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— The aim of this research work is to design three types of active controller for active suspension system. A 3 Degree Of Freedom (DOF) quarter car model is used to analyze and compare the performance characteristics of the active system with the uncontrolled system or passive suspension system. Suspension system plays an essential role in isolating vehicle body from road shocks and vibrations. The goal of suspension system is to improve ride comfort, road handling and stability of vehicles. The objective is to determine control strategy to deliver better performance with respect to seat velocity, suspension deflection, sprung mass displacement, sprung mass velocity, peak overshoot, settling time etc. The three controllers designed are LQR based fuzzy controller, Fuzzy PID controller and Linear Quadratic Controller (LQR). In this work, MATLAB/SIMULINK software is used for simulation purpose and simulation result shows that active suspension system exhibits better result than passive suspension system. Also the result of comparison shows that Fuzzy LQR controller based active suspension system gives better result and stability as compared to other active controllers and passive model. Keywords—Degree of freedom(DOF),LQR based Fuzzy controller,Fuzzy PID controller, LQR controller, seat velocity, suspension deflection, sprung mass displacement, sprung mass velocity, peak overshoot, settling time.
Applied Mechanics and Materials, 2014
The objective of this paper is to design a linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controllers for an active anti-roll bar system. The use of an active anti-roll bar will be analysed from two different perspectives in vehicle ride comfort and handling performances. This paper proposed the basic vehicle dynamic modelling with four degree of freedom (DOF) on half car model and are described that show, why and how it is possible to control the handling and ride comfort of the car, with the external forces also control strategies on the front anti-roll bar. By simulation analysis, the design model is validity and the performance under control of linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controller are achieved. Both two controllers are modeled in MATLAB/SIMULINK environment. It has to be determined which control strategy delivers better performance with respect to roll angle and the roll rate of half vehicle body. The result shows, however, that LQG produced better response compared to a LQR strategy.
Applied Mechanics and Materials, 2014
ABSTRACT This paper presents and analyses a performance comparison between a Linear Quadratic Regulator (LQR) and Composite Nonlinear Feedback (CNF) controllers for an active anti-roll bar (ARB) system. The anti-roll bar system has to balance the trade-off involving ride comfort and handling performance. The basic vehicle dynamic modelling with four degree of freedom (DOF) on half car model is proposed. The design model is validity and the performances of roll angle and roll rate under control of LQR and CNF controller are achieved by using simulation analysis. Both two controllers are modeled in MATLAB/SIMULINK environment. It has to be determined which control strategy delivers better performance with respect to roll angle and the roll rate of half vehicle body to achieve this goal. The result shows, the CNF LQR fusion control strategy improve the performance compared to LQR and CNF control strategy.
In this paper a MATLAB SIMULINK model of seven Degrees Of Freedom (DOF) full vehicle model is developed. Mathematical equations are obtained using Newton ' s second law and free body diagram concept. Validation of the SIMULINK model is obtained to ensure that the model is suitable for studying the ride comfort. A Genetic algorithm optimization technique is used to find the optimum values of spring stiffness and damping coefficient for front and rear passive suspension system of the seven DOF vehicle model at variable velocities which improve the performance of the suspension system of the vehicle. Also Proportional Integral (PI) controller is implemented to the model to study its effect on ride comfort. Comparison of the results for body acceleration and sprung mass displacement of the optimized data of suspension parameters and model with PI controller are illustrated. The results show that the optimized parameters and PI controller give significant improvements of the vehicle ride performance over the passive suspension system.
Optimal vehicle handling, good driving pleasure, best comfort for passengers, effective and efficient isolation of road noise and vibration in suspension systems has been a key research area. In this paper two control techniques; a conventional Proportional Integral and Derivative (PID) and intelligent Fuzzy Logic Control (FLC) schemes are proposed and compared for the passive quarter car suspension system. MATLAB Simulink environment was used for both designs, investigation of the effects of the two control techniques, their comparison and verification of the results obtained and the results are shows the effectiveness of the controllers. Index Terms-Proportional Integral and Derivative (PID), Fuzzy Logic Control (FLC), Quarter car.
In the present work, the performance of a vehicle active suspension system using different control strategies is investigated under different road disturbances. The tested control strategies are proportional integral derivative (PID), A quarter car and full car vehicle models have been used to model suspension system of a passenger car. For PID, Different road profiles have been input to the modeled active suspension system. These road profiles are Single Sine bump, Pulse input, Step input, Ramp input and Longitudinal profiles, which classifications are based on the International Organization for Standardization (ISO 8606).
Mathematical Problems in Engineering, 2014
This paper addresses the problem of control of an active suspension system accomplished using a computer. Delay in the states due to the acquisition and transmission of data from sensors to the controller is taken into account. The proposed control strategy uses state predictors along with sliding mode control technique. Two approaches are made: a continuous-time and a discrete-time control. The proposed designs, continuous-time and discrete-time, are applied to the active suspension module simulator from Quanser. Results from computer simulations and experimental tests are analyzed to show the effectiveness of the proposed control strategy.
Jurnal Teknologi, 2014
This paper describes the mathematical modeling and control of a nonlinear active suspension system for ride comfort and road handling performance by using multi-body dynamics software so-called CarSim. For ride quality and road handling tests the integration between MATLAB/Simulink and multi-body dynamics system software is proposed. The control algorithm called the Conventional Composite Nonlinear Feedback (CCNF) control was introduced to achieve the best transient response that can reduce to overshoot on the sprung mass and angular of control arm of MacPherson active suspension system. The numerical experimental results show the control performance of CCNF comparing with Linear Quadratic Regulator (LQR) and passive system.
This paper aims to design a controller for a vehicle active suspension system of an automobile. The vehicle cab motion is limited to heave in the y-direction and a small amount of pitch u of the vehicle’s longitudinal axis. The tires are assumed to remain in contact with the road surface at all times. Vehicle is subjected to random excitation due to road unevenness and variable velocity and sometimes due to speed bumps. The system has three translational degree of freedom. Based on the degree of freedom, from a rider’s comfort point of view the damping parameters and spring stiffness are adjusted to fit the criteria of a less bumpy ride. For controlling the vehicles degree of movement, the controller is designed based on Proportional controller, PID Controller, and pole placement. For the purpose of analysis, this paper only deals with the linear part of the system and excludes non-linear portion from the equation. The result shows that the response of the controlled suspension system can trace the input signal that is the PID controller is successfully able to control the variable shock absorber in order to eliminate the road surface disturbances effect to the car body.
In this paper, a genetic algorithm (GA) based in an optimization approach is presented in order to search the optimum weighting matrix parameters of a linear quadratic regulator (LQR). A Macpherson strut quarter car suspension system is implemented for ride control application. Initially, the GA is implemented with the objective of minimizing root mean square (RMS) controller force. For single objective optimization, RMS controller force is reduced by 20.42% with slight increase in RMS sprung mass acceleration. Trade-off is observed between controller force and sprung mass acceleration. Further, an analysis is extended to multi-objective optimization with objectives such as minimization of RMS controller force and RMS sprung mass acceleration and minimization of RMS controller force, RMS sprung mass acceleration and suspension space deflection. For multi-objective optimization, Pareto-front gives flexibility in order to choose the optimum solution as per designer’s need.
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