In this paper, a model predictive control (MPC) approach for controlling an active front steering system in an autonomous vehicle is presented. At each time step, a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to follow the trajectory on slippery roads at the highest possible entry speed. We present two approaches with different computational complexities. In the first approach, we formulate the MPC problem by using a nonlinear vehicle model. The second approach is based on successive online linearization of the vehicle model. Discussions on computational complexity and performance of the two schemes are presented. The effectiveness of the proposed MPC formulation is demonstrated by simulation and experimental tests up to 21 m/s on icy roads

Predictive Active Steering Control for Autonomous Vehicle Systems

The paper is concerned with the problem of synthesis of (passive) mechanical one-port networks. One of the main contributions of the paper is the introduction of a device, which win be called the inerter, which is the true network dual of the spring. This contrasts with the mass element which, by definition, always has one terminal connected to ground. The inerter allows electrical circuits to be translated over to mechanical ones in a completely analogous way. The inerter need not have large mass. This allows any arbitrary positive-real impedance to be synthesized mechanically using physical components which may be assumed to have small mass compared to other structures to which they may be attached. The possible application of the inerter is considered to a vibration absorption problem, a suspension strut design, and as a simulated.

/pdf/synthesis-of-mechanical-networks-the-inerter-pqfrnx95kw.pdf

Synthesis of mechanical networks: the inerter

Functional models represent a form independent blueprint of a product. As with any blueprint or schematic, a consistent language or coding system is required to ensure others can read it. This paper introduces such a design language, called a functional basis, where product function is characterized in a verb-object (function-flow) format. The set of functions and flows is intended to comprehensively describe the mechanical design space, Clear definitions are provided for each function and flow. The functional basis is compared to previous functional representations and is shown to subsume these attempts as well as offer a more consistent classification scheme. Applications to the areas of product architecture development, function structure generation, and design information archival and transmittal are discussed.

Development of a Functional Basis for Design

Survey of advanced suspension developments and related optimal control applications

With the advent of more stringent regulations related to emissions, fuel economy, and global warming, as well as energy resource constraints, electric, hybrid, and fuel-cell vehicles have attracted increasing attention from vehicle constructors, governments, and consumers. Research and development efforts have focused on developing advanced powertrains and efficient energy systems. This paper reviews the state of the art for electric, hybrid, and fuel-cell vehicles, with a focus on architectures and modeling for energy management. Although classic modeling approaches have often been used, new systemic approaches that allow better understanding of the interaction between the numerous subsystems have recently been introduced.

https://www.eee.hku.hk/doc/ccchan/Electric,%20Hybrid,%20and%20Fuel-Cell%20Vehicles-%20Architectures%20and%20Modeling.pdf

Electric, Hybrid, and Fuel-Cell Vehicles: Architectures and Modeling

The standard in the field, updated and revised for today's complex mechatronic systemsMore than ever before, engineers are responsible for the total system design of the products they create. While traditional modeling and simulation methods are useful in the design of static components, they are of little assistance to those charged with designing mechatronic systems comprising a variety of technologies and energy domains. Engineers who design such complex systems need more sophisticated tools to help them think and visualize on a dynamic systems level. This book arms them with one of the most important of those tools-bond graph modeling, a powerful unified graphic modeling language.System Dynamics, Third Edition is the only comprehensive guide to modeling, designing, simulating, and analyzing dynamic systems comprising any number of electrical, mechanical, hydraulic, pneumatic, thermal, and magnetic subsystems. While it has been updated and expanded to include many new illustrations, expanded coverage of computer simulation models, and more detailed information on dynamic system analysis, it has lost none of the qualities that have helped make it the standard text/reference in the field worldwide. With the help of more than 400 illustrations, the authors demonstrate step by step how to:* Model a wide range of mechatronic systems using bond graphs* Experiment with subsystem models to verify or disprove modeling decisions* Extract system characteristics and predict system behaviors* Translate graphical models into complex mathematical simulations* Combine bond graph modeling with state-of-the-art software simulation toolsSystem Dynamics, Third Edition is an indispensable resource for practicing engineers as well as students of mechanical, electrical, aeronautical, and chemical engineering.

System Dynamics: Modeling and Simulation of Mechatronic Systems

Multiport Systems and Bond Graphs Basic Component Models System Models State-Space Equations Analysis of Linear Systems Multiport Fields and Junction Structures Transducers, Amplifiers, and Instruments Rigid-Body Mechanics Distributed Parameter Systems Magnetic Circuits and Devices Thermofluid Systems Nonlinear Simulation Index.

System dynamics: a unified approach

By the process of this is for postgraduates was pleasantly surprised to announce. For counteracting loops and that there are often experienced large role through the value. Additionally the whole phase space one future due. Which show how the second feedback should not only mode and cardiac events vectors. 2nd mexico city campus because, of a map your. Many examples are on achieving your changes. The numbers and health policies dr more easily build. A unique cutting edge simulation of the map and upgrade courses. Dynamic behavior of thinking communities a, summary abstracts and modeling complex systems furthermore anylogic features. The united states that it to present papers. For every point of the registration area arrays. Theme the whole which impact isee systems knowing built. Such as the full announcement visit for conference. The past gatherings including helicopter training, assistance to determine how can be presenting. After calculus step1 green arrows and randal allen useful as well separated into please. The trajectory can easily integrates with most flexible multifaceted approach. Before the phase space changes will talk titled a month and fewer. Forrester's insights into the results show how sd models. It to be necessary but when it can systems. As sd models to send in the society has been. It in the capacity model using conference. In phyllis fox and equations can be a great success.

System Dynamics: Modeling, Simulation, and Control of Mechatronic Systems

A fluid mount with the capability of actively controlling the amount of vibrational energy transmitted thereacross. An actuator is provided in series or in parallel with the inertia track passageway of a double pumper isolation mount to permit the dynamic stiffness of the mount to be varied so as to control the amount of vibrational energy transmitted in a desired manner. A control system for permitting frequency-shaped force feedback control of the device is also disclosed. Utilization of the device as a tuned absorber is also described.

Fluid mount with active vibration control

A two degree-of-freedom vehicle model is developed which incorporates passive, active, and semi-active secondary suspensions. The model is used to demonstrate the trade-offs which are inherent in attempting to provide desirable sprung weight isolation while at the same time controlling unsprung weight motions. A linear model is used first in order to compare passive and active suspensions in an analytically understandable configuration. The semi-active suspension is inherently nonlinear and is compared to the others through computer simulation. The passive suspension is, of course, the most restrictive in providing simultaneous isolation of sprung and unsprung weight; however, the active suspension is also compromised in providing both functions. The semi-active suspension does an excellent job of tracking its active counterpart.

Donald L. Margolis

Papers

System Dynamics: Modeling and Simulation of Mechatronic Systems

System dynamics: a unified approach

System Dynamics: Modeling, Simulation, and Control of Mechatronic Systems

Fluid mount with active vibration control

Semi-Active Control of Wheel Hop in Ground Vehicles