Intelligent Feedback Linearization for Active Vehicle Suspension Control

2000 ◽  
Vol 123 (4) ◽  
pp. 727-733 ◽  
Author(s):  
Gregory D. Buckner ◽  
Karl T. Schuetze ◽  
Joe H. Beno
Keyword(s):  
Feedback Linearization ◽  
Linear Time ◽  
Estimation Algorithm ◽  
Linear Control ◽  
Effective Control ◽  
Ride Quality ◽  
Vehicle Suspension ◽  
Control Techniques ◽  
Suspension Systems ◽  
Quarter Car

Effective control of ride quality and handling performance are challenges for active vehicle suspension systems, particularly for off-road applications. Off-road vehicles experience large suspension displacements, where the nonlinear kinematics and damping characteristics of suspension elements are significant. These nonlinearities tend to degrade the performance of active suspension systems, introducing harshness to the ride quality and reducing off-road mobility. Typical control strategies rely on linear, time-invariant models of the suspension dynamics. While these models are convenient, nominally accurate, and tractable due to the abundance of linear control techniques, they neglect the nonlinearities and time-varying dynamics present in real suspension systems. One approach to improving the effectiveness of active vehicle suspension systems, while preserving the benefits of linear control techniques, is to identify and cancel these nonlinearities using Feedback Linearization. In this paper the authors demonstrate an intelligent parameter estimation approach using structured artificial neural networks that continually “learns” the nonlinear parameter variations of a quarter-car suspension model. This estimation algorithm becomes the foundation for an Intelligent Feedback Linearization (IFL) controller for active vehicle suspensions. Results are presented for computer simulations, real-time experimental tests, and field evaluations using an off-road vehicle (a military HMMWV). Experimental results for a quarter-car test rig demonstrate 60% improvements in ride quality relative to baseline (non-adapting) control algorithms. Field trial results reveal 95% reductions in absorbed power and 65% reductions in peak sprung mass acceleration using this IFL approach versus conventional passive suspensions.

scholarly journals Nonlinear Control Design of a Half-Car Model Using Feedback Linearization and an LQR Controller

2020 ◽  
Vol 10 (9) ◽  
pp. 3075
Author(s):  
Muhammad Aseer Khan ◽  
Muhammad Abid ◽  
Nisar Ahmed ◽  
Abdul Wadood ◽  
Herie Park
Keyword(s):  
Feedback Linearization ◽  
Control Method ◽  
Control Technique ◽  
Effective Control ◽  
Ride Quality ◽  
Linear Quadratic ◽  
Suspension Systems ◽  
Car Model ◽  
Road Disturbance ◽  
Lqr Controller

Effective control of ride quality and handling performance are challenges for active vehicle suspension systems, particularly for off-road applications. The nonlinearities tend to degrade the performance of active suspension systems; these introduce harshness to the ride quality and reduce off-road mobility. Typical control strategies rely on linear models of the suspension dynamics. While these models are convenient, nominally accurate, and controllable due to the abundance of linear control techniques, they neglect the nonlinearities present in real suspension systems. The techniques already implemented and methods used to cope with problem of Half-Car model were studied. Every method and technique had some drawbacks in terms of complexity, cost-effectiveness, and ease of real time implementation. In this paper, an improved control method for Half-Car model was proposed. First, input/output feedback linearization was performed to convert the nonlinear system of Half-Car model into an equivalent linear system. This was followed by a Linear Quadratic Regulator (LQR) controller. This controller had minimized the effects of road disturbances by designing a gain matrix with optimal robustness properties. The proposed control technique was applied in the presence of the deterministic road disturbance. The results were verified using the Matlab/Simulink toolbox.

Advanced Control Techniques for Semi-Active Suspension Systems

2020 ◽  
Author(s):  
Jessica Gissella Maradey Lazaro ◽  
Kevin Sebastián Cáceres Mojica ◽  
Silvia Juliana Navarro Quintero
Keyword(s):  
Control Technique ◽  
External Control ◽  
Vehicle Suspension ◽  
Driving Experience ◽  
Control Techniques ◽  
Suspension Systems ◽  
Active Suspension Systems ◽  
Advanced Control ◽  
The Subject ◽  
Correct Application

Abstract Semiactive suspension system provides comfort and precise support for any type of driving in vehicles. Their main feature consists in the modification of the damping coefficient by applying an external control. Commonly, these suspensions work with non-linear dampers, such as magnetorheological, electrorheological, pneumatic, dry friction, among others; which generate a discontinuous behavior of force, causing an annoying noise known as “chattering”; however, this can be deleted by the correct application of the control technique. So, control strategy selection is a key task in the modeling of dynamic behavior and to describe the variation of characteristics, as well as to achieve the best vehicle’s driving experience in terms of comfort, performance, reliability, stability, and safety. This article shows three advanced control techniques used to design a semi-active vehicle suspension taking the quarter car as the model. From the review of the state of the art, relevant works and authors on the subject are reported. After, the application of the control techniques is shown together with the results obtained, specially, the performance of the system is carried out by means of computer simulations in the Matlab/Simulink virtual environment, accompanied by near-reality disturbances to verify the effectiveness of this study.

Magnetorheological damper in semi-active vehicle suspension system using SDRE control for a quarter car model

2018 ◽  
Author(s):  
Maria Aline Gonçalves ◽  
Rodrigo Tumolin Rocha ◽  
Frederic Conrad Janzen ◽  
José Manoel Balthazar ◽  
Angelo Marcelo Tusset
Keyword(s):  
Suspension System ◽  
Magnetorheological Damper ◽  
Vehicle Suspension ◽  
Quarter Car Model ◽  
Car Model ◽  
Quarter Car ◽  
Vehicle Suspension System ◽  
Active Vehicle Suspension System

Non-Linear Control of Tilting-Quadcopter Using Feedback Linearization Based Motion Control

2014 ◽  
Author(s):  
Alireza Nemati ◽  
Manish Kumar
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Motion Control ◽  
Feedback Linearization ◽  
Linear Control ◽  
Control Architecture ◽  
Simulation Studies ◽  
Nonlinear Dynamic Model ◽  
Feedback Linearization Control ◽  
Arbitrary Trajectory

In this paper, a nonlinear control of a tilting rotor quadcopter is presented. The overall control architecture is divided into two sub-controllers. The first controller is based on the feedback linearization control derived from the dynamic model of the tilting quadcopter. This controls the pitch, roll, and yaw motions required for movement along an arbitrary trajectory in space. The second controller is based on two PD controllers which are used to control the tilting of the quadcopter independently along the pitch and the yaw directions respectively. The overall control enables the quadcopter to combine tilting and movement along a desired trajectory simultaneously. Simulation studies are presented based on the developed nonlinear dynamic model of the tilting rotor quadcopter to demonstrate the validity and effectiveness of the overall control system for an arbitrary trajectory tracking.

scholarly journals On the ship course-keeping control system design by using robust feedback linearization

2013 ◽  
Vol 20 (1) ◽  
pp. 70-76 ◽  
Author(s):  
Zenon Zwierzewicz
Keyword(s):  
Feedback Linearization ◽  
High Performance ◽  
Linearization Method ◽  
Model Parameters ◽  
Control System Design ◽  
Control Approach ◽  
Ship Model ◽  
Control Techniques ◽  
System Nonlinearity ◽  
Ship Autopilot

Abstract In the paper the problem of ship autopilot design based on feedback linearization method combined with the robust control approach, is considered. At first the nonlinear ship model (of Norrbin type) is linearized with the use of the simple system nonlinearity cancellation. Next, bearing in mind that exact values of the model parameters are not known, the ensuing inaccuracies are taken as disturbances acting on the system. Thereby is obtained a linear system with an extra term representing the uncertainty which can be treated by using robust, H∞ optimal control techniques. The performed simulations of ship course-changing process confirmed a high performance of the proposed controller despite the assumed significant errors of its parameters.

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