Singularity-Free Adaptive Controller for Uncertain Hysteresis Suspension Using Magnetorheological Elastomer-Based Absorber

The magnetorheological elastomer (MRE) is a smart material widely used in recent vibration systems. A system using these materials often faces difficulties designing the controller such as unknown parameters, hysteresis state, and input constraints. First, a model is designed for the MRE-based absorber to portray the behavior of MRE and predict the appropriate electric current supplied. The conventional adaptive controller often suffers from so-called control singularities. The singularity-free adaptive controller is proposed to eliminate the singularity with parametric uncertainty. The proposed controller consists of four components: an adaptive linearizing controller, a deputy adaptive neural network controller, an auxiliary part designed for the controller to overcome the input constraint problem, and a smooth switching algorithm used to exchange the takeover rights of the two controllers. Moreover, the controller is designed to obtain the stabilization of hysteretic state estimation for the vibration system. The adaptive algorithms are proposed to update the unknown system parameters and to observe the unmeasurable hysteretic state. Meanwhile, closed-loop system stability is comprehensively assessed. Finally, the simulation performed on a quarter-car suspension with an MRE-based absorber shows the proposed controller's efficiency.

Observer-Based Fault-Tolerant Predictive Control for LPV Systems with Sensor Faults: An Active Car Suspension Application

In this paper, an observer-based robust fault-tolerant predictive control (ORFTPC) strategy is proposed for Linear Parameter-Varying (LPV) systems subject to input constraints and sensor failures. The main objective of this work is to establish a real observer based on a virtual observer to be used to estimate both states and sensor failures of the system. The proposed virtual observer is employed to improve the observation precision and reduce the impacts of the sensor faults and the external disturbances in the LPV systems. In addition, a real observer is proposed to overcome the virtual observer margins and to ensure that all states and sensor faults of the system are properly estimated, without the need for any fault isolation modules. The proposed solution demonstrates that, using both observers, a robust fault-tolerant predictive control is established via the Lyapunov function. Moreover, sufficient stability conditions are derived using the Lyapunov approach for the convergence of the proposed robust controller. Furthermore, the proposed approach simultaneously computes the gains of the real observer and the controller from a linear matrix inequality (LMI), which is deduced from the estimation errors. Finally, the performance of the proposed approach is investigated by a simulation example of a quarter-vehicle model, and the simulation results under a sensor fault illustrate the robustness and performance of the proposed method.

Hybrid Sliding Mode Control of Full-Car Semi-Active Suspension Systems

With the advance in technology in driving vehicles, there is currently more emphasis on developing advanced control systems for better road handling stability and ride comfort. However, one of the challenging problems in the design and implementation of intelligent suspension systems is that there is currently no solution supporting the export of generic suspension models and control components for integration into embedded Electronic Control Units (ECUs). This significantly limits the usage of embedded suspension components in automotive production code software as it requires very high efforts in implementation, manual testing, and fulfilling coding requirements. This paper introduces a new dynamic model of full-car suspension system with semi-active suspension behavior and provides a hybrid sliding mode approach for control of full-car suspension dynamics such that the road handling stability and ride comfort characteristics are ensured. The semi-active suspension model and the hybrid sliding mode controller are implemented as Functional Mock-Up Units (FMUs) conforming to the Functional Mock-Up Interface for embedded systems (eFMI) and are calibrated with a set experimental tests using a 1/5 Soben-car test bench. The methods and prototype implementation proposed in this paper allow both model and controller re-usability and provide a generic way of integrating models and control software into embedded ECUs.

Kinematic model of the suspension of an electric car

The purpose of the work considered in this article is to develop approaches and methods for designing an electric vehicle from the concept phase to production based on the use of digital simulation. In this study, calculations were performed using the calculation of the kinematic model of the electric car suspension and CAE. Based on the results of the calculations and their compliance with the matrix of targets and resource constraints, the geometry of the suspension parts was changed during the study. For each of the iterations of the geometry, the types and materials were selected for the subsequent production of electric car suspension parts. The application of the above-mentioned approach from the earliest stages of work allowed us not only to achieve the required criteria for the mechanical characteristics of the structure, but also to comply with the conditions for reducing the development time, the cost of production and improving its quality.

Analisis Pengaturan Quarter-Car Active Suspension Menggunakan Neuro-Fuzzy Adaptif PID Control

Car as a vehicle has a suspension on the wheels that connect the body with the road surface. The suspension is arranged in such way as to ensure the comfort in driving even on uneven road surfaces or damaged road surfaces. Because of the changes in road surface, it is very important to make adjustments to the suspension. The car suspension is adjusted using Neuro-Fuzzy Adaptive PID Control System so that the performance of the suspension can be improved in ensuring user comfort by reducing vibrations in the car body. Improved performance can be seen in the results of the suspension setting, which can suppress the movement of the car body because of the change in road surface more than 80%.

A Methodology to Investigate Powered Two-Wheeler Rider’s Comfort over Road Sections with Skew Superelevation

The proper surface water drainage not only affects vehicle movement dynamics but also increases the likelihood of an accident since inadequate drainage is associated with potential hydroplaning and splash and spray driving conditions. Nine solutions have been proposed to address hydroplaning in sections with inadequate drainage e.g. augmented superelevation and longitudinal slope, reduction of runoff length, and skew superelevation. The latter has been extensively implemented in highways recently, enhancing the safety level in the applied road segments regarding the effective drainage of the rainwater. However, the concept of the skew superelevation has raised concerns regarding the level of driver’s comfort when traveling over skew superelevation sections particularly with high speeds. These concerns were alleviated through the concept of the round-up skew superelevation which reduces both the lateral and the vertical acceleration imposed on the drivers and hence, improves comfort and traffic safety. The present study investigates the behaviour of power two-wheeler riders since they are susceptible to any changes on the pavement surface and therefore a comparison between the traditional superelevation practice and the skew superelevation concept is of paramount importance. The methodology is based on the utilization of sophisticated software to design the model of the road for several values of longitudinal slopes. Based on the values of the slopes and the use of mathematical equations, the accelerations imposed on the wheel of the motorcycle were calculated. Since the final aim of the study is the influence of the skew superelevation to the rider, it was deemed necessary to convey the calculated accelerations from the wheel to the rider. That was accomplished by implementing the quarter car suspension model adjusted to the features of two-wheeler vehicles. Finally, the accelerations derived from this process evaluated according to specific thresholds based on the literature which correspond to certain levels of comfort. The most important conclusion drawn is that the comfort of the riders is not dependent to a great extent on the form of the road gradient because the vertical acceleration imposed on the riders took similar values regardless of the value of the longitudinal slope.

Optimal Speed Control Humps Design Based on Driver Comfort

The purpose of this study is to optimise the different speed control humps by considering the vertical and horizontal acceleration of the driver’s head. In previous researches, the main focus was only on vertical acceleration, but in this study, horizontal acceleration of the head is also considered. Here, the root mean square (RMS) of acceleration of head is considered as a measure of occupant comfort. The modelling is performed by a non-linear half-car suspension system (4-DOF) with a linear model of a driver (10-DOF) and a seat. The hamps under study are circular, sinusoidal, half-sinusoidal, and trapezoidal. Finally, by analysing the results, the optimal design of each type of hump is performed. The objective function used is a combination of horizontal and vertical acceleration which is performed using MATLAB genetic algorithm. The results show a significant reduction in horizontal and vertical acceleration at all speeds. From this modelling, it is possible to extract a suitable range for passing the speed of cars over different types of humps. In this study, it is shown that the acceleration values for the circular and half-sinusoidal humps at all speeds are quite close to each other.