Study on Control Technology for Vehicle Active Suspension

2011 ◽  
Vol 143-144 ◽  
pp. 69-73
Author(s):  
Xiao Bin Fan ◽  
Bing Xu Fan ◽  
Hui Gang Wang
Keyword(s):  
Pid Control ◽  
Ride Comfort ◽  
Design Method ◽  
Control Design ◽  
Active Suspension ◽  
Fuzzy Pid ◽  
Linear Quadratic ◽  
Fuzzy Pid Control ◽  
Suspension Control ◽  
Lqg Control

An active suspension system has been proposed to improve the ride comfort. A quarter-car 2 degree-of-freedom system is designed and constructed on the basis of the concept of a four-wheel independent suspension. The aim of the work described in the paper was to illustrate the application of fuzzy Proportional Integration Derivative (PID) technique and Linear Quadratic Guass (LQG) control to the active suspension control system. The paper describes also the model and controller used in the study and discusses the vehicle response results obtained from a range of road input simulations. This work describes some comparison of active suspension fuzzy PID control and LQG control design method by MATLAB simulations. Simulation results show that the LQG controller achieved better performances in all carried-out investigations.

Control analysis of vehicle ride comfort through integrated control devices on the quarter and half car active suspension systems

2020 ◽  
pp. 095440702096830
Author(s):  
Sharifah Munawwarah ◽  
Fitri Yakub
Keyword(s):  
Pid Control ◽  
Ride Comfort ◽  
Integrated Control ◽  
Active Suspension ◽  
Control Analysis ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Handling Performance ◽  
Suspension Systems ◽  
Active Suspension Systems

This study proposed an integrated chassis control of the quarter car and half car active suspension systems to enhance vehicle ride comfort and road handling performance. The integrated controls of PID-LQR and Fuzzy-PID were designed to maximize driving comfort by keeping the vehicle wheels in contact with the road surface. The PID control which is commonly used in car manufacturing was set as a controller benchmark. Multiple road conditions such as speed bumps of different heights, 0.1 m < h < 0.3 m and widths, 0.3 m < d < 0.5 m were used in the system for analysis. In comparison with PID-LQR, Fuzzy-PID showed the lowest peak amplitude and reached the stability state in a minimum time against the controller benchmark. This indicates that vehicle ride comfort and road handling performance can be optimized using the proposed Fuzzy-PID control.

Intelligent Information of TS Fuzzy PID Control System of BLDCM

2013 ◽  
Vol 846-847 ◽  
pp. 313-316 ◽  
Author(s):  
Xiao Yun Zhang
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Pid Control ◽  
Control Method ◽  
Design Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Precision ◽  
Simulation Results ◽  
Intelligent Information

This paper presented a new method based on the Fuzzy self - adaptive PID for BLDCM. This method overcomes some defects of the traditional PID control. Such as lower control precision and worse anti - jamming performance. It dynamic model of BLDCM was built, and then design method for TS fuzzy PID model is given, At last, it compared simulation results of PID control method with TS Fuzzy PID control method. The results show that the TS Fuzzy PID control method has more excellent dynamic antistatic performances, as well as anti-jamming performance. The experiment shows that TS fuzzy PID control has the stronger adaptability robustness and transplant.

scholarly journals Design of and Research into a Multiple-Fuzzy PID Suspension Control System Based on Road Recognition

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2190
Author(s):  
Xinkai Ding ◽  
Ruichuan Li ◽  
Yi Cheng ◽  
Qi Liu ◽  
Jilu Liu
Keyword(s):  
Control System ◽  
Pid Control ◽  
Good Control ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
The Road ◽  
Suspension Control ◽  
Neural Network Algorithm ◽  
Road Grade ◽  
Differential Control

By analyzing the shortcomings of the traditional fuzzy PID(Abbreviation for Proportional, Integral and Differential) control system (FPID), a multiple fuzzy PID suspension control system based on road recognition (MFRR) is proposed. Compared with the traditional fuzzy PID control system, the multiple fuzzy control system can identify the road grade and take changes in road conditions into account. Based on changes in road conditions and the variable universe and secondary adjustment of the control parameters of the PID controller were carried out, which makes up for the disadvantage of having too many single input parameters in the traditional fuzzy PID control system. A two degree of freedom 1/4 vehicle model was established. Based on the suspension dynamic parameters, a road elevation algorithm was designed. Road grade recognition was carried out based on a BP neural network algorithm. The experimental results showed that the sprung mass acceleration (SMA) of the MFRR was much smaller than that of the passive suspension system (PS) and the FPID on single-bump and sinusoidal roads. The SMA, suspension dynamic deflection (SDD) and tire dynamic load (TDL) of the MFRR were significantly less than those of the other two systems on roads of each grade. Taking grade B road as an example, compared with the PS, the reductions in the SMA, SDD and TDL of the MFRR were 40.01%, 34.28% and 32.64%, respectively. The control system showed a good control performance.

scholarly journals Design of Static Output Feedback and Structured Controllers for Active Suspension with Quarter-Car Model

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8231
Author(s):  
Manbok Park ◽  
Seongjin Yim
Keyword(s):  
Output Feedback ◽  
Ride Comfort ◽  
Linear Quadratic Regulator ◽  
Active Suspension ◽  
Static Output Feedback ◽  
State Variables ◽  
Linear Quadratic ◽  
Suspension Control ◽  
Quarter Car ◽  
Static Output

This paper presents a method to design active suspension controllers for a 7-Degree-of-Freedom (DOF) full-car (FC) model from controllers designed with a 2-DOF quarter-car (QC) one. A linear quadratic regulator (LQR) with 7-DOF FC model has been widely used for active suspension control. However, it is too hard to implement the LQR in real vehicles because it requires so many state variables to be precisely measured and has so many elements to be implemented in the gain matrix of the LQR. To cope with the problem, a 2-DOF QC model describing vertical motions of sprung and unsprung masses is adopted for controller design. LQR designed with the QC model has a simpler structure and much smaller number of gain elements than that designed with the FC one. In this paper, several controllers for the FC model are derived from LQR designed with the QC model. These controllers can give equivalent or better performance than that designed with the FC model in terms of ride comfort. In order to use available sensor signals instead of using full-state feedback for active suspension control, LQ static output feedback (SOF) and linear quadratic Gaussian (LQG) controllers are designed with the QC model. From these controllers, observer-based controllers for the FC model are also derived. To verify the performance of the controllers for the FC model derived from LQR and LQ SOF ones designed with the QC model, frequency domain analysis is undertaken. From the analysis, it is confirmed that the controllers for the FC model derived from LQ and LQ SOF ones designed with the QC model can give equivalent performance to those designed with the FC one in terms of ride comfort.

Based on Single Neuron PID Control of Vehicle Active Suspension System

2013 ◽  
Vol 380-384 ◽  
pp. 528-531 ◽  
Author(s):  
Xiao Feng Liu ◽  
Xin Hua Xie
Keyword(s):  
Control Strategy ◽  
Pid Control ◽  
Single Neuron ◽  
Ride Comfort ◽  
Control Strategies ◽  
Active Suspension ◽  
Vital Role ◽  
Suspension System ◽  
Suspension Control ◽  
Single Neuron Pid

Relative to the passive suspension, automotive active suspension car driving more ride comfort and stability, has a vital role to further improve the performance of the vehicle. For such a typically complex active suspension system research, the key issue is the selection of control strategies. The problems in the currently active suspension control strategy, the principle of a simple, effective, this paper, a single neuron PID control strategy used in the automotive active suspension system. The results show that compared with other control strategies, single neuron PID control strategy is reliable, has more advantages.

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