38 research outputs found

    State of the art of control schemes for smart systems featuring magneto-rheological materials

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    This review presents various control strategies for application systems utilizing smart magneto-rheological fluid (MRF) and magneto-rheological elastomers (MRE). It is well known that both MRF and MRE are actively studied and applied to many practical systems such as vehicle dampers. The mandatory requirements for successful applications of MRF and MRE include several factors: advanced material properties, optimal mechanisms, suitable modeling, and appropriate control schemes. Among these requirements, the use of an appropriate control scheme is a crucial factor since it is the final action stage of the application systems to achieve the desired output responses. There are numerous different control strategies which have been applied to many different application systems of MRF and MRE, summarized in this review. In the literature review, advantages and disadvantages of each control scheme are discussed so that potential researchers can develop more effective strategies to achieve higher control performance of many application systems utilizing magneto-rheological materials

    Global Chassis Control System Using Suspension, Steering, and Braking Subsystems

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    A novel Global Chassis Control (GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation

    Intelligent controllers for vechicle suspension system using magnetorheological damper

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    Semi-active suspension control with magnetorheological (MR) damper is one of the most fascinating systems being studied in improving the vehicle ride comfort. This study aims to investigate the development of intelligent controllers for vehicle suspension system using MR damper, namely, the proportional-integral-derivative (PID) and fuzzy logic (FL) controllers optimized using particle swarm optimization (PSO), firefly algorithm (FA) and advanced firefly algorithm (AFA). Since the conventional optimization method always has a problem in identifying the optimum values and it is time consuming, the evolutionary algorithm is the best approach in replacing the conventional method as it is very efficient and consistent in exploring the values for every single space. The PSO and FA are among of the evolutionary algorithms which have been studied in this research. Nevertheless, the weakness of FA such as getting trapped into several local minima is an attractive area that has been focused more as a possible improvement during the evolutionary process. Thus, a new algorithm based on the improvement of the original FA was introduced to improve the solution quality of the FA. This algorithm is called advanced firefly algorithm. A parametric modelling technique known as Spencer model was proposed and employed to compute the dynamic behaviour of the MR damper system. The Spencer model was experimentally validated and conducted to capture the behaviour of the Lord RD-1005-3 MR damper with the same excitation input. A simulation of a semi-active suspension system was developed within MATLAB Simulink environment. The effectiveness of all control schemes were investigated in two major issues, namely the ability of the controller to reject the unwanted motion of the vehicle and to overcome the damping constraints. The result indicates that, the PID-AFA control scheme is more superior as compared to the PID-PSO, PID-FA, FL-PSO, FL-FA, FL-AFA and passive system with up to 27.1% and 19.1% reduction for sprung mass acceleration and sprung mass displacement, respectively. Finally, the performance of the proposed intelligent control schemes which are implemented experimentally on the developed quarter vehicle suspension test rig shows a good agreement with the results of the simulation study. The proposed control scheme of PID-AFA has reduced the sprung mass acceleration and sprung mass displacement over the FL-AFA and passive system up to 28.21% and 16.9%, respectively

    State and parameter estimator design for control of vehicle suspension system

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    Modern vehicle stability and navigational systems are mostly designed using inaccurate bicycle models to approximate the full-car models. This results in incomplete models with various unknown parameters and states being neglected in the controller and navigation system design processes. Earlier estimation algorithms using the bicycle models are simpler but have many undefined parameters and states that are crucial for proper stability control. For existing vehicle navigation systems, direct line of sight for satellite access is required but is limited in modern cities with many high-rise buildings and therefore, an inertial navigation system utilizing accurate estimation of these parameters is needed. The aim of this research is to estimate the parameters and states of the vehicle more accurately using a multivariable and complex full-car model. This will enhance the stability of the vehicle and can provide a more consistent navigation. The proposed method uses the kinematics estimation model formulated using special orthogonal SO3 group to design estimators for vehicles velocity, attitude and suspension states. These estimators are used to modify the existing antilock braking system (ABS) scheme by incorporating the dynamic velocity estimation to reduce the stopping distance. Meanwhile the semi-active suspension system includes suspension velocity and displacement states to reduce the suspension displacements and velocities. They are also used in the direct yaw control (DYC) scheme to include mass and attitude changes to reduce the lateral velocity and slips. Meanwhile in the navigation system, the 3-dimensional attitude effects can improve the position accuracy. With these approaches, the stopping distance in the ABS has been reduced by one meter and the vehicle states required for inertial navigation are more accurately estimated. The results for high speed lane change test indicate that the vehicle is 34% more stable and 16% better ride comfort on rough terrains due to the proposed DYC and the active suspension system control. The methods proposed can be utilized in future autonomous car design. This research is therefore an important contribution in shaping the future of vehicle driving, comfort and stability

    Optimal design of a quadratic parameter varying vehicle suspension system using contrast-based Fruit Fly Optimisation

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    In the UK, in 2014 almost fifty thousand motorists made claims about vehicle damages caused by potholes. Pothole damage mitigation has become so important that a number of car manufacturers have officially designated it as one of their priorities. The objective is to improve suspension shock performance without degrading road holding and ride comfort. In this study, it is shown that significant improvement in performance is achieved if a clipped quadratic parameter varying suspension is employed. Optimal design of the proposed system is challenging because of the multiple local minima causing global optimisation algorithms to get trapped at local minima, located far from the optimum solution. To this end an enhanced Fruit Fly Optimisation Algorithm − based on a recent study on how well a fruit fly’s tiny brain finds food − was developed. The new algorithm is first evaluated using standard and nonstandard benchmark tests and then applied to the computationally expensive suspension design problem. The proposed algorithm is simple to use, robust and well suited for the solution of highly nonlinear problems. For the suspension design problem new insight is gained, leading to optimum damping profiles as a function of excitation level and rattle space velocity

    Advanced suspension system using magnetorheological technology for vehicle vibration control

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    In the past forty years, the concept of controllable vehicle suspension has attracted extensive attention. Since high price of an active suspension system and deficiencies on a passive suspension, researchers pay a lot attention to semi-active suspension. Magneto-rheological fluid (MRF) is always an ideal material of semi-active structure. Thanks to its outstanding features like large yield stress, fast response time, low energy consumption and significant rheological effect. MR damper gradually becomes a preferred component of semi-active suspension for improving the riding performance of vehicle. However, because of the inherent nonlinear nature of MR damper, one of the challenging aspects of utilizing MR dampers to achieve high levels of performance is the development of an appropriate control strategy that can take advantage of the unique characteristics of MR dampers. This is why this project has studied semi-active MR control technology of vehicle suspensions to improve their performance. Focusing on MR semi-active suspension, the aim of this thesis sought to develop system structure and semi-active control strategy to give a vehicle opportunity to have a better performance on riding comfort. The issues of vibration control of the vehicle suspension were systematically analysed in this project. As a part of this research, a quarter-car test rig was built; the models of suspension and MR damper were established; the optimization work of mechanical structure and controller parameters was conducted to further improve the system performance; an optimized MR damper (OMRD) for a vehicle suspension was designed, fabricated, and tested. To utilize OMRD to achieve higher level of performance, an appropriate semi-active control algorithm, state observer-based Takagi-Sugeno fuzzy controller (SOTSFC), was designed for the semi-active suspension system, and its feasibility was verified through an experiment. Several tests were conducted on the quarter-car suspension to investigate the real effect of this semiactive control by changing suspension damping. In order to further enhance the vibration reduction performance of the vehicle, a fullsize variable stiffness and variable damping (VSVD) suspension was further designed, fabricated, and tested in this project. The suspension can be easily installed into a vehicle suspension system without any change to the original configuration. A new 3- degree of freedom (DOF) phenomenological model to further accurately describe the dynamic characteristic of the VSVD suspension was also presented. Based on a simple on-off controller, the performance of the variable stiffness and damping suspension was verified numerically. In addition, an innovative TS fuzzy modelling based VSVD controller was designed. The TS fuzzy modelling controller includes a skyhook damping control module and a state observer based stiffness control module which considering road dominant frequency in real-time. The performance evaluation of the VSVD control algorithm was based on the quarter-car test rig which equipping the VSVD suspension. The experiment results showed that this strategy increases riding comfort effectively, especially under off-road working condition. The semi-active control system developed in this thesis can be adapted and used on a vehicle suspension in order to better control vibration

    A Comparison of Type-1 and Type-2 Fuzzy Logic Controllers in Robotics: A review

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    Most real world applications face high levels of uncertainties that can affect the operations of such applications. Hence, there is a need to develop different approaches that can handle the available uncertainties and reduce their effects on the given application. To date, Type-1 Fuzzy Logic Controllers (FLCs) have been applied with great success to many different real world applications. The traditional type-1 FLC which uses crisp type-1 fuzzy sets cannot handle high levels of uncertainties appropriately. Nevertheless it has been shown that a type-2 FLC using type-2 fuzzy sets can handle such uncertainties better and thus produce a better performance. As such, type-2 FLCs are considered to have the potential to overcome the limitations of type-1 FLCs and produce a new generation of fuzzy controllers with improved performance for many applications which require handling high levels of uncertainty. This paper will briefly introduce the interval type-2 FLC and its benefits. We will also present briefly some of the type-2 FLC real world applications

    Vibration isolation under isolator-structure interaction

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    This thesis analyses a general case of the vibration isolation (VI) problem, considering both a rigid and non-rigid supporting structures. The aim is to study changes on the behaviour of both systems isolators and supporting structure when the interaction phenomenon between them is considered. The influence of the VI task on the base response is evaluated. In addition, the effect of the base dynamics on the the VI and alignment problem is studied. The novel contribution to the knowledge of this thesis is formulation of a novel VI approach, which facilitates a holistic analysis of the problem considering all the systems involved on it. This approach is valid for any number of isolators and for any type of base structure. Moreover, different control objectives can be easily defined; evaluation of the interaction phenomenon on both the platform and base response for different VI techniques; demonstration of the importance of the isolator damping ratio on the influence that the VI task has on the base response; evaluation of the effects of the supporting structure dynamics on the VI and alignment problem when multiple isolators are involved; analysis of the Multiple-Input-Multiple-Ouput (MIMO) control strategy by comparison with the Single-Input-Single-Output (SISO) control strategy. This comparative has been made for the VI and alignment problem of multiple isolators on a non-rigid supporting structure and includes analysis of the effectiveness of the Coral Reefs Optimization algorithms to find nearly-optimal control gains in VI and alignment problems. Through the investigation made for this thesis, a number of significant results have been reached, which show the importance of the supporting structure dynamics on the VI and alignment task. Moreover, the interaction phenomenon, and its consequence on the base response, has been investigated experimentally. The results derived from this thesis conclude that, for most scenarios, the dynamics of the base affects the VI task. Also, the active VI (AVI) technique shows a greater influence on the base response than passive VI (PVI) technique, for most cases. It has been observed that the use of AVI technique can additionally be oriented to control vibrations of the supporting structure, while the VI task is developed. Significant differences have been found when multiple isolators are involved in the same task for the alignment and VI problem, depending on whether or not the dynamics of the base are considered. The best set of control gains for the rigid-support case (which lead to maximum damping ratio) differ from those obtained when the supporting structure is considered as a flexible system, for different cases analysed in this thesis. The MIMO control strategy has shown great improvement with respect to the use of the SISO control strategy. Also, the Coral Reefs Optimization algorithms have been demonstrated to be a suitable tool to find nearly-optimal solutions for this type of problems
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