Half-car Active Suspension Research Articles

Constrained Active Suspension Control with Parameter Uncertainty for Non-stationary Running Based on LMI Optimization

The research on a constrained robust H∞ control of half-car active suspension-based linear matrix inequality (LMI) optimization method was carried out for non-stationary vehicle running conditions in this study. The H∞ state feedback controller of active vehicle suspension system was proposed which contains the time-domain hard constraints and differential equation model of the half-car control system with parameter uncertainty for non-stationary running was established. The results of vehicle dynamics analysis indicate that the dynamic performance of this half-car active suspension controlled by the proposed control strategy is obviously superior to the performances of passive suspensions. The proposed control strategy shows good stability, even though vehicles are in non-stationary running and the actual system parameters (including unsprung mass, suspension rigidity, and tire rigidity) are uncertain. Moreover, besides improving the vehicle ride comfort, the proposed control method can also ameliorate the dynamic flexibility of vehicle suspension system, static-dynamic load ratio response characteristic of vehicle tyres, and requirement of constrained control forces.

Design of half-car active suspension system for passenger riding comfort

In this paper, the active suspension system is designed to reduce vibration on the passenger seat caused by change in road-surface shapes or disturbance. PID control is utilized in the design of this active suspension system, and Direct Synthesis method is proposed to tune PID parameters. Direct Synthesis method optimize PID tuning parameters to achieve desired output response in different road surface. In this study, three interference signals are used as disturbance from surface road i.e step, impulse, and sinus. The aim of the suspension control design is to obtain the control parameters that conform to ISO 2631. The simulation results show that value of τc 0.0002 for step disturbance provide aRMS 0.086 m/s2 and damping ratio 0.21. For impulse input the value of τc 0.002 provide aRMS 0.112 m/s2 and damping ratio of 0.22. For sinus input value of τc 0.00005 provide aRMS 0.09 m/s2.

Adaptive prescribed performance control of half-car active suspension system with unknown dead-zone input

Abstract This paper proposes a novel adaptive control scheme for half-car active suspension system (HCASS) with unknown dead-zone input. Under the proposed control framework, the overall HCASS is divided into two subsystems. The proposed controller is designed based on the first subsystem, and the second subsystem is regarded as zero dynamics of HCASS. For the first subsystem, a new robust adaptive strategy is first constructed to compensate the adverse effects of unknown dead-zone input nonlinearities. Further, in order to ensure some important state variables within the given restrictive conditions all the time, a novel prescribed performance control strategy (PPC, for short) is designed. For the second subsystem, the corresponding stability analysis of zero dynamics is presented. Finally, the solution of the resulting closed-loop system is ensured to be uniformly ultimately bounded, and the effectiveness of the proposed approach is illustrated by a strict and complete simulation analysis.

Simulation of disturbance rejection control of half-car active suspension system using active disturbance rejection control with decoupling transformation

In recent years, Active Disturbance Rejection Control (ADRC) has become a popular control alternative due to its easy applicability and robustness to varying processes. In this article, ADRC with input decoupling transformation (ADRC-IDT) is proposed to improve ride comfort of a vehicle with an active suspension system using half-car model. The ride performance of the ADRC-IDT is evaluated and compared with decentralized ADRC control as well as the passive system. Simulation results show that both ADRC and ADRC-IDT manage to appreciably reduce body accelerations and able to cope well with varying conditions typically encountered in an active suspension system. Also, it is sufficient to control only the body motions with both active controllers to improve ride comfort while maintaining good road holding and small suspension working space.

Performance Analysis of Half Car Suspension Model with 4 DOF using PID, LQR, FUZZY and ANFIS Controllers

The suspension system helps to enhance the ride quality, steering stability, passenger comfort and NVH. In this paper, using a half car active suspension model with 4 Degrees Of Freedom (4 DOF) the controllers such as Proportional Integral Derivative, Linear Quadratic Regulator, Fuzzy and Adaptive Neuro Fuzzy Inference System (ANFIS) are designed using MATLAB-Simulink. The response of these controllers has been analysed using the random road profile (ISO 8608) against the conventional passive suspension system. The results indicate that ANFIS based controller performs better on the parameters ‘Settling Time’ and ‘Amplitude’ of the road disturbances, compared with other controllers.

Self-tuning PID controller design using fuzzy logic for half car active suspension system

A car active suspension system plays an imperative role in adequately guaranteeing the stability of the car, retaining the continuous road wheel contact and improving the suspension performances. In this paper, Proportional Integral Derivative (PID), fuzzy logic and $$\hbox {H}\infty $$ controllers are used to control the car suspension system based on half car model. Moreover, a self-tuning PID controller based on fuzzy logic is developed to improve the performance of the system. The proposed structure overcomes the difficulty of having suitable responses in controlling the process in all conditions, especially when the system parameters are changing. The controllers are designed based on the mathematical model of the system. Through the proposed method, suspension working space is minimized and the best comfort of the driver is achieved. The comparison between simulation results demonstrates that by applying the presented method, the performance of the suspension system will be improved significantly.

Sliding Mode Control of Half-car Active Suspension

Sliding Mode Control of Half-car Active Suspension

Adaptive Fault Tolerant Control of a Half-Car Active Suspension Systems Subject to Random Actuator Failures

Adaptive fault tolerant control problem for half-car active suspension systems subject to stochastic actuator failures is considered in this paper. Two stochastic functions related to Markovian variables have been introduced to denote the failure for the front and the rear actuators embedded between the car body and the wheel–axle. This makes the problem practical, yet it makes the stability analysis of zero dynamics involving Markovian variables very challenging. By employing adaptive backstepping technique, a new adaptive fault tolerant control scheme is proposed, which ensures the boundedness in probability of the considered systems. Comparative simulation results for a half-car active suspension system are presented to show the effectiveness of the proposed control scheme.

RELIABLE ROBUST CONTROLLER FOR HALF-CAR ACTIVE SUSPENSION SYSTEMS BASED ON HUMAN-BODY DYNAMICS

The paper investigates a non-fragile robust control strategy for a half-car active suspension system considering human-body dynamics. A 4-DoF uncertain vibration model of the driver’s body is combined with the car’s model in order to make the controller design procedure more accurate. The desired controller is obtained by solving a linear matrix inequality formulation. Then the performance of the active suspension system with the designed controller is compared to the passive one in both frequency and time domain simulations. Finally, the effect of the controller gain variations on the closed-loop system performance is investigated numerically.

Robust Control for Ride Comfort Improvement of an Active Suspension System considering Uncertain Driver's Biodynamics

This paper presents a robust output feedback control design for a half-car active suspension system by considering driver's biodynamics. Because of different kinds of passengers there is a wide range of variations in biodynamics' parameters, and an appropriate robust control design approach, μ-synthesis approach, is used to tackle these parametric uncertainties. The performance of active suspension system with designed controller is compared with the open loop one in both frequency and time domain simulations. The results show that μ-synthesis based controller achieves great performance in ride comfort. In addition, suspension deflections, road holding and actuators force remain in reasonable regions. Finally, analysis of robust performance indicating that the μ-synthesis controller remains stable in a wide range of frequency domain despite parametric uncertainties, which is also validated by a specific case in this paper.

A New Fuzzy Control Strategy for Active Suspensions Applied to a Half Car Model

In this paper, we propose a new control strategy for the active control of a hydraulically controlled half-car active suspension system. Our study propose a special construction of the suspension system where the hydraulic actuator is to be placed in series with the conventional passive one to form a special case of low-frequency active suspension. The full dynamics of the electro-hydraulic servo-valve and hydraulic actuator were employed. Response of proposed control strategy has been tested for different road profiles and riding conditions including car chassis rolling effect when cornering and pitch movements when braking/acceleration. Results have shown superior performance of our modified controller over passive suspensions and many other controllers of previous studies. Simulations show that our proposed controller provide better passenger comfort as it lowers maximum body acceleration by 67% and with reduction in body travel by 89% of that of passive one. Also, our proposed control strategy has shown better road handling and car stability over a whole range of road and inertial disturbances.

Saturated Adaptive Robust Control for Active Suspension Systems

This paper investigates the problem of vibration control in vehicle active suspension systems, whose aim is to stabilize the attitude of the vehicle and improve ride comfort. In response to uncertainties in systems and the possible actuator saturation, a saturated adaptive robust control (ARC) strategy is proposed. Specifically, an antiwindup block is added to adjust the control strategy in a manner conducive to stability and performance preservation in the presence of saturation. Furthermore, the proposed saturated ARC approach is applied to the half-car active suspension systems, where nonlinear springs and piecewise linear dampers are adopted. Finally, the typical bump road inputs are considered as the road disturbances in order to illustrate the effectiveness of the proposed control law.

NARMA-L2 Control of a Nonlinear Half-Car Servo-Hydraulic Vehicle Suspension System

In this paper, the performance of a nonlinear, 4 degrees-of-freedom, servo- hydraulic half-car active vehicle suspension system is compared with that of a passive vehicle suspension system with similar model parameters. The active vehicle suspension system is controlled by an indirect adaptive Neural Network-based Feedback Linearization controller (NARMA-L2). Hydraulic actuator force tracking is guaranteed by an inner Proportional+Integral+Derivative-based force feedback control loop. The output responses of the vehicles are presented and analyzed in the frequency and time domains, in the presence of model uncertainties in the form of variation in vehicle sprung mass loading. The results show that the NARMA-L2-based active vehicle suspension system performed better than the passive vehicle suspension system within the constraints.

Digital Controller Design for Half-Car Active Suspension System with Using Singular Perturbation Theory

In this paper the digital controller design for vehicle suspension system, based on a half-car model using singular perturbed systems is considered. This strategy is based on the slow and fast subsystems controller design. The simulation results show them favorable performance of the controller and achieve fast and good response.

Observer and Controller Design for Half-Car Active Suspension System Using Singular Perturbation Theory

In this paper the singular perturbation theory is used to design observer for estimation of state variables for proper control of half-car active suspension system. The liner quadric Gaussian (LQG) controller has been used to obtain feedback gains. The suspension system performance is optimized with respect to ride comfort, tire deflections and front and rear suspension travels. The simulation results show that the proposed approach is highly effective in evaluating the performance of an active suspension system.

Almost disturbance decoupling control of mimo nonlinear system subject to feedback linearization and a feedforward neural network: Application to half-car active suspension system

A novel tracking and almost disturbance decoupling problem of multi-input, multi-output (MIMO) nonlinear systems based on feedback linearization and a multi-layered feedforward neural network approach has been proposed. The feedback linearization and neural network controller guarantees exponentially global uniform ultimate bounded stability and almost disturbance decoupling performance without using any learning or adaptive algorithms. The new approach renders the system to be stable with the almost disturbance decoupling property at each step when selecting weights to enhance the performance if the proposed sufficient conditions are maintained. One example, which cannot be solved by the existing approach of the almost disturbance decoupling problem because it requires the sufficient conditions that the nonlinearities that multiply the disturbances satisfy structural triangular conditions, is proposed to exploit the fact that the tracking and the almost disturbance decoupling performances are easily achieved by the proposed approach. In order to demonstrate the practical applicability, a famous half-car active suspension system is investigated.

A New Optimal Nonlinear Approach to Half Car Active Suspension Control

A New Optimal Nonlinear Approach to Half Car Active Suspension Control

Road-adaptive algorithm design of half-car active suspension system

This paper describes the application of a road-adaptive nonlinear control integrated with active suspensions into a half-car model by employing road-adaptive algorithm schemes. We augment this controller with a road-adaptive algorithm which continuously monitors suspension travel and adjusts online the shape of the filter nonlinearity in response to different road profiles. This adaptive design realizes the true potential of active suspensions, which is their ability to yield a better performance over a much wider range of road surfaces than do original backstepping control, optimal control, and passive suspensions. As a result, our road-adaptive algorithm does indeed possess the potential to achieve the desired control goals. Furthermore, some simulation results are given to illustrate the excellent performance of half-car active suspensions.

Half-Car Active Suspension System with a Reduced Order State Feedback Control

Half-Car Active Suspension System with a Reduced Order State Feedback Control

Parameterization of all stable controllers stabilizing full state information systems and mixed sensitivity

Analytical expressions for the parameterization of all one- and two-degrees-of-freedom stable controllers stabilizing full state information systems are presented. It is assumed that the strictly proper, lumped, and linear time-invariant nominal plant has a stabilizable realization and is strongly stabilizable, and that the number of entries of the plant state is even and is double the number of entries of the plant input. Right and left coprime factorizations of the transfer function of the plant in terms of the matrices of the plant realization are proposed, the Diophantine equation is solved, and stabilizing controllers are obtained using Youla parameterization. Conditions for strong stability are given, and the free parameters of the stabilizing controllers solving the mixed sensitivity problem are established. The results are illustrated through simulation examples of a half-car active suspension system and a two-degrees-of-freedom planar rotational robot.