Electrohydraulic Suspension Research Articles

Event‐triggered based finite‐frequency control for vehicle electrohydraulic suspension with force tracking

AbstractThis study investigates the problem of event‐triggered based finite‐frequency control for vehicle electrohydraulic suspensions with force tracking. A novel hierarchical control methodology is proposed by designing event‐triggered finite frequency and active force tracking controllers to improve the suspension performance. In practical application, active suspension system can be constructed as the network control system under consideration of the electrohydraulic actuator's nonlinear dynamics and parametric uncertainties, and in‐vehicle network delay in a unified framework. Then, due to the more sensitiveness of the human body to vertical vibrations in 4–8 Hz and limited in‐vehicle network communication resource, an event‐triggered finite frequency controller is developed based on the generalized KYP lemma and Lyapunov stability theory. The triggered condition is designed for the network control system with in‐vehicle network delay. Other physical constraints including suspension working space, tire dynamic load and actuator saturation are also introduced in this controller design. It can generate the target force to satisfy suspension performance requirements under each triggered instant period. Furthermore, since the nonlinearity and uncertainty always exist in the electrohydraulic actuator, a filter‐based adaptive sliding mode control method is employed to design the active force tracking controller. It can precisely drive electrohydraulic actuator to track the target constant force generated by event‐triggered finite frequency controller. Finally, the results validate the effectiveness and saving communication resource capability of the proposed control methodology.

Reducing Operation Emissions and Improving Work Efficiency Using a Pure Electric Wheel Drive Tractor

In response to the problems of excessive greenhouse-gas and particulate emissions and the low traction efficiency of conventional diesel tractors in the field, a purely electric wheel-side drive tractor was studied, including an electric motor drive system, a battery ballast system, and an electro–hydraulic suspension system. This paper develops a dynamics model of an electric tractor-ploughing unit under complex soil conditions, leading to the proposal of an active control method for drive wheel torque and a joint control method for the traction force of the suspension system and the front- and rear-axle loads of a tractor. Finally, the tractor is prototyped and assembled, and ploughing tests are carried out. The ploughing results show that the active torque-distribution control method proposed in this study reduces the tractor slip by 14.83% and increases the traction efficiency by 10.28% compared with the average torque-distribution mode. Compared with the conventional traction control mode, the joint control method for traction and ballast proposed in this paper results in a 3.7% increase in traction efficiency, a 15.05% decrease in slip, and a 4.9% reduction in total drive motor energy consumption. This study will help to improve the operation quality and traction efficiency of electric tractors in complex soil conditions.

Adaptive hierarchical optimization control for electrohydraulic suspension with resistor-capacitor operator

The controller design for integrated electrohydraulic suspension with leaf spring is a complicated and challenging task, aiming to achieve optimal dynamic performance for heavy vehicles. Considering the hysteresis property of leaf spring, parameter uncertainties and nonlinearity, a novel hierarchical optimization control strategy including upper and bottom controllers is proposed to effectively suppress the vertical vibration of vehicle body. To describe the hysteresis property of leaf spring, a novel resistor-capacitor operator hysteresis model is identified by experiment and optimized by genetic algorithm. Based on hysteresis model, the filter adaptive backstepping control with sprung mass uncertainty is designed as upper controller to generate the desired active force for electrohydraulic actuator. Then, the projection adaptive fuzzy sliding mode control is designed as bottom controller for nonlinear actuator with time-varying fluid parameter to accurately track the required target force. Additionally, a stratified sampling algorithm is investigated to optimize the parameters of hierarchical control strategy for addressing multi-objective optimization issue of electrohydraulic suspension with leaf spring. Finally, the results show that the proposed method has better robustness and effectiveness, and it can ensure ride comfort, safety and optimal performance.

Design and Test of a Tractor Electro-Hydraulic-Suspension Tillage-Depth and Loading-Control System Test Bench

Electro-hydraulic suspension systems are one of the key working systems of tractors. Due to the complex and changeable working conditions in the field, it is of great significance to shorten the development cycle of the control strategy and reduce the development cost by using the indoor bench for test verification at the beginning of the study. Based on this, this paper has proposed a complete set of tractor hydraulic-suspension tillage-depth and loading-control test-bench designs. The system was mainly composed of three parts: an industrial computer, a suspension electro-hydraulic control system, and a loading electro-hydraulic control and data-acquisition system. The human–computer interaction interface of the test-bench measurement and control system was built, and the loading-force control system and suspension tillage-depth and loading integrated-control system were built based on PID and fuzzy PID control algorithms, respectively. The system can realize the control of suspension tillage depth and loading during the operation process and has the functions of the real-time acquisition, display, and data storage of related sensor signals during the working process. The test results showed that the response time of the loading-control system was less than 1.2 s, and the maximum steady-state error was less than 0.8%. The response time of the suspension control system was less than 2.3 s, and the maximum steady-state error was less than 1%. The system has good responsiveness and stability. These research results can provide platform and method of support for the development and test of tractor electro-hydraulic suspension systems.

Decoupled adaptive terminal sliding mode control strategy for a 6-DOF electro-hydraulic suspension test rig with RBF coupling force compensator

Aiming at the problems of poor tracking accuracy, low convergence speed, weak robustness of a 6-DOF electro-hydraulic suspension test system under system uncertainties and external disturbance, this article proposes double closed-loop control scheme. In the outer loop controller, this article designs a new decoupled adaptive fast nonsingular terminal sliding mode (DAFNTSM) control to achieve fast convergence rate, high accurate and adaptive disturbances estimation during trajectory tracking. Additionally, a coupling force compensator based on RBF neural network is employed, which can reduce online calculation quantity and guarantee accuracy. For six inner loop controllers, each hydraulic actuator can precisely follow the required force solved by outer loop controller. The hard-in-loop experiment results reveal that the control approach we proposed in this paper realize superior trajectory tracking characteristics in comparison with the conventional nonsingular terminal sliding mode (CNTSM) method.

Quality prediction of tractor rotary tillage based on BiConvLSTM with self-attention

To accurately predict rototilling performance and rotary tillage quality based on multi-sensor measured data of tractor electro-hydraulic suspension system, an improved ConvLSTM-based model is proposed, and field tests of rototilling operation are carried out to verify the accuracy. The model is based on the SA-BiConvLSTM (Self-attention Bi-directional ConvLSTM, BiConvLSTM) network as the core, and the BiConvLSTM can take the time dependence of the load sequence’s contextual state information into account and extract the local features more deeply and accurately; the self-attention mechanism strengthens the inner correlation of long-range load features, it significantly reduces the number of model parameters, solving the problems of degraded prediction performance and low computing efficiency caused by the length of the load sequence. The experimental results showed that the accuracy and F1-score of the rotary tillage quality prediction based on the measured data reached 97.40% and 97.47%, respectively, and the model had a considerable improvement in the prediction efficiency with the highest increase of 14.09%, and all evaluation metrics were better than the experimental results of the control group. This model ensures the breadth, depth and correlation of the load feature, significantly simplifies the model complexity and directly improves the prediction effect and computing efficiency. This study explores an intelligent technological approach for predicting the quality of rotary tillage, providing a new technological reference for the research and application of precision agriculture.

Research on Variable-Universe Fuzzy Control Technology of an Electro-Hydraulic Hitch System

To improve the quality and control accuracy of the farming tractor electro-hydraulic hitch system, a variable-universe fuzzy control algorithm is introduced herein based on force–position mixed adjustment. (1) Background: This research sought to improve the operation quality and control precision of the tractor electro-hydraulic suspension operation system by solving the slow response and low precision problems in the target value control of the system. (2) Methods: According to the characteristics of the operating system, the working principle is discussed. The variable-universe fuzzy controller and the control module were designed based on MC9S12XS128. At the same time, we used Matlab/Simulink to study the step response, and field tests were carried out based on the existing test conditions. (3) Results: In the response stage, the variable-universe fuzzy control only needs 5.85 s, and there is no overshoot problem; in the normal tillage stage, the maximum tillage depth difference is only 1.6 cm, and the traction force is 428 N, which is closer to the expected value. (4) Conclusions: The farming quality and efficiency of the operating system were improved. Additionally, the operating system can also provide technical support for intelligent agricultural machinery and the field management mode in the future.

An LMI-based approach for the control of semi-active magnetorheological suspensions

We address modelling and control of semi-active suspensions based on magnetorhe-ological (MR) fluids. We first introduce a saturation-based model of the underlying nonlinear phenomena, and combine the MR suspension with a quarter car model whose parameters resemble an SUV-like vehicle. Then we present simulation results to test the passenger comfort arising from the passive configuration (namely holding the input constant over the whole simulation) and the use of the Skyhook controller (which is adapted from its typical use in electrohydraulic suspensions). Finally, we propose LMI-based control designs exploiting an approximated model and typical generalized sector conditions for saturation nonlinearities. The simulation results show the advantages of the proposed design.

Model Predictive Control of Half-Car Active Suspension Systems Using Particle Swarm Optimisation

This paper presents the design of a particle swarm-optimised model predictive controller (MPC) for a half-car nonlinear electrohydraulic suspension system as it traverses a deterministic road disturbance. The particle swarm optimisation (PSO) algorithm uses an objective function which is based on conflicting active vehicle suspension system (AVSS) design specifications such as: ride comfort, road holding, road handling, suspension travel and power consumption. An inner-loop PID-based force feedback control is incorporated in the design to ensure good force tracking. The half-car model is composed of nonlinear suspensions and actuator dynamics. Simulation results demonstrate the superior performance of the proposed control scheme over the passive vehicle suspension system (PVSS) and the non-optimised MPC in rejecting the deterministic road disturbance.

Vehicle roll stability control with active roll-resistant electro-hydraulic suspension

This study examines roll stability control for vehicles with an active roll-resistant electro-hydraulic suspension (RREHS) subsystem under steering maneuvers. First, we derive a vehicle model with four degrees of freedom and incorporates yaw and roll motions. Second, an optimal linear quadratic regulator controller is obtained in consideration of dynamic vehicle performance. Third, an RREHS subsystem with an electric servo-valve actuator is proposed, and the corresponding dynamic equations are obtained. Fourth, field experiments are conducted to validate the performance of the vehicle model under sine-wave and double-lane-change steering maneuvers. Finally, the effectiveness of the active RREHS is determined by examining vehicle responses under sine-wave and double-lane-change maneuvers. The enhancement in vehicle roll stability through the RREHS subsystem is also verified.

Proportional + integral + derivative control of nonlinear full-car electrohydraulic suspensions using global and evolutionary optimization techniques

Resolving the trade-offs between suspension travel, ride comfort, road holding, vehicle handling and power consumption is the primary challenge in the design of active vehicle suspension system. Multi-loop proportional + integral + derivative controllers’ gains tuning with global and evolutionary optimization techniques is proposed to realize the best compromise between these conflicting criteria for a nonlinear full-car electrohydraulic active vehicle suspension system. Global and evolutionary optimization methods adopted include: controlled random search, differential evolution, particle swarm optimization, modified particle swarm optimization and modified controlled random search. The most improved performance was achieved with the differential evolution algorithm. The modified particle swarm optimization and modified controlled random search algorithms performed better than their predecessors, with modified controlled random search performing better than modified particle swarm optimization in all aspects of performance investigated both in time and frequency domain analyses.

Fuzzy Preview Control for Half-vehicle Electro-hydraulic Suspension System

This paper proposes a new fuzzy preview control method for an electro-hydraulic suspension system to further improve the suspension performance and extend the results to practical situations that use the actual actuator in a preview suspension system. A new augmented system that includes hydraulic actuators and preview information of road disturbances is proposed and described by the T-S fuzzy system. Based on the parallel distributed compensation (PDC) and multi-objective H∞/GH2 control design scheme, the fuzzy preview controller is designed for a newly obtained model in which the closed-loop suspension system is asymptotically stable with guaranteed robust performance in the H∞ sense. The simulation results clearly validate the effectiveness of the proposed controllers in terms of its suspension performance.

ELECTRO HYDRAULIC SUSPENSION SYSTEM DESIGN WITH OPTIMAL STATE DERIVATIVE FEEDBACK CONTROLLER

This paper is concerned with a control design of an electro-hydraulic suspension system. In some practical problems, for instance in the active suspension design, the state derivative signals such as acceleration and velocity are easier to obtain rather than the state variables such as displacement and velocity, since the most commonly used sensors are the accelerometers. Hence, design of an optimal state derivative feedback controller is proposed by employing the linear matrix inequalities framework. In order to demonstrate the effectiveness of the proposed controller, a two-degree-of-freedom quarter vehicle suspension model equipped with an electro hydraulic actuator is preferred. Throughout the numerical simulation studies, bump type road irregularities at different vehicle forward velocities are applied to evaluate the performances of the controller in terms of ride comfort and safety.

Intelligent feedback linearization control of nonlinear electrohydraulic suspension systems using particle swarm optimization

The core factors governing the performance of active vehicle suspension systems (AVSS) are the inherent trade-offs involving suspension travel, ride comfort, road holding and power consumption. In addition to this, robustness to parameter variations is an essential issue that affects the effectiveness of highly nonlinear electrohydraulic AVSS. Therefore, this paper proposes a nonlinear control approach using dynamic neural network (DNN)-based input–output feedback linearization (FBL) for a quarter-car AVSS. The gains of the proposed controllers and the weights of the DNNs are selected using particle swarm optimization (PSO) algorithm while addressing simultaneously the AVSS trade-offs. Robustness and effectiveness of the proposed controller were demonstrated through simulations.

Particle Swarm Optimized Intelligent Control of Nonlinear Full-Car Electrohydraulic Suspensions

This paper presents the design of an indirect adaptive feedback linearization (FBL)-based control using dynamic neural networks (DNN) for full-car nonlinear electrohydraulic suspensions. Particle swarm optimization (PSO) algorithm is used in training the DNN to learn the dynamics of the system. A multi-loop, PSO-optimized proportional-integral-derivative (PID) control is implemented for the feedback-linearized DNN model to improve system performance. The proposed control scheme outperformed the passive vehicle suspension system (PVSS) and the benchmark PSO-optimized PID controller.

Proportional-integral-derivative control of nonlinear half-car electro-hydraulic suspension systems

This paper presents the development of a proportional-integral-derivative (PID)-based control method for application to active vehicle suspension systems (AVSS). This method uses an inner PID hydraulic actuator force control loop, in combination with an outer PID suspension travel control loop, to control a nonlinear half-car AVSS. Robustness to model uncertainty in the form of variation in suspension damping is tested, comparing performance of the AVSS with a passive vehicle suspension system (PVSS), with similar model parameters. Spectral analysis of suspension system model output data, obtained by performing a road input disturbance frequency sweep, provides frequency response plots for both nonlinear vehicle suspension systems and time domain vehicle responses to a sinusoidal road input disturbance on a smooth road. The results show the greater robustness of the AVSS over the PVSS to parametric uncertainty in the frequency and time domains.

Differential Evolution-Based PID Control of Nonlinear Full-Car Electrohydraulic Suspensions

This paper presents a differential-evolution- (DE-) optimized, independent multiloop proportional-integral-derivative (PID) controller design for full-car nonlinear, electrohydraulic suspension systems. The multiloop PID control stabilises the actuator via force feedback and also improves the system performance. Controller gains are computed using manual tuning and through DE optimization to minimise a performance index, which addresses suspension travel, road holding, vehicle handling, ride comfort, and power consumption constraints. Simulation results showed superior performance of the DE-optimized PID-controlled active vehicle suspension system (AVSS) over the manually tuned PID-controlled AVSS and the passive vehicle suspension system (PVSS).

Robust control of vehicle suspension with electrohydraulic actuator

This paper presents a study on robust control of vehicle electrohydraulic suspension with parameter uncertainties. The change of sprung mass and the variation of spring stiffness, damping coefficient, and actuator parameters are considered as parameter uncertainties and described by different methods. A robust controller is then designed for the uncertain vehicle suspension model to optimise its performances on ride comfort, suspension deflection, and road holding ability considering suspension and actuator parameter uncertainties and actuator saturation. The sufficient conditions for designing such a controller are derived as linear matrix inequalities (LMIs) which can be solved using standard software. Numerical simulations are used to validate the effectiveness of the proposed approach. It is confirmed by the simulation results that the applied control strategy performs better than the passive suspension regardless of the parameter uncertainties.

Static Output Feedback Control for Electrohydraulic Active Suspensions via T–S Fuzzy Model Approach

The paper presents a fuzzy static output feedback controller design approach for vehicle electrohydraulic active suspensions based on Takagi–Sugeno (T–S) fuzzy modeling technique. The T–S fuzzy model is first applied to represent the nonlinear dynamics of an electrohydraulic suspension. Then, the fuzzy static output feedback controller is designed for the obtained T–S fuzzy model to optimize the H∞ performance of ride comfort through the parallel distributed compensation scheme. The sufficient conditions for the existence of such a controller are derived in terms of linear matrix inequalities (LMIs) with an equality constraint. A computational algorithm is presented to convert the equality constraint into a LMI so that the controller gains can be obtained by solving a minimization problem with LMI constraints. To validate the effectiveness of the proposed approach, two kinds of static output feedback controllers, which use suspension deflection and sprung mass velocity, and suspension deflection only, respectively, as feedback signals, are designed. It is confirmed by the simulations that the designed controllers can achieve good suspension performance similar to that of the active suspension with optimal skyhook damper.

Fuzzy Control for Nonlinear Uncertain Electrohydraulic Active Suspensions With Input Constraint

This paper presents a Takagi-Sugeno (T-S) model-based fuzzy control design approach for electrohydraulic active vehicle suspensions considering nonlinear dynamics of the actuator, sprung mass variation, and constraints on the control input. The T-S fuzzy model is first applied to represent the nonlinear uncertain electrohydraulic suspension. Then, a fuzzy state feedback controller is designed for the obtained T-S fuzzy model with optimized H infin performance for ride comfort by using the parallel-distributed compensation (PDC) scheme. The sufficient conditions for the existence of such a controller are derived in terms of linear matrix inequalities (LMIs). Numerical simulations on a full-car suspension model are performed to validate the effectiveness of the proposed approach. The obtained results show that the designed controller can achieve good suspension performance despite the existence of nonlinear actuator dynamics, sprung mass variation, and control input constraints.