A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Advanced Fault-Tolerant Control of Induction-Motor Drives for EV/HEV Traction Applications: From Conventional to Modern and Intelligent Control Techniques

International audienceThis paper describes active fault-tolerant control systems for a high-performance induction-motor drive that propels an electrical vehicle (EV) or a hybrid one (HEV). The proposed systems adaptively reorganize themselves in the event of sensor loss or sensor recovery to sustain the best control performance, given the complement of remaining sensors. Moreover, the developed systems take into account the controller-transition smoothness, in terms of speed and torque transients. The two proposed fault-tolerant control strategies have been simulated on a 4-kW induction-motor drive, and speed and torque responses have been carried to evaluate the consistency and the performance of the proposed approaches. Simulation results, in terms of speed and torque responses, show the global effectiveness of the proposed approaches, particularly the one based on modern and intelligent control techniques in terms of speed and torque smoothness

Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review

Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.publishedVersio

Fault estimation and fault-tolerant control for discrete-time dynamic systems

In this paper, a novel discrete-time estimator is proposed, which is employed for simultaneous estimation of system states, and actuator/sensor faults in a discrete-time dynamic system. The existence of the discrete-time simultaneous estimator is proven mathematically. The systematic design procedure for the derivative and proportional observer gains is addressed, enabling the estimation error dynamics to be internally proper and stable, and robust against the effects from the process disturbances, measurement noise, and faults. Based on the estimated fault signals and system states, a discrete-time fault-tolerant design approach is addressed, by which the system may recover the system performance when actuator/sensor faults occur. Finally, the proposed integrated discrete-time fault estimation and fault-tolerant control technique is applied to the vehicle lateral dynamics, which demonstrates the effectiveness of the developed techniques

A Fuzzy-Based Strategy to Improve Control Reconfiguration Performance of a Sensor Fault-Tolerant Induction Motor Propulsion

International audienceThis short paper deals with the transition performance improvement of a sensor fault-tolerant controller devoted to automotive applications. Indeed, improvements are brought over a previously developed technique that exhibit abrupt changes in the torque if a sensor fault is detected and after a transition from a control technique to another one [1]. The Fault-Tolerant Control (FTC) system firstly concerns the sliding mode control technique since better performances are obtained with an encoder to get the speed information. In the event of unavailability of the speed sensor, a sensorless fuzzy control technique is applied. In the proposed active fault-tolerant control approach a short and a smooth transition are achieved from the encoder-based control technique to the sensorless one using an appropriate fuzzy logic decision approach

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

Robust Fault-Tolerant Control of In-Wheel Driven Bus with Cornering Energy Minimization

The aim of this paper is to design fault-tolerant and energy optimal trajectory tracking control for a four-wheel independently actuated (FWIA) electric bus with a steer-by-wire steering system. During normal driving conditions, the architecture of the proposed controller enables the bus to select an energy optimal split between steering intervention and torque vectoring, realized by the independently actuated in-wheel motors by minimizing the cornering resistance of the bus. In the case of skidding or a fault event of an in-wheel motor or the steering system, a high-level control reconfiguration using linear parameter varying (LPV) techniques is applied to reallocate control signals in order to stabilize the bus. The main novelty of the paper is the control reconfiguration method based on the specific characteristics of the in-wheel bus which enables introducing such scheduling variables, with which the safety and efficiency of the FWIA bus can be enhanced

On the Transition Improvement of EV or HEV Induction Motor Propulsion Sensor Fault-Tolerant Controller

International audienceThis technical paper deals with the transition performance improvement of a sensor fault-tolerant controller devoted to Electric (EV) or Hybrid Electric Vehicles (HEV). Indeed, improvements are brought over a previously developed technique that exhibit abrupt changes in the torque if a sensor fault is detected and after a transition from a control technique to another one [1]. The Fault-Tolerant Control (FTC) system firstly concerns the sliding mode control technique since better performances are obtained with an encoder to get the speed information. In the event of unavailability of the speed sensor, a sensorless fuzzy control technique is applied. In the proposed active fault-tolerant control approach a short and a smooth transition are achieved from the encoder-based control technique to the sensorless one using an appropriate fuzzy logic decision approach