A number of activevehiclesuspensioncontrolstrategies has been studied and/or proposed by researchers. Agharkakli et al  investigated the application of an LQR controller to an activesuspensionsystem. The model used was a quarter vehicle model. A single cosine and repeated cosine bumpy profiles were input as road disturbances. They concluded that activesuspension systems implementing linear quadratic regulator (LQR) gave lower amplitudes and faster settling time for sprung- mass displacement and acceleration, suspension travel, and wheel deflection compared to passive ones. However, performance was evaluated for a discrete, limited single cosine bump but not for a standard real road (ISO random road profile) which is more representative and realistic . Kumar  tested the performance of an activesuspensionsystemusing a proportional integral derivative (PID) controller whose gains are tuned using Zeigler and Nichols tuning rules. A quarter vehicle model has been used. A unit step and an ISO random road were used as road disturbances. He reported that the PID- based activesuspensionsystem improved ride comfort but with no appreciable improvement in road holding . Changizi et al  compared the performance of activesuspensionsystemusing PID and FLC controllers based on a quarter vehicle model. A unit step input was used as road disturbance. Their activesuspensionsystemusing the fuzzy logic control (FLC) controller performed better than when using the PID controller. However, road handling performance was not evaluated in their work  . Sharkawy  compared the performance of an activesuspensionsystem under LQR, FLC and adaptive FLC controllers. A quarter vehicle model has been used to investigate the suspension behaviour under a unit step input and a varying frequency sine wave as road disturbances. He concluded that the performance quality in a descending order was adaptive FLC, FLC and LQR respectively. Other controlstrategies such as PID Controller tuned by Back Propagation Neural Network , adaptive neuro active force control  and Fuzzy logic controller optimized by genetic algorithm  have been proposed for activesuspension systems.
were focused on the interaction between the ASS and ABS. Lin and Ting  used two back-stepping controllers for decentralized integration of ASS and ABS in a quarter car model. In this study, the stopping distance was improved by increasing tire normal force, but the performance of suspensionsystem was ignored. Wang et al.  investigated a Takagi-Sugeno (T-S) fuzzy neural network for integration of ASS and ABS. In another work, fuzzy and sliding mode control was used for integration of braking and steering control systems . The results indicated that the proposed switching multi-layer controlstrategies improved the vehicleperformance in different situations. In order to control the vertical and yaw motions, Vassal et al.  used the gain- scheduled method for both suspension and braking control systems. Kaldas and Soliman  investigated the influence of preview controller for both ASS and ABS systems in half car model. In this work, the ride performance of vehicle is considered in terms of ride comfort and road holding and the braking performance is evaluated in terms of braking distance. Riaz and Khan  designed a neuro-fuzzy based adaptive control scheme for ASS and a sliding mode control for ABS, for each station of vehicle. Zhang et al.  proposed a linear quarter model of activesuspensionsystem and used barrier Lyapunov function control method for both ASS and ABS systems. The results of this work showed that, the ASS can assist the ABS by increasing the tire vertical force to reduce the braking distance.
A heavily damped suspension will yield good vehicle handling, but also transfers much of the road input to the vehicle body. When the vehicle is traveling at low speed on a rough road or at high speed in a straight line, this will be perceived as a harsh ride. The vehicle operators may find the harsh ride objectionable, or it may damage cargo. A lightly damped suspension will yield a more comfortable ride, but can significantly reduce the stability of the vehicle in turns, lane change maneuvers, or in negotiating an exit ramp. Good design of a passive suspension can to some extent optimize ride and stability, but cannot eliminate this compromise. The need to reduce the effects of this compromise has led to the development of active and semiactive suspensions. Active suspensions use force actuators. Unlike a passive damper, which can only dissipate energy, a force actuator can generate a force in any direction regardless of the relative velocity across it. Using a good control policy (here fuzzy loggy), it can reduce the compromise between comfort and stability. However, the complexity and large power requirements of active suspensions make them too expensive for wide spread commercial use. Semiactive dampers are capable of changing their damping characteristics by using a small amount of external power. Semi active suspensions are less complex, more reliable, and cheaper than active suspensions. They are becoming more and more popular for commercial vehicles.
The activesuspension of ground vehicles is a very active subject for research owing to its potential to improve the vehicle ride performance. Many analytical and experimental studies performed recently have been concluded that the activesuspension can in general provide substantial performance improvements over optimized passive suspensions [1, 2, 3, 4, 5 and 6]. Using Fuzzy-Logic control in a simple form with the activesuspensionsystem applied to a quarter vehicle model is studied theoretically by .  evaluated the ride performance under various road inputs. The simulation results indicated a great enhancement in the ride performance in terms of body acceleration and suspension working space for different road inputs.
In the proposed control algorithm, supply current is directly measured by a sensor and will be regulated as sinusoidal signal by the current controller which is known as Indirect current control scheme. With this indirect current control, by using only PI controller it is impossible to achieve sinusoidal supply current because the supply currents are indirectly controlled by regulating the filter currents which are the non-sinusoidal signals . Like in traditional control scheme, if the load currents are measured directly and a series of resonant controllers are tuned at high frequencies, we can achieve good current performance [4, 5]. There is a limitation of control bandwidth of PI controller due to which it is unable to regulate harmonic currents satisfactorily and the distortion [THD] is not within the standards. In order to achieve sufficient regulation of harmonic currents we must have
This paper purpose the procedure to estimate conity (λ), longitudinal creep coefficients (f11) also lateral creep coefficients (f22) . The Continuous- Time Recursive Least Absolute Error (C-T RLAE) with Variable Forgetting Factor (VFF) method to estimate solid axle wheelset parameter in Linear Quadratic Regulator (LQR) of two axle railway are presented. The Continuous- Time Recursive Least Absolute Error (C-T RLAE) with Variable Forgetting Factor (VFF) are used to overcome this bias problem. The Continuous Time Recursive Least Absolute Error (C-T RLAE) are designed for Linear time invariant (LTI) system but the Variable Forgetting Factor (VFF) are used for time varying system. The performance of Continuous Time Recursive Least Absolute Error (C-T RLAE) originally and Continuous- Time Recursive Least Absolute Error (C-T RLAE) with Variable Forgetting Factor (VFF) methods are compared. Linear Quadratic Regulator (LQR) was applying to stabilise wheelset traveling especially at high speeds wheelset parameters. Continuous- Time Recursive Least Absolute Error (C-T RLAE) with Variable Forgetting Factor (VFF) methods give good estimated of railway wheelset compared Continuous- Time Recursive Least Absolute Error (C-T RLAE). From this combination from (C-T RLAE) with (VFF) can reduce estimation bias.
In this type of optimal control method, controllers in this section are designed using linear H Synthesis . As is standard in the H framework, the performance objectives are achieved via minimizing weighted transfer function norms. Weighting functions serve two purposes in the H framework: They allow the direct comparison of differentperformance objectives with the same norm, and they allow for frequency information to be incorporated into the analysis. A block diagram of the H control design interconnection for the activesuspension problem is shown in Fig.11.
The 17-DOF railway vehicle model, MR damper model along with fuzzy bogie-based skyhook and fuzzy body-based skyhook have been developed and simulated in Matlab Simulink software. The sine wave track irregularity with the excitation frequencies of 1, 3 and 5 rad/sec has been considered in this study to observe the potential benefit of the proposed controller. The performance of the two semi-active controllers was compared with passive system in terms of the body lateral displacement, body roll angle and body yaw angle. From the simulation results, fuzzy bogie-based skyhook can outperform the passive system as well as the fuzzy body- based skyhook and is able to improve all three performance criterions, namely body lateral displacement, body roll angle and body yaw angle.
systems is typically rated by their ability to provide improved road handling and passenger comfort. Passenger comfort in ground vehicles depends on a combination of vertical and angular motions. The main objective of vehiclesuspensionsystem is to reduce the effect of the vibrations generated by road irregularities on the human body. The performance of vehiclesuspension systems is typically rated by their ability to provide improved road handling and passenger comfort. Activesuspensionsystem is the modern system which uses controlsystem for reducing unwanted oscillations of suspension systems. The existing system (using adaptive PID and sliding-mode-controller) used for reducing parameter variations and actuator faults in activesuspensionsystem have a main disadvantage is that, settling time of oscillations of suspensionsystem is very high. This problem reduces the performance of activevehiclesuspensionsystem. To avoid this, in proposed system, introduce fractional order PID and sliding-mode-controller. To analyze the performance of the proposed approach, computer simulations are carried out to illustrate controlperformance and robustness
Chapter 3 presents the methodology, modelling and validation of quarter car model. In this chapter, the mathematical equation of 2DOF quarter car model is introduced. Then, the mathematical model with quarter car is presented in order to validate the simulation results. The development of a validated quarter car model based on the mathematical quarter car is described. This chapter also presented the development of force tracking controlsystem. In this chapter, a mathematical formulation of MR damper dynamics is introduced. Then, the algorithm of force tracking controlsystem is formulated. Finally, the evaluation of force tracking controlperformance is discussed in terms of the tracking ability of the pneumatic force to the desired force.
1.1 Suspensionsystem: The suspensionsystem of an automobile helps to support the car body, engine and passengers, and at the same time absorbs shocks received from the ground while vehicle moves on rough roads and un even roads. The dynamic model of the suspension and steering system of the motor vehicles includes the kinematic elements - bodies (car body, axle, wheel carrier, guiding links), as well as the elastic and damping elements (ex. springs, dampers, bushings, antiroll bar, bumper and rebound elements) are very important to understand the behavior of the vehicle.. The increasingly growing demand for more comfortable passenger car imposes new models of the guiding systems, close to real systems on the vehicle. Suspension systems serve a dual purpose — contributing to the vehicle's road holding/handling and braking for good active safety and driving pleasure, and keeping vehicle occupants comfortable and a ride quality reasonably well isolated from road noise, bumps, and vibrations. A typical suspensionsystem is shown in the figure 1.
Abstract- The purpose of this paper is to construct an activesuspensioncontrol for a quarter car model subject to excitation from a road profile using an improved sliding mode control with an observer design. The sliding mode is chosen as a control strategy, and the road profile is estimated by using an observer design. The objective of a car suspensionsystem is to improve the riding quality without compromising the handling characteristic by directly controlling the suspension forces to suit the road and driving conditions. However, the mathematical model obtained suffers from few uncertainties. In order to achieve the desired ride comfort, road handling and to solve the uncertainties, a sliding mode control technique is presented. A nonlinear surface is used to ensure fast convergence of vehicle’s vertical velocity. The nonlinear surface changes the system’s damping. The effect of sliding surface selection in the proposed controller is also presented. Extensive simulations are performed and the results obtained shows that the proposed controller perform well in improving the ride comfort and road handling for the quarter car model using the hydraulically actuated suspensionsystem. The main motivation for designing an activesuspensionsystem is to improve the ride comfort by absorbing the shocks due to a rough and uneven road.
The need of suspension for vehicle is important due to safety aspect, ride comfort and good vehicle handling. Suspensionsystem has the facility to minimize vibration due to road roughness or uneven road profile because this suspensionsystem will seclude passenger from vibration and shocks arising from road roughness. Suspension comprises of the arrangement of springs, shock absorbers and linkages that link a vehicle to its wheels. The suspensionsystem also can secure the vehicle itself and any payload or luggage from damage and wear. There are two types of suspensionsystem which is passive suspension and activesuspension. A passive suspensionsystem store energy through spring and dissipate it by a damper because there is no energy supplied by the suspension component to the system. While, the ability of an activesuspensionsystem is to store, dissipate and to supply energy to the system because it has force actuator.
The simulation results for this disturbance are illustrated in Figures 10, 11, 12 and 13. As it is shown in these figures, the ANFIS system has better performance compared to passive system, fuzzy and LQR systems which can cause good handling for the vehicle. Also, the proposed system has significant reduction in control force as compared with LQR and fuzzy controllers. Figure 14 shows the body displacement for the first road disturbance with different magnitude. It is shown that the ANFIS controller allows a fast rise time and quick settling time without oscillatory behavior. Simulation show that the ANFIS controller givessuitable results for pulse and sinusoidal function road disturbances effectively, and hence it can be said that this controller could handle other real road situations.
actuator between the tire and the vehicle body. The system is capable to insert or remove energy through the efforts that are variable. The actuator requires sensors to measure the displacement and acceleration of the vehicle body and the tire, which are used as input signals. The force applied between the tire and the vehicle body does not only depend on relative displacement, but also on other variables, as example the position of the vehicle body and the tire and acceleration of the vehicle body. The semi-activesuspension is not capable to inject energy into the system, it is just capable to store or dissipate the energy of the system. Therefore, semi active suspensions are not able to achieve the same levels of comfort and stability of an activesuspension, but feature a higher robustness and lower cost than activesuspensionsystem. They are considered as a ―middle ground‖ between the active and passive suspension . The actuator is often a damper, which is generally constituted by electromechanical valves  or valves that use magneto rheological fluid (MR). In the literature, controllers used in semi-active suspensions are skyhook and fuzzy type combined with some optimal control (in this case semi-activesuspension with MR fluid) . Therefore, in this article is proposed the design a Takagi- Sugeno fuzzy (TS-F) skyhook, Mandani fuzzy (M-F) skyhook. All controllers were simulated and compared with each other.
Nowadays, the automotive suspension makes a design method based on the optimal controlstrategies. Sprung mass acceleration, suspension deflection and tire deflection are optimized by the suspensionsystem. the main components use to designing in suspensionsystem is a spring and parallel damper. All the components are placed together between the vehicle body and the wheels. Ride comfort as well as good handling is an important factor in designing the suspensionsystem.
ABSTRACT:This paper presents evaluation of effect of in-wheel electric motors mass on the performance of activesuspensionsystem by using one of more common control methods which is Linear Quadratic Regulator (LQR).Unsprung mass is one of the important parameters which effects on road holding and ride comfort behaviors in the vehicles, this effect obtained in this work by comparing the performance of the systemusing standard tire and tire with In-Wheel Electric Motor. Also,modeling and simulation of quarter car model completed to construct the Simulink model of the systemusing MATLAB software. The study summarized bad effect of increasing the weight of tires by add In-Wheel Motors to the system on the road traction and the vehicles drivers comfort, at the same time the suspensionsystem with in-wheel motor needs high actuator force to work compared to the same system without in- wheel motor
The suspensionsystem of a vehicle is one of the most important parts which is involved in the process of vehicle designing. When a vehiclesuspensionsystem is designed, the evaluation of its performance against the road disturbances such as shocks and bumps are very important. The most commonly used systems consist of four hydraulic Jacks with mobility in vertical line with low speed and low exactitude. This paper offers a new mechanism for inspecting the suspensionsystem of a vehicleusing a parallel robot called Stewart. This robot is a special kind of parallel robots with capability of movements in different directions with high speed, accuracy and repeatability. In this paper the suspensionsystem is evaluated on a quarter model of a simulated vehicle with control and guidance of Stewart robot using PID controller. The Stewart robot simulates the isolated and uneven bumps on a flat road in order to evaluate the given suspensionsystem, and to investigate some criteria such as comforting of the passengers and remaining of the vehicle on the road. The results of the simulations show that the proposed method has a high accuracy, applicability and flexibility as well as simplicity, compared to currently used mechanisms.
Meanwhile in activesystem, the component of spring or damper is replaced with an actuator. An actuator is controlled by using the feedback from the vehicle body. Technically, activesuspensionsystem is used to control the movement of a vehicleusing onboard controller by controlling the tire movement during cornering, braking and accelerating. The method of the controller for activesuspension can be divided into four types based upon the control techniques namely Solenoid Actuated, Hydraulic Actuated, Electromagnetic Recuperative and Magneto- rheological Damper.
The purpose of the report is to varying the effect of the toe and camber angle on the front wheel .Then, to determine the performance of the vehicle after the changes of the toe and camber angle. Moreover, it is intended to perform the conceptual design due to choose the best design for the report and to understand the operation and system of the Active Geometry Controlsuspension (AGCS).