An active suspension system for lunar crew mobility

The optimal control design of the ground-vehicle active suspension system is presented. The active suspension system is to improve the vehicle ride comfort by isolating vibrations induced by the road profile and vehicle velocity. The vehicle suspension system is approached by a quarter car model. Dynamic equations of the system are derived by applying Newton’s second law. The control law of the active suspension system is designed using linear quadratic regulator (LQR) method. Performance evaluation is done by benchmarking the active suspension system to a passive suspension system. Both suspension systems are simulated in computer. The simulation results show that the active suspension system significantly improves the vehicle ride comfort of the passive suspension system by reducing 50.37% RMS of vertical displacement, 45.29% RMS of vertical velocity, and 1.77% RMS of vertical acceleration.

Suspension system is used to fulfil the criteria of ride comfort and road handling. In this paper, a quarter car active & semi-active suspension systems are designed using Matlab/Script software. Comparison of active & semi-active suspension systems are done using robust control theory for the control targets suspension deflection, body acceleration and body travel. H infinity controller is selected to compare the two suspensions using time domain analysis. Finally the simulation result prove the effectiveness of the active suspension system by decreasing the body acceleration & sustaining the suspension deflection and body travel outputs.

During blueberry picking operations, changes in the blueberry harvester’s body posture (BHBP) caused by undulating farmland surfaces significantly affect the operational stability of the harvesting device. To mitigate these effects, an active suspension (AS) control system was developed. First, considering the coherence and time lag of the four-wheel tracks, the filtered white noise method was chosen to generate road excitations. Subsequently, the virtual prototype model of the blueberry harvester (BH) was built in ADAMS with the nonlinear properties of the passive suspension. A fuzzy proportion integral differential (PID) control algorithm and decoupled control strategy were employed to design the AS control system. Finally, ADAMS-MATLAB co-simulations and field tests were conducted. The results indicate that the measured farmland road profile conforms to standard D-level road excitations according to ISO8608, and the co-simulation model accurately predicts the BH’s dynamic response. Under AS control, the vertical acceleration, pitch acceleration, and roll acceleration of the BH decreased by 38.52%, 37.39%, and 34.29%, respectively, during simulations compared to the passive suspension. In field tests, these reductions were 36.51%, 33.84%, and 30.21%, respectively. The AS control system proposed in this study significantly improves the stability of the BH under farmland road excitation, effectively mitigating equipment impacts and wear caused by machine jolts while enhancing harvesting performance. This research addresses the gap in applying AS technology within the field of harvesting machinery, offering a novel technical approach for the development of vehicle control systems for harvesting machinery targeting blueberries and other shrub crops. It holds considerable theoretical value and practical significance.

Enhancing vehicle stability, while maintaining vehicle control and ride comfort, can significantly improve the chances of accident avoidance in an emergency situation. While traditional vehicle suspension systems provide a compromise between ride and handling, this research study proposes the design of a controllable pneumatic suspension system using fluidic muscle pneumatic actuators, providing a low natural frequency response, for improving ride comfort, but having the ability to respond to severe dynamic maneuvers by increasing the suspension stiffness. In addition, individual corner stiffness and damping will be controlled to manage pitch, roll and yaw movement, as well as ride height, in response to road inputs, direction changes, and vehicle load fluctuations. The objective of this research is to develop an active suspension control model that will dynamically optimise both the ride and handling parameters of a pneumatic fluidic muscle suspension on a light, off-road experimental motor vehicle. This paper focusses on phase one of the study, namely the research and design of the active pneumatic suspension system, and also provides test results of fluidic muscle characterisation tests to determine their suitability in this application.

On a flat city road, the specificity of the suspension poses a challenge. Sport utility vehicles (SUVs) have less flexibility compared to regular cars, despite providing a firm grip on asphalt and concrete. Constant adjustments to the center of gravity of SUVs are necessary. Surprisingly, they are less reliable and stable in urban settings due to this characteristic. In this study, a mathematical model of the suspension system of SUVs based on the Newtonian approach is introduced and validated with data from experiments carried out by the MTS machine system on the mono-tube (oil/air) mixed damper element. The model accurately predicts the performance of this damper, commonly used in SUVs, across various operating conditions, including different frequencies. A coil spring element, serving as a passive suspension unit with this damper, is also tested experimentally under similar conditions. By integrating passive suspension elements with the active actuator, the proposed modified design reduces the power consumption needed for the actuator to function and ensures a certain level of reliability. The effectiveness and performance of the modified active suspension system in comparison to the traditional passive suspension system are assessed using three different strategies: hybrid PID-LQR, linear quadratic regulator (LQR), and proportional-integral-derivative (PID). The genetic algorithm is utilized to determine the optimal parameter values for each controller by minimizing a cost function, maximizing performance, and minimizing energy consumption. Simulation results demonstrate that the active suspension system controlled by the PID-LQR controller offers significantly improved ride comfort and vehicle stability compared to other systems. This suggests that the performance of the active suspension system is greatly enhanced by the combined application of the hybrid PID-LQR controller compared to other systems.

This paper proposes the study of automobile active suspension system for the purpose of improving ride comfort to passengers and simultaneously improving the stability of vehicle by reducing vibration effects on suspension system. With the increased demand of fine control of parameters, the mechatronic controller is being used for increasing the comfort of vehicle with their application to the suspension system of the vehicle. This is the prime location for the consideration of inclusion of controller. The modeling and simulation is carried out in Simulink environment and the PID (Proportional Integral derivative) controller is introduced for improving the performance of the suspension system. The active control of the suspension system is being carried out by proper tuning of the controller. The dynamic performance of the integrated system is improved significantly by using the controller.

Fuzzy and neuro control for semi-active and active suspension

This paper proposes a bioinspired reference model based fuzzy adaptive tracking control for active suspension systems. A general bioinspired nonlinear structure, which can present ideal nonlinear quasi-zero stiffness for vibration isolation, is adopted as tracking reference model. Fuzzy logic systems are used to approximate unknown nonlinear terms in nonlinear suspension systems. Particularly, a nonlinear damping is designed to improve damping characteristics of the bioinspired reference model. With beneficial nonlinear stiffness and improved nonlinear damping of the bioinspired reference model, the proposed fuzzy adaptive controller can effectively suppress vibration of suspension systems with less actuator force and much improved ride comfort, thus energy saving performance can be achieved. Finally, a quarter-vehicle active suspension system with considering payload uncertainties, general disturbance, and actuator saturation is provided for evaluating the validity and superiority of the bioinspired nonlinear dynamics based fuzzy adaptive control approach proposed in this paper.

Effective control of ride quality and handling performance are challenges for active vehicle suspension systems, particularly for off-road applications. Off-road vehicles experience large suspension displacements, where the nonlinear kinematics and damping characteristics of suspension elements are significant. These nonlinearities tend to degrade the performance of active suspension systems, introducing harshness to the ride quality and reducing off-road mobility. Typical control strategies rely on linear time-invariant models of the suspension dynamics. While these models are convenient, nominally accurate, and tractable due to the abundance of linear control techniques, they neglect the nonlinearities and time-varying dynamics present in real suspension systems. One approach to improving the effectiveness of active vehicle suspension systems, while preserving the benefits of linear control techniques, is to estimate and cancel the nonlinearities using feedback linearization. In this paper, the authors demonstrate an intelligent parameter estimation approach, using structured artificial neural networks, that continually "learns" the nonlinear parameter variations of a quarter-car suspension model. This estimation algorithm becomes the foundation for an intelligent feedback linearization (IFL) controller for active vehicle suspensions. Results are presented for real-time experimental tests and field evaluations on a military HMMWV. These results clearly demonstrate the viability and effectiveness of this approach as a tool for rapid, online development of vehicle suspension models and controllers.

This paper considers experiments on the control of a helicopter gearbox hybrid electromagnetic suspension. As the new generation of helicopters includes variable engine revolutions per minute (RPMs) during flight, it becomes relevant to add active control to their suspension systems. Most active system performance derives directly from the controller construction, its optimization to the system controlled, and the disturbances expected. An investigation on a feedback and feedforward filtered-x least mean square (FXLMS) control applied to an active DAVI suspension has been made to optimize it in terms of narrow-band disturbance rejection. In this paper, we demonstrate the efficiency of a new hybrid active suspension by combining the advantages of two different approaches in vibration control: resonant absorbers and active suspensions. Here, a hybrid active suspension based on the passive vibration filter called DAVI is developed. The objective of this paper is to prove the relevancy of coupling a resonant vibration absorber with a control actuator in order to create an active suspension with larger bandwidth efficiency and low energy consumption. The simulations and experimentation achieved during this suspension system development support this hypothesis and illustrate the efficiency and low energy cost of this smart combination.

Active suspension can improve vehicle vibrations caused by road excitation. For trucks, the vehicle mass change is usually large, and changes in vehicle mass will affect the control performance of the active suspension. In order to solve the problem of active suspension control performance decreasing due to large changes in vehicle mass, this paper proposes an active suspension control method integrating online mass estimation. This control method is designed based on the mass estimation algorithm of the recursive least squares method with a forgetting factor (FFRLS) and the Linear Quadratic Regulator (LQR) algorithm. A set of feedback control matrices K is obtained according to different vehicle masses. Then, the mass estimation algorithm can estimate the actual vehicle mass in real-time during the vehicle acceleration process. According to the mass estimation value, a corresponding feedback control matrix K is selected from the control matrix set, and K is used as the actual control gain matrix of the current active suspension. With specific simulation cases, the vehicle vibration response is studied by the numerical simulation method. The results of the simulation process have shown that when the vehicle mass changes largely, the suspension dynamic deflection and tire dynamic deformation are significantly reduced while keeping a good vehicle body attitude control effect by using an active suspension controller integrated with online mass estimation. In the random road simulation, suspension dynamic deflection is reduced by 3.26%, and tire dynamic deformation is reduced by 5.91% compared with the original active suspension controller. In the road bump simulation, suspension dynamic deflection and tire dynamic deformation are also significantly reduced. As a consequence, the stability and comfort of the vehicle have been greatly enhanced.

In this article, the human sensitivity to vibration acceleration at various frequencies is incorporated in the design of active suspension by using the frequency-shaped linear-quadratic-Gaussian (LQG) method. And three new sufficient conditions of stability robustness for the frequency-shaped LQG active suspension systems subject to both disturbance/noise uncertainties and linear time-varying parameter perturbations are also presented in this article. The proposed new sufficient conditions provide a quantitative measure for automotive designers to design the frequency-shaped LQG active suspension systems with robustness properties. An illustrated example is given to demonstrate the applicability of the proposed new sufficient criteria.

Vibration suppression is considered as a keyresearch field in civil engineering to ensure the safety and comfort of their occupants and users of mechanical structures. To reduce the system vibration, an effective vibration control with isolation is necessary. Vibration control techniques have classically been categorized into two areas, passive and active controls. For a long time, efforts were made to make the suspension system work optimally by optimizing its parameters, but due to the intrinsic limitations of a passive suspension system, improvements were effective only in a certain frequency range. Compared with passive suspensions, active suspensions can improve the performance of the suspension system over a wide range of frequencies. Semi-active suspensions were proposed in the early 1970s [1], and can be nearly as effective as active suspensions. When the control system fails, the semi-active suspension can still work under passive conditions. Compared with active and passive suspension systems, the semi-active suspension system combines the advantages of both active and passive suspensions because it provides better performance when compared with passive suspensions and is economical, safe and does not require either higher-power actuators or a large power supply as active suspensions do [2].

In order to improve the vehicle ride comfort, the vehicle EHA (electro-hydrostatic actuator, EHA) active suspension structure has been proposed. The mathematical model of the 2 DOF active suspension and the mathematical model of the EHA active suspension system are established. The influence of the actuator (brushless DC motor) on the main force of the system is analyzed. A force tracking control strategy is designed, which includes the system outer ring LQG controller and the system inner loop motor speed & current controller. According to the influence of the brushless DC motor on the active suspension system, the simulation analysis of the suspension system under the control of the force tracking and the LQG control without considering the influence of the motor on the system is carried out. The results show that the force tracking control strategy can effectively track the active force of the system and improve the dynamic characteristics of the EHA active suspension.

Active suspension have not been used widely due to its magnificent energy consuming. A kind of electromechanical energy-regenerative suspension is proposed in this paper. Suspension dynamic equations are modeled by MATLAB/Simulink. In order to get an optimal performance of suspension, several indices are discussed in this paper with three control curve on a motor MAP diagram. The results indicated that optimal control strategy depends on subjective object; As for energy recovery, performance contour is the best choice. If the objective is the balance of all indices, middle torque curve is the ideal choose. Also an active control suspension and energy-regenerative suspension are compared in this paper. It can be concluded that the active control suspension can obtain good dynamic effects but consume considerable energy.