Robust control and actuator dynamics compensation for railway vehicles

A robust controller is designed for active steering of a high speed train bogie with solid axle wheel sets to reduce track irregularity effects on the vehicle’s dynamics and improve stability and curving performance. A half-car railway vehicle model with seven degrees of freedom equipped with practical accelerometers and angular velocity sensors is considered for the H∞ control design. The controller is robust against the wheel/rail contact parameter variations. Field measurement data are used as the track irregularities in simulations. The control force is applied to the vehicle model via ball-screw electromechanical actuators. To compensate the actuator dynamics, the time delay is identified online and is used in a second order polynomial extrapolation carried out to predict and modify the control command to the actuator. The performance of the proposed controller and actuator dynamics compensation technique are examined on a one-car railway vehicle model with realistic structural parameters and nonlinear wheel and rail profiles. The results showed that for the case of nonlinear wheel and rail profiles significant improvements in the active control performance can be achieved using the proposed compensation technique

Robust control for independently rotating wheelsets on a railway vehicle using practical sensors

This paper presents the development of H-infinity control strategy for the active steering of railway vehicles with independently rotating wheelsets. The primary objective of the active steering is to stabilize the wheelset and to provide a guidance control. Some fundamental problems for active steering are addressed in the study. The developed controller is able to maintain stability and good performance when parameter variations occur, in particular at the wheel-rail interface. The control is also robust against structured uncertainties that are not included in the model such as actuator dynamics. Furthermore the control design is formulated to use only practical sensors of inertial and speed measurements, as some basic measurements required for active steering such as wheel-rail lateral displacement cannot be easily and economically measured in practice

Convolution based real-time control strategy for vehicle active suspension systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A novel real-time control method that minimises linear system vibrations when it is subjected to an arbitrary external excitation is proposed in this study. The work deals with a discrete differential dynamic programming type of problem, in which an external disturbance is controlled over a time horizon by a control force strategy constituted by the well-known convolution approach. The proposed method states that if a control strategy can be established to restore an impulse external disturbance, then the convolution concept can be used to generate an overall control strategy to control the system response when it is subjected to an arbitrary external disturbance. The arbitrary disturbance is divided into impulses and by simply scaling, shifting and summation of the obtained control strategy against the impulse input for each impulse of the arbitrary disturbance, the overall control strategy will be established. Genetic Algorithm was adopted to obtain an optimal control force plan to suppress the system vibrations when it is subjected to a shock disturbance, and then the Convolution concept was used to enable the system response to be controlled in real-time using the obtained control strategy. Numerical tests were carried out on a two-degree of freedom quarter-vehicle active suspension model and the results were compared with results generated using the Linear Quadratic Regulator (LQR) method. The method was also applied to control the vibration of a seven-degree of freedom full-vehicle active suspension model. In addition, the effect of a time delay on the performance of the proposed approach was also studied. To demonstrate the applicability of the proposed method in real-time control, experimental tests were performed on a quarter-vehicle test rig equipped with a pneumatic active suspension. Numerical and experimental results showed the effectiveness of the proposed method in reducing the vehicle vibrations. One of the main contributions of this work besides using the Convolution concept to provide a real time control strategy is the reduction in the number of sensors needed to construct the proposed method as the disturbance amplitude is the only parameter needed to be measured (known). Finally, having achieved what has been proposed above, a generic robust control method is accomplished, which not only can be applied for active suspension systems but also in many other fields

Active suspension control of electric vehicle with in-wheel motors

In-wheel motor (IWM) technology has attracted increasing research interests in recent years due to the numerous advantages it offers. However, the direct attachment of IWMs to the wheels can result in an increase in the vehicle unsprung mass and a significant drop in the suspension ride comfort performance and road holding stability. Other issues such as motor bearing wear motor vibration, air-gap eccentricity and residual unbalanced radial force can adversely influence the motor vibration, passenger comfort and vehicle rollover stability. Active suspension and optimized passive suspension are possible methods deployed to improve the ride comfort and safety of electric vehicles equipped with inwheel motor. The trade-off between ride comfort and handling stability is a major challenge in active suspension design. This thesis investigates the development of novel active suspension systems for successful implementation of IWM technology in electric cars. Towards such aim, several active suspension methods based on robust H∞ control methods are developed to achieve enhanced suspension performance by overcoming the conflicting requirement between ride comfort, suspension deflection and road holding. A novel fault-tolerant H∞ controller based on friction compensation is in the presence of system parameter uncertainties, actuator faults, as well as actuator time delay and system friction is proposed. A friction observer-based Takagi-Sugeno (T-S) fuzzy H∞ controller is developed for active suspension with sprung mass variation and system friction. This method is validated experimentally on a quarter car test rig. The experimental results demonstrate the effectiveness of proposed control methods in improving vehicle ride performance and road holding capability under different road profiles. Quarter car suspension model with suspended shaft-less direct-drive motors has the potential to improve the road holding capability and ride performance. Based on the quarter car suspension with dynamic vibration absorber (DVA) model, a multi-objective parameter optimization for active suspension of IWM mounted electric vehicle based on genetic algorithm (GA) is proposed to suppress the sprung mass vibration, motor vibration, motor bearing wear as well as improving ride comfort, suspension deflection and road holding stability. Then a fault-tolerant fuzzy H∞ control design approach for active suspension of IWM driven electric vehicles in the presence of sprung mass variation, actuator faults and control input constraints is proposed. The T-S fuzzy suspension model is used to cope with the possible sprung mass variation. The output feedback control problem for active suspension system of IWM driven electric vehicles with actuator faults and time delay is further investigated. The suspended motor parameters and vehicle suspension parameters are optimized based on the particle swarm optimization. A robust output feedback H∞ controller is designed to guarantee the system’s asymptotic stability and simultaneously satisfying the performance constraints. The proposed output feedback controller reveals much better performance than previous work when different actuator thrust losses and time delay occurs. The road surface roughness is coupled with in-wheel switched reluctance motor air-gap eccentricity and the unbalanced residual vertical force. Coupling effects between road excitation and in wheel switched reluctance motor (SRM) on electric vehicle ride comfort are also analysed in this thesis. A hybrid control method including output feedback controller and SRM controller are designed to suppress SRM vibration and to prolong the SRM lifespan, while at the same time improving vehicle ride comfort. Then a state feedback H∞ controller combined with SRM controller is designed for in-wheel SRM driven electric vehicle with DVA structure to enhance vehicle and SRM performance. Simulation results demonstrate the effectiveness of DVA structure based active suspension system with proposed control method its ability to significantly improve the road holding capability and ride performance, as well as motor performance

Series active variable geometry suspension application to comfort enhancement

This paper explores the potential of the Series Active Variable Geometry Suspension (SAVGS) for comfort and road holding enhancement. The SAVGS concept introduces significant nonlinearities associated with the rotation of the mechanical link that connects the chassis to the spring-damper unit. Although conventional linearization procedures implemented in multi-body software packages can deal with this configuration, they produce linear models of reduced applicability. To overcome this limitation, an alternative linearization approach based on energy conservation principles is proposed and successfully applied to one corner of the car, thus enabling the use of linear robust control techniques. An H∞ controller is synthesized for this simplified quarter-car linear model and tuned based on the singular value decomposition of the system's transfer matrix. The proposed control is thoroughly tested with one-corner and full-vehicle nonlinear multi-body models. In the SAVGS setup, the actuator appears in series with the passive spring-damper and therefore it would typically be categorized as a low bandwidth or slow active suspension. However, results presented in this paper for an SAVGS-retrofitted Grand Tourer show that this technology has the potential to also improve the high frequency suspension functions such as comfort and road holding

Temperature sensitive controller performance of MR dampers

Magnetorheological (MR) dampers can experience large temperature changes as a result of heating caused by energy dissipation, but control systems are often designed without consideration of this fact. Furthermore, due to the highly nonlinear behavior of MR dampers, many control strategies have been proposed and it is difficult to determine which is the most effective. This paper aims to address these issues through a numerical and experimental study of an MR mass isolator subject to temperature variation. A dynamic temperature dependant model of an MR damper is first developed and validated. Control system experiments are then performed using hardware-in-the-loopsimulations. Proportional, PID, gain scheduling, and on/off control strategies are found to be equally affected by temperature variation. Using simulations incorporating the temperature dependant MR damper model, it is shown that this is largely due to a change in fluid viscosity and the associated movement of the lower clipped optimal' control bound. This zero-volts condition determines how close any controller can perform to the ideal semiactive case, thus all types of controller are affected. In terms of relative performance, proportional and PID controllers perform equally well and outperform the on/off and gain scheduling strategies. Gain scheduling methods are superior to on/off control

LMI-based H∞ controller of vehicle roll stability control systems with input and output delays

This article belongs to the Section Physical Sensors.Many of the current research works are focused on the development of different control systems for commercial vehicles in order to reduce the incidence of risky driving situations, while also improving stability and comfort. Some works are focused on developing low-cost embedded systems with enough accuracy, reliability, and processing time. Previous research works have analyzed the integration of low-cost sensors in vehicles. These works demonstrated the feasibility of using these systems, although they indicate that this type of low-cost kit could present relevant delays and noise that must be compensated to improve the performance of the device. For this purpose, it is necessary design controllers for systems with input and output delays. The novelty of this work is the development of an LMI-Based H∞ output-feedback controller that takes into account the effect of delays in the network, both on the sensor side and the actuator side, on RSC (Roll Stability Control) systems. The controller is based on an active suspension with input and output delays, where the anti-roll moment is used as a control input and the roll rate as measured data, both with delays. This controller was compared with a controller system with a no-delay consideration that was experiencing similar delays. The comparison was made through simulation tests with a validated vehicle on the TruckSim® software.This work was supported by the FEDER/Ministry of Science and Innovation-Agencia Estatal de Investigacion (AEI) of the Government of Spain through the project [RTI2018-095143-B-C21]

Passive fault-tolerant control for vehicle active suspension system based on H2/H∞ approach

In this paper, a robust passive fault-tolerant control (RPFTC) strategy based on H2/H∞ approach and an integral sliding mode passive fault tolerant control (ISMPFTC) strategy based on H2/H∞ approach for vehicle active suspension are presented with considering model uncertainties, loss of actuator effectiveness and time-domain hard constraints of the suspension system. H∞ performance index less than γ and H2 performance index is minimized as the design objective, avoid choosing weighting coefficient. The half-car model is taken as an example, the robust passive fault-tolerant controller and the integral sliding mode passive fault tolerant control law is designed respectively. Three different fault modes are selected. And then compare and analyze the control effect of vertical acceleration of the vehicle body and pitch angular acceleration of passive suspension control, robust passive fault tolerant control and integral sliding mode passive fault tolerant control to verify the feasibility and effectiveness of passive fault tolerant control algorithm of active suspension. The studies we have performed indicated that the passive fault tolerant control strategy of the active suspension can improve the ride comfort of the suspension system

A Deep Reinforcement Learning-Based Controller for Magnetorheological-Damped Vehicle Suspension

This paper proposes a novel approach to controller design for MR-damped vehicle suspension system. This approach is predicated on the premise that the optimal control strategy can be learned through real-world or simulated experiments utilizing a reinforcement learning algorithm with continuous states/actions. The sensor data is fed into a Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which generates the actuation voltage required for the MR damper. The resulting suspension space (displacement), sprung mass acceleration, and dynamic tire load are calculated using a quarter vehicle model incorporating the modified Bouc-Wen MR damper model. Deep RL's reward function is based on sprung mass acceleration. The proposed approach outperforms traditional suspension control strategies regarding ride comfort and stability, as demonstrated by multiple simulated experimentsComment: 19 pages , 9 figures , 5 table