Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Linear time-invariant Systems

Linear time-invariant Systems

A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...

Control Systems: Applications

Control Systems: Applications

Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...

Application of Linearization and Approximation

Application of Linearization and Approximation

A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...

Systems of Linear Equations in Two Variables

Systems of Linear Equations in Two Variables

Solving a system of linear equations is a fundamental concept in algebra. A system of equations consists of two or more linear equations involving the same set of variables. One of the most efficient algebraic methods for solving such systems is the substitution method. This technique involves expressing one variable in terms of the other from one equation and substituting it into the second equation. This method is particularly useful when one of the equations is easily rearranged.Consider the...

Control Systems

Control Systems

Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...

Application of Rates of Change

Application of Rates of Change

The movement of a car along a highway can be examined through key principles of calculus and kinematics. As the car travels, its position varies over time and can be represented mathematically as a function of time. Analyzing the rate of these changes enables the measurement of velocity and acceleration, fundamental aspects of motion analysis.Velocity describes how position changes over time. The average velocity during a specific time interval is calculated by dividing the change in position...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Analysis of explicit model predictive control for path-following control.

PloS one·2018

See all related articles

Search research articles

Related Experiment Video

Updated: Feb 1, 2026

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Published on: June 27, 2025

Explicit model predictive control for linear time-variant systems with application to double-lane-change maneuver.

Junho Lee¹, Hyuk-Jun Chang²

¹Department of Secured Smart Electric Vehicle, Kookmin University, Seoul, Republic of Korea.

|December 5, 2018

Summary

Explicit model predictive control (eMPC) offers a computationally efficient alternative to model predictive control (MPC) for autonomous driving. This study presents a robust eMPC for varying vehicle speeds, outperforming traditional methods in simulations.

More Related Videos

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

The Use of Chemostats in Microbial Systems Biology

The Use of Chemostats in Microbial Systems Biology

Published on: October 14, 2013

Related Experiment Videos

Last Updated: Feb 1, 2026

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Published on: June 27, 2025

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

The Use of Chemostats in Microbial Systems Biology

The Use of Chemostats in Microbial Systems Biology

Published on: October 14, 2013

Area of Science:

Control Systems Engineering
Automotive Engineering
Robotics

Background:

Model Predictive Control (MPC) faces computational challenges in real-time applications.
Explicit Model Predictive Control (eMPC) offers a computationally efficient solution while maintaining performance.
Vehicle dynamics are often simplified to Linear Time-Invariant (LTI) systems, neglecting velocity variations.

Purpose of the Study:

Design and evaluate an eMPC for the Double Lane Change (DLC) maneuver in autonomous driving.
Develop a robust eMPC strategy for discrete-time Linear Time-Variant (LTV) systems.
Enhance eMPC performance by accommodating variations in vehicle longitudinal velocity.

Main Methods:

Designed an eMPC controller for autonomous vehicle trajectory tracking.
Implemented an add-on unit to handle parameter variations (longitudinal velocity) in the eMPC.
Utilized CarSim software for vehicle dynamics simulation and controller performance evaluation.

Main Results:

The proposed eMPC demonstrated superior performance compared to a standard driver model in CarSim at high velocities.
The eMPC designed for LTV systems showed enhanced performance over the LTI-based eMPC.
The add-on unit effectively managed parameter variations without altering the core eMPC solution.

Conclusions:

The developed eMPC is effective for autonomous driving maneuvers like DLC.
The eMPC approach for LTV systems provides robustness against parameter variations, particularly vehicle speed.
This method offers a promising direction for computationally efficient and robust control in autonomous vehicles.