In this paper semi-active control of the suspension of an all-terrain vehicle is considered. A seven degree of freedom suspension model is presented first. A fuzzy approach for controller synthesis is then proposed. Expert knowledge is stored in the form of IF-THEN rules. The Takagi-Sugeno inference system is employed, with triangle membership functions. The fuzzy system output is the damper coefficient. In contrary to many other control algorithms, the presented fuzzy algorithm does not require inverse modelling of the magnetorheological damper. Instead, some scaling parameters are set. They can be chosen experimentally, or a bio-inspired strategy can be applied. The fuzzy control is then compared with the Skyhook control in simulations, in terms of road holding and driving comfort indicators. Obtained results are similar. However, lack of necessity to use an MR inverse model allows the fuzzy system to provide successful performance in case of different operating conditions, what is an important benefit.

https://journals.sagepub.com/doi/pdf/10.1260/0263-0923.32.3.217

Fuzzy Control for Semi-Active Vehicle Suspension

This paper investigated the performance of PID controller for active suspension system. A half car model has been simulated by using an analytical model within Matlab SIMULINK environment. Three different road disturbances, namely, the bump and hole, sine and random input have been applied to disturb the suspension system. Based on these three road disturbances, the performances of passive and active suspension system were investigated. Moreover, for active suspension system, hydraulic actuator was included in the simulation and PID controller was introduced. Three tuning methods namely heuristic tuning, Ziegler-Nichols (ZN) tuning, and iterative learning algorithm (ILA) were used to obtain the optimum value of the PID controller parameters. A comparative study was carried out between active and passive suspension systems, and these three methods of tuning the PID controller. The active suspension system has been proven to perform better than the passive suspension system provided the PID controller parameters are tuned properly. Also, in this investigation, the comparative assessment indicated that the PID controller tuned by the iterative learning algorithm for active suspension system with hydraulic actuator has performed better than the other two tuning algorithms.

Self-tuning PID controller for active suspension system with hydraulic actuator

The control problems associated with vehicle height adjustment of electronically controlled air suspension (ECAS) still pose theoretical challenges for researchers, which manifest themselves in the publications on this subject over the last years. This paper deals with modeling and control of a vehicle height adjustment system for ECAS, which is an example of a hybrid dynamical system due to the coexistence and coupling of continuous variables and discrete events. A mixed logical dynamical (MLD) modeling approach is chosen for capturing enough details of the vehicle height adjustment process. The hybrid dynamic model is constructed on the basis of some assumptions and piecewise linear approximation for components nonlinearities. Then, the on-off statuses of solenoid valves and the piecewise approximation process are described by propositional logic, and the hybrid system is transformed into the set of linear mixed-integer equalities and inequalities, denoted as MLD model, automatically by HYSDEL. Using this model, a hybrid model predictive controller (HMPC) is tuned based on online mixed-integer quadratic optimization (MIQP). Two different scenarios are considered in the simulation, whose results verify the height adjustment effectiveness of the proposed approach. Explicit solutions of the controller are computed to control the vehicle height adjustment system in realtime using an offline multi-parametric programming technology (MPT), thus convert the controller into an equivalent explicit piecewise affine form. Finally, bench experiments for vehicle height lifting, holding and lowering procedures are conducted, which demonstrate that the HMPC can adjust the vehicle height by controlling the on-off statuses of solenoid valves directly. This research proposes a new modeling and control method for vehicle height adjustment of ECAS, which leads to a closed-loop system with favorable dynamical properties.

A hybrid approach to modeling and control of vehicle height for electronically controlled air suspension

Fuzzy logic control (FLC) algorithm grants a means of converting a linguistic control technique and it is widely used in vehicle applications. This paper demonstrates the application of fuzzy logic technique to design a controller for the active vehicle suspension system to improve the suspension system performance by altering the number and arrangement of the rules set and the universe of discourses. A mathematical model and equations of motion of quarter vehicle active suspension is derived and solved using MATLAB/Simulink software. The proposed fuzzy controllers using 9, 25 and 49 rules set with two different types of membership functions, trapezoidal and triangle, are implemented in a closed loop control system to demonstrate the influence of the numbers of rule set and the type of membership function on the performance of suspension system. Suspension performance criteria were assessed in both time and frequency domains. Performance comparisons between the passive suspension, as a reference, and the proposed controllers of the active suspension were achieved. The simulation results indicate that the proposed active fuzzy controllers can dissipate the energy due to road excitation effectively and improves suspension performance. Among the investigated systems, the 25 rules set with a trapezoidal membership function for the fuzzy controller gives the best performance.

Vibration Control of Active Vehicle Suspension System Using Fuzzy Logic Controller

The current research of air suspension mainly focuses on the characteristics and design of the air spring. In fact, electronically controlled air suspension (ECAS) has excellent performance in flexible height adjustment during different driving conditions. However, the nonlinearity of the ride height adjusting system and the uneven distribution of payload affect the control accuracy of ride height and the body attitude. Firstly, the three-point measurement system of three height sensors is used to establish the mathematical model of the ride height adjusting system. The decentralized control of ride height and the centralized control of body attitude are presented to design the ride height control system for ECAS. The exact feedback linearization method is adopted for the nonlinear mathematical model of the ride height system. Secondly, according to the hierarchical control theory, the variable structure control (VSC) technique is used to design a controller that is able to adjust the ride height for the quarter-vehicle anywhere, and each quarter-vehicle height control system is independent. Meanwhile, the three-point height signals obtained by three height sensors are tracked to calculate the body pitch and roll attitude over time, and then by calculating the deviation of pitch and roll and its rates, the height control correction is reassigned based on the fuzzy algorithm. Finally, to verify the effectiveness and performance of the proposed combined control strategy, a validating test of ride height control system with and without road disturbance is carried out. Testing results show that the height adjusting time of both lifting and lowering is over 5 s, and the pitch angle and the roll angle of body attitude are less than 0.15°. This research proposes a hierarchical control method that can guarantee the attitude stability, as well as satisfy the ride height tracking system.

Hierarchical control of ride height system for electronically controlled air suspension based on variable structure and fuzzy control theory

The existing researches of the evaluation method of ride comfort of vehicle mainly focus on the level of human feelings to vibration. The level of human feelings to vibration is influenced by many factors, however, the ride comfort according to the common principle of probability and statistics and simple binary logic is unable to reflect these uncertainties. The random fuzzy evaluation model from people subjective response to vibration is adopted in the paper, these uncertainties are analyzed from the angle of psychological physics. Discussing the traditional evaluation of ride comfort during vehicle vibration, a fuzzily random evaluation model on the basis of annoyance rate is proposed for the human body’s subjective response to vibration, with relevant fuzzy membership function and probability distribution given. A half-car four degrees of freedom suspension vibration model is described, subject to irregular excitations from the road surface, with the aid of software Matlab/Simulink. A new kind of evaluation method for ride comfort of vehicles is proposed in the paper, i.e., the annoyance rate evaluation method. The genetic algorithm and neural network control theory are used to control the system. Simulation results are obtained, such as the comparison of comfort reaction to vibration environments between before and after control, relationship of annoyance rate to vibration frequency and weighted acceleration, based on ISO 2631/1(1982), ISO 2631-1(1997) and annoyance rate evaluation method, respectively. Simulated assessment results indicate that the proposed active suspension systems prove to be effective in the vibration isolation of the suspension system, and the subjective response of human being can be promoted from very uncomfortable to a little uncomfortable. Furthermore, the novel evaluation method based on annoyance rate can further estimate quantitatively the number of passengers who feel discomfort due to vibration. A new analysis method of vehicle comfort is presented.

Annoyance rate evaluation method on ride comfort of vehicle suspension system

Quantum particle swarm optimization algorithm with the truncated mean stabilization strategy

sy presented for the control of an active suspension n is paper, a fuzzy logic control desig In this Abstract: is adopted, the road roughness intensity is modeled as a filtered white noise with seven degrees of freedom full vehicle model ss. Two cases of fuzzy logic control strategies are proposed. In the first case, one fuzzy controller is presented, stochastic proce he the dynamic travel of suspension and the derivation of dynamic travel of suspension are designed as the input variables. In t the heave movement controller, the pitch movement controller, the roll , namely , s are designed four controller second case, odels of full vehicle . With the aid of software Matlab/Simulink, the simulation m logical controller movement controller and the obtained for is odel due to road disturbance of the vehicle m nse s of controller are achieved. The time respo two case in model e each control strategy. Simulation results demonstrate that the proposed active suspension system proves to be effective in th ive stability enhancement of the suspension system. ride comfort and dr

/pdf/the-application-of-fuzzy-logic-control-algorithm-to-active-4e5x0qgjcc.pdf

The Application of Fuzzy Logic Control Algorithm to Active Suspensions of Vehicles

In this study, a fuzzy logic control design is represented for the control of an active suspension system. A seven degrees of freedom non linear full vehicle model is established, instead of two degrees of freedom one quarter model and four degrees of freedom half body model and the road roughness intensity is modeled as a white noise stochastic process. Then a fuzzy logic controller is designed for the control of the seven degrees of freedom full vehicle model, the input variables are the suspension displacement and the output variables are the control force. The time responses of the full vehicle model are obtained, not only the vertical body acceleration, but also the roll angular acceleration and pitch angular acceleration. Finally, uncontrolled and controlled cases are compared. With the aid of software Matlab/simulink, simulation process is done. Simulation results indicate that the proposed active suspension system proves to be effective in the vibration isolation of the suspension system both in ride comfort and in stability.

Yan Ma

Papers

Annoyance rate evaluation method on ride comfort of vehicle suspension system

Quantum particle swarm optimization algorithm with the truncated mean stabilization strategy

The Application of Fuzzy Logic Control Algorithm to Active Suspensions of Vehicles

The Application of Fuzzy Control Algorithm of Vehicle with Active Suspensions