An adaptive neuro fuzzy hybrid control strategy for a semiactive suspension with magneto rheological damper

The main function of a vehicle suspension system is to isolate the vehicle body from external excitation in order to improve passenger comfort and road holding and to stabilise its movement. This paper considers the implementation of an adaptive neuro fuzzy inference system (ANFIS) with a fuzzy hybrid control technique to control a quarter vehicle suspension system with a semiactive magneto rheological (MR) damper. A quarter car suspension model is set up with an MR damper and a semiactive controller consisting of a fuzzy hybrid skyhook-groundhook controller and an ANFIS model is also designed. The fuzzy hybrid controller is used to generate the desired control force, and the ANFIS is designed to model the inverse dynamics of MR damper in order to obtain a desired current. Finally, numerical simulations of the semiactive suspensions with the ANFIS- hybrid controller, the traditional hybrid controller, and passive suspension are compared. The results of simulations show that the proposed ANFIS-hybrid controller provides better isolation performance than the other controllers

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

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

Vibration control for an experimental off-road vehicle using magnetorheological dampers

The paper presents research studies in the field of semiactive vibration control of an experimental off-road vehicle which is equipped with suspension magnetorheological (MR) dampers. Accelerometers and vehicle progressive velocity sensors are installed in body and underbody parts of the vehicle and are used in control scheme. Furthermore, IMU modules and suspension deflection sensors were used for validation of measurement part of the system. Semiactive Skyhook control algorithm, including on/off and smooth suspension MR damper control, was implemented in order to validate the control system. Quality of measurements is deteriorated by multiple factors including vehicle engine and shape of tires which was examined. Experimental results indicated better vibration suppression of vehicle body part for smooth Skyhook controller compared with passive soft and hard suspension. The presented semiactive suspension control system can be applied for complex vehicle dynamics analysis and control schemes dedicated to both the ride comfort and ride safety issues

Advanced suspension system using magnetorheological technology for vehicle vibration control

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

Adaptive vibration control of a nonlinear quarter car model with an electromagnetic active suspension

The main goal of the active suspension system used in a vehicle is reducing the vehicle vibration. In this study, an adaptive control approach is applied to a nonlinear quarter car model with an active suspension system. An electromagnetic actuator is used in the active suspension system. The attractive aspect of the applied control method is not required to both vehicle parameters and actuator parameters. Using Lyapunov based stability analysis; it is shown that all the signals in the closed loop system are bounded. Hence, the applied controller ensures the vibration reduction of the nonlinear quarter car model. The simulation results show that the applied adaptive controller provide a good ride comfort despite the parametric uncertainties while keeping suspension travel and tire deflection in acceptable limits

Feasibility of Using Nonlinear Time-Frequency Control for Magnetorheological Dampers in Vehicle Suspension

Semi-active vehicle suspensions that use magnetorheological (MR) dampers are able to better dissipate vibrations compared to conventional dampers because of their controllable damping characteristics. The performance of current MR damper control methods is often hindered by incorrect assumptions and linearized models. Therefore, a need exists to design an adaptive controller with improved accuracy and reliability. The objective of this research is to design an improved controller for MR dampers in vehicle suspension using the nonlinear time-frequency control approach and evaluate its feasibility by numerically employing MATLAB Simulink. Simulations in this research are performed using a simplified quarter car suspension model and modified Bouc-Wen damper model. The proposed control method is evaluated based on its ability to reduce the amplitude of vibrations and minimize acceleration of the car body for various test cases. Simulations are also performed using the skyhook controller and passive suspension to assess the performance of the proposed controller. The results of the simulations show that the proposed nonlinear time-frequency controller can successfully be applied to an MR damper suspensions system for vibration control. The proposed controller outperforms the skyhook controller in terms of reducing acceleration of the car body in each of the tested scenarios. The proposed controller also shows the ability to more efficiently manage the current input to the system. In general, the skyhook controller gives more improved vibration amplitude responses but is prone to generate large spikes in car body acceleration at higher frequency road profile inputs. Simulations performed with the passive system show large displacement amplitudes and inability to prevent oscillation. The feed-forward aspect and adaptive nature of the proposed controller gives it the ability to better compensate for the time-delay in the operation of the MR damper. The proposed controller shows sensitivity to controller parameters when pursuing the best response for different road profile input cases

A Deep Reinforcement Learning-Based Controller for Magnetorheological-Damped Vehicle Suspension

This paper proposes a novel approach to controller design for MR-damped vehicle suspension system. This approach is predicated on the premise that the optimal control strategy can be learned through real-world or simulated experiments utilizing a reinforcement learning algorithm with continuous states/actions. The sensor data is fed into a Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which generates the actuation voltage required for the MR damper. The resulting suspension space (displacement), sprung mass acceleration, and dynamic tire load are calculated using a quarter vehicle model incorporating the modified Bouc-Wen MR damper model. Deep RL's reward function is based on sprung mass acceleration. The proposed approach outperforms traditional suspension control strategies regarding ride comfort and stability, as demonstrated by multiple simulated experimentsComment: 19 pages , 9 figures , 5 table

Innovative magnetorheological devices for shock and vibration mitigation

Vibration and impact protection have been a popular topic in research fields, which could directly affect the passengers’ and drivers’ comfort and safety, even cause spines fracture. Therefore, an increasing number of vehicle suspensions and aircraft landing gears are proposed and manufactured. Magnetorheological fluids (MRFs), as a smart material, are growly applied into the above device owing to its unique properties such as fast response, reversible properties, and broad controllable range, which could improve the vibration/impact mitigation performance. MRF was utilized to achieve adaptive parameters of the vehicle suspensions by controlling the magnetic field strength of the MRF working areas. Generally, the magnetic field is provided by a given current, subsequently, it would consume massive energy from a long-term perspective. Thus, a self-powered concept was applied as well. This thesis reports a compact stiffness controllable MR damper with a self-powered capacity. After the prototype of the MR damper, its property tests were conducted to verify the stiffness controllability and the energy generating ability using a hydraulic Instron test system. Then, a quarter-car test rig was built, and the semi-active MR suspension integrated with the self-powered MR damper was installed on a test rig. Two controllers, one based on short-time Fourier transform (STFT) and a classical skyhook controller was developed to control the stiffness. The evaluation results demonstrate that the proposed MR damper incorporated with STFT controller or skyhook controller could suppress the response displacements and accelerations obviously comparing with the conventional passive systems