussian-shaped and low-pass (Butter-worth and elliptic) filtered input torque functions, are developed and used in an open-loop configuration and their performance studied in comparison to a bang-bang input torque through experimentation on a single-link flexible manipulator system. Closed-loop control strategies that use both collocated (hub angle and hub velocity) and non-collocated (end-point acceleration) feedback are then proposed. A collocated proportional and derivative (PD) control is first developed and its performance studied through experimentation. The collocated control is then extended to incorporate, additionally, non-collocated feedback through a proportional integral derivative (PID) configuration. The performance of the hybrid collocated and non-collocated control strategy thus developed is studied through experimentation. Experimental results verifying the performance of the developed control strategies are presented and discussed.

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