Kai Zhao

Bio: Kai Zhao is an academic researcher from Beijing Institute of Technology. The author has contributed to research in topics: Suspension (vehicle) & Active suspension. The author has an hindex of 1, co-authored 1 publications receiving 4 citations.

Adaptive neural network sliding mode control for active suspension systems with electrohydraulic actuator dynamics

Abstract: The object of this article is to design an observer-based adaptive neural network sliding mode controller for active suspension systems. A general nonlinear suspension model is established, and the...

A Novel Sliding Mode Control Algorithm for an Active Suspension System Considering with the Hydraulic Actuator

Abstract: The suspension system has the role of regulating and extinguishing oscillations in the vehicle. To improve stability and comfort, the active suspension system is proposed to replace the passive suspension system. There are many algorithms used for active suspension system control, such as PID, LQR, Fuzzy, etc. Among them, the nonlinear control method which uses the SMC algorithm gives a stable performance. This research proposes the use of the SMC algorithm to control the operation of the active suspension system equipped with a quarter dynamics model. The process of linearization of the hydraulic actuator is presented in the paper. As a result of the simulation, the values of displacement and acceleration of the sprung mass were significantly reduced when the vehicle used the active suspension system controlled by the SMC algorithm. The SMC controller established in this paper provides stability in many situations. Therefore, the vehicle's smoothness and comfort have been significantly improved. In the future, intelligent algorithms can be combined with SMC algorithms to improve the efficiency of the controller.

A Novel Hybrid Control Algorithm Sliding Mode-PID for the Active Suspension System with State Multivariable

Abstract: This paper introduces a novel method to control the operation of the active suspension system. In this research, a quarter-dynamic model is used to simulate the vehicle’s vibrations. Besides, the sliding mode-PID-integrated algorithm with five state variables is proposed to be used. This is a completely original and novel algorithm. The process of establishing the control algorithm is clearly described. The simulation is performed by the MATLAB software. The results of the paper have shown the advantages of the sliding mode-PID algorithm used in this research. Accordingly, the displacement and acceleration of the sprung mass were significantly reduced when this algorithm was used. The maximum and average values of the displacement of the sprung mass are only 1.31% and 1.29%, respectively, compared with the situation of the vehicle using a passive suspension. Similarly, the value of the acceleration is 6.98% and 2.94%, respectively. In addition, the phenomenon of “chattering” has also been significantly reduced when using this controller. In the future, some more complex algorithms can be proposed.

Application of MIMO Control Algorithm for Active Suspension System: A New Model with 5 State Variables

Abstract: This paper introduces the LQR control algorithm for the active suspension system. Because the model of the vehicle dynamics used in this paper includes a hydraulic actuator, therefore, this model will include five state variables. Besides, the process of linearization of the hydraulic actuator is also shown in this paper. This is a completely novel and original method. It is possible to describe almost all the characteristics of hydraulic actuators with just one linear differential equation. Also, the parameters of the LQR controller are optimized through the in-loop optimization algorithm. The results of the research showed that the values of displacement and acceleration of the sprung mass were significantly reduced when this algorithm was used. In the investigation cases, these values usually do not exceed 2.68% and 43.00% compared to the situation of the vehicle using only a passive suspension system. Therefore, ride comfort and stability can be enhanced in many driving conditions when the active suspension system with the LQR control algorithm is used.

Fuzzy Multiple Hidden Layer Neural Sliding Mode Control of Active Power Filter With Multiple Feedback Loop

Abstract: A fuzzy multiple hidden layer neural sliding mode control with multiple feedback loop (FMHLNSMCMFL) is proposed for a single-phase active power filter (APF), where a sliding mode controller is designed to make the current tracking error converge to zero and a new neural network with multiple feedback loops is introduced to approximate unknown dynamics. At the same time, the fuzzy neural network can eliminate chattering, improve the control accuracy and reduce the current distortion rate of APF. Moreover, the proposed double feedback fuzzy double hidden layer recurrent neural network is the weighted sum of fuzzy network and double hidden layer network and has strong global learning ability. The adaptive parameters obtained by Lyapunov function can ensure the asymptotic stability of the system. Simulation and hardware experiments verify the introduced FMHLNSMCMFL scheme is a viable control solution for the APF.

Active Suspension Control Strategy of Multi-Axle Emergency Rescue Vehicle Based on Inertial Measurement Unit

Abstract: Active suspension control strategies are a top priority in active suspension system. The current research on active suspension control strategies is mostly focused on two-axle vehicles, and there is less research investigating multi-axle vehicles. Additionally, their effective implementation is dependent on accurate mathematical models, and most of them adopt force feedback control, which is vulnerable to external interference. To solve these problems, this paper proposes an active suspension control strategy based on Inertial Measurement Unit. The multi-axle emergency rescue vehicle is made to be equivalent to a 3-degrees-of-freedom parallel mechanism by using the method of grouping and interconnecting the suspension units of the whole vehicle. The attitude change of the vehicle body was transformed into the servo actuator’s displacement by solving the inverse solution of the parallel mechanism position and the action of the servo actuator was driven in reverse according to the displacement obtained. In this way, the vehicle body attitude can be compensated, and the ride comfort and the handling stability of the vehicle can be improved. To verify the effectiveness of the control strategy proposed, the three-axle six vehicle was taken as the research object, the position inverse solution of its equivalent 3-degrees-of-freedom parallel mechanism was deduced, and a high-pass filter was designed. The three-axle vehicle experiment platform integrating active suspension and hydro-pneumatic suspension was built, and the gravel road and slope road experiments were carried out and the results compared with those obtained with hydro-pneumatic suspension. The experiment results showed that, compared with hydro-pneumatic suspension, the active suspension control strategy based on Inertial Measurement Unit proposed in this paper can not only stabilize the body attitude, but also effectively suppress body vibration, improving the ride comfort and handling stability of the vehicle significantly.