One Step Ahead MPC for an Automotive Control Application

Balau, Andreea Elena; Lazăr, Corneliu

doi:10.1109/ecbs-eerc.2011.18

Cited by 7 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In such scheme, future behaviour of the state variables are estimated linearly at time t+∆t depending on the system state variables at time 't' and previous dynamical behaviour of the system itself [22]. One step ahead prediction is used with adaptive feature, using an on-line identification technique for parameter estimation [23,24]. The scheme is suitable for a non linear and time varying system and automatically updates itself, in case system is exposed to some uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Dynamic performance improvement of isolated power system using intelligently controlled SMES

Zargar

Mufti

Lone

2020

IET Generation Trans & Dist

View full text Add to dashboard Cite

Isolated power system comprising of wind, diesel and energy storage presents an effective economical approach for supplying power. Advanced and intelligent control techniques are required to improve the power dispatch between storage devices and wind-diesel system especially during disturbances. This paper focuses on development of one step ahead adaptively controlled superconducting magnetic energy storage (SMES) for smoothing the power fluctuations of a standalone wind-diesel power system. Two sets of gate turn off (GTO) converters are utilized for obtaining a four quadrant operation of SMES system. System is represented by a third order autoregressive discrete time model. For estimating the system parameters online, recursive least square algorithm is used. System is considered as a two input two output system, where real and reactive powers demanded by SMES are the control signals issued by the controller. To restrict the energy trade within limits, constraints are imposed on the SMES current. Discrete time model of SMES is used for converting SMES current constraints into the energy level predictions and a separate model is then used for imposing the constraints. Scheme is tested for two disturbances and in both the cases, SMES current constraints are never violated while reducing the frequency and voltage deviations significantly.

show abstract

Section: Introductionmentioning

confidence: 99%

Dynamic performance improvement of isolated power system using intelligently controlled SMES

Zargar

Mufti

Lone

2020

IET Generation Trans & Dist

View full text Add to dashboard Cite

show abstract

“…Previous studies have controlled automobile drive systems, including backlash via modeling. In particular, many outcomes are related to model predictive control and state estimations [18][19][20][21][22][23][24][25]. These are broadly considered effective techniques.…”

Section: Introductionmentioning

confidence: 99%

Vibration Control of Automotive Drive System With Nonlinear Gear Backlash

Yonezawa

Kajiwara

Sato

et al. 2019

Journal of Dynamic Systems, Measurement, and Control

View full text Add to dashboard Cite

In automotive drive systems, differential gear backlash degrades the control performance. Specifically, a shock torque, which is generated when the gear runs freely and collides with the backlash, increases the vibration amplitude. Consequently, it is important to develop a vibration control method to suppress the adverse effect of nonlinearity due to backlash. Furthermore, considering implementations on actual vehicles, design at the development site, and mass production, a simple and practical control method is necessary. This paper describes the configuration of a basic experimental device, which abstracts an actual vehicle to focus on the influence due to backlash while reflecting the basic structure of an automotive drive system. Next, a basic controller is designed using a mixed H2/H∞ control theory, and a servo system is constructed to track the target value. A simple control mode switching algorithm is proposed for backlash compensation. This algorithm is suited to practical applications because it uses only an output without a state estimation and it compensates for performance deteriorations due to the nonlinearity by operating a single linear controller. Finally, simulations and experiments verify the effectiveness of the proposed control system.

show abstract

“…Balau and Lazar developed a MPC algorithm for dual clutch powershift automatic transmissions with dry clutches using a novel more accurate state space piecewise affine drivetrain model. 21 The sources of flexibilities are the clutch and driveshafts. Due to the complexity of the model and necessity for a real time solution, the authors commented that the standard sufficiently long horizon MPC approach did not represent a viable solution.…”

Section: Introductionmentioning

confidence: 99%

Model based predictive engine torque control for improved drivability

Atabay

Ötkür

Ereke

2017

Proceedings of the Institution of Mechanical Engineers, Part D:

View full text Add to dashboard Cite

Elasticity of the various driveline components and backlash originating from gear reduction mechanisms and fasteners may cause torsional vibrations resulting in unintended shunt and shuffle behaviours, when a vehicle is subjected to an acceleration change request. As a result of recent improvements to engine control structures and computational capability developments during the last few decades, the idea of using generated brake torque control has been considered a state of the art research topic among academic researchers and original equipment manufacturers (OEMs). In order to improve transient vehicle response to an acceleration change manoeuvre, a novel engine generated brake torque based model predictive control (MPC) algorithm with an additional anti-shuffle control element has been developed to manipulate the pedal map oriented torque demand signal in an automotive powertrain application. A four mass powertrain model was built and model validation considering longitudinal vehicle dynamics was performed with vehicle level tests using a tip-in followed by a tip out acceleration pedal signal input manoeuvre. Comparison of simulation results and vehicle test data shows that the proposed model is capable of capturing the vehicle acceleration profile revealing unintended error states for the specified input signals. MPC structures based on three mass vehicle models (derived from the four mass model via subtracting tyre dynamics due to high order nonlinearities at the tyre model) was developed in a “MATLAB/Simulink” environment to obtain a smooth and responsive acceleration profile. The MPC controller delivers signal states with the expected performance metrics without error states such as excessive jerks and shuffles. An additional engine to wheel speed difference based proportional controller is employed in order to further reduce powertrain oscillations without compromising from overall system response speed resulting in a comfortable drive.

show abstract

One Step Ahead MPC for an Automotive Control Application

Cited by 7 publications

References 15 publications

Dynamic performance improvement of isolated power system using intelligently controlled SMES

Dynamic performance improvement of isolated power system using intelligently controlled SMES

Vibration Control of Automotive Drive System With Nonlinear Gear Backlash

Model based predictive engine torque control for improved drivability

Contact Info

Product

Resources

About