An Energy Efficient Control Strategy for Electric Vehicle Driven by In-Wheel-Motors Based on Discrete Adaptive Sliding Mode Control

This paper presents an energy-efficient control strategy for electric vehicles(EVs)driven by in-wheel-motors(IWMs)based on discrete adaptive sliding mode control(DASMC).The nonlinear vehicle model,tire model and IWM model are established at first to represent the operation mechanism of the whole system.Based on the modeling,two virtual control variables are used to represent the longitudinal and yaw control efforts to coordinate the vehicle motion control.Then DASMC method is applied to calculate the required total driving torque and yaw moment,which can improve the tracking performance as well as the system robustness.According to the vehicle nonlinear model,the additional yaw moment can be expressed as a function of longitudinal and lateral tire forces.For further control scheme development,a tire force estimator using an unscented Kalman filter is designed to estimate real-time tire forces.On these bases,energy efficient torque allocation method is developed to distribute the total driving torque and differential torque to each IWM,considering the motor energy consumption,the tire slip energy consumption,and the brake energy~?recovery.Simulation results of the proposed control strategy using the co-platform of Matlab/Simulink and CarSim way.

Adaptive sliding mode backstepping control for near space vehicles considering engine faults

A fault tolerant control methodology based adaptive sliding mode(ASM) backstepping is proposed for near space vehicle(NSV) attitude control system under engine faults. The proposed scheme combined adaptive backstepping with the sliding mode control strategy could guarantee the system’s stability and track desired signals under external disturbances and engine faults. Firstly, attitude mode description and the engine faulty model are given. Secondly, a nominal control law is designed.Thirdly, a sliding mode observer is given later in order to estimate both the information of engine faults and external disturbances. An adaptive sliding mode technology based on the previous nominal control law is developed via updating faulty parameters. Finally,analyze the system’s fault-tolerant performance and reliability through experiment simulation, which verifies the proposed design of fault-tolerant control can tolerate engine faults, as well as the strong robustness for external disturbance.

Neural-Fuzzy-Based Adaptive Sliding Mode Automatic Steering Control of Vision-based Unmanned Electric Vehicles

This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters.Primarily,the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed,and in which the relationship between the look-ahead time and vehicle velocity is revealed.Then,in order to overcome the external disturbances,parametric uncertainties and time-varying features of vehicles,a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles,which includes an equivalent control law and an adaptive variable structure control law.In this novel automatic steering control system of vehicles,a neural network system is utilized for approximating the switching control gain of variable structure control law,and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time.The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory.Finally,the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

Adaptive Sliding Mode BTT Autopilot for Cruise Missiles with Variable-Swept Wings

In this paper,an adaptive sliding mode method was proposed for BTT autopilot of cruise missiles with variable-swept wings. To realize the whole state feedback,the roll angle,normal overloads and angular rates were considered as state variables of the autopilot,and a parametric sliding mode controller was designed via feedback linearization. A novel parametric adaptation law was put forward to estimate the nonlinear timevarying parameter perturbations in real time based on Lyapunov stability theory. A sliding mode boundary layer theory was adopted to smooth the discontinuity of control variables and eliminate the control chattering. The simulation was presented for the roll angle and overload commands tracking in different configuration schemes. The results indicated that the controlled system has robust dynamic tracking performance in condition of the large-scale aerodynamic parametric variety resulted from variable-swept wings.

Adaptive sliding mode control of modular self-reconfigurable spacecraft with time-delay estimation

The reconstruction control of modular self-reconfigurable spacecraft (MSRS) is addressed using an adaptive sliding mode control (ASMC) scheme based on time-delay estimation (TDE) technology. In contrast to the ground, the base of the MSRS is floating when assembled in orbit, resulting in a strong dynamic coupling effect. A TED-based ASMC technique with exponential reaching law is designed to achieve high-precision coordinated control between the spacecraft base and the robotic arm. TDE technology is used by the controller to compensate for coupling terms and uncertainties, while ASMC can augment and improve TDE’s robustness. To suppress TDE errors and eliminate chattering, a new adaptive law is created to modify gain parameters online, ensuring quick dynamic response and high tracking accuracy. The Lyapunov approach shows that the tracking errors are uniformly ultimately bounded (UUB). Finally, the on-orbit assembly process of MSRS is simulated to validate the efficacy of the proposed control scheme. The simulation results show that the proposed control method can accurately complete the target module’s on-orbit assembly, with minimal perturbations to the spacecraft’s attitude. Meanwhile, it has a high level of robustness and can effectively eliminate chattering.

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

Adaptive Nonlinear Sliding Mode Control for DC Power Distribution in Commercial Buildings

The developing populace and industrialization power demand prompted the requirement for power generation from elective sources.The desire for this pursuit is solid due to the ever-present common assets of petroleum deri-vatives and their predominant ecological issues.It is generally acknowledged that sustainable power sources are one of the best answers for the energy emergency.Among these,Photovoltaic(PV)sources have many benefits to bestow a very promising future.If integrated into the existing power distribution infrastructure,the solar source will be more successful,requiring efficient Direct Current(DC)-Alternating Current(AC)conversion.This paper mainly aims to improve control-lers’performance between AC/DC Energy sources and the DC loads using the Adaptive Nonlinear Sliding Mode(ANSM)control method.The proposed ANSM method efficiently controls power quality issues,such as transient response,powerflow reliability and Total Harmonics Distortion(THD).The proposed con-troller is applied for both AC/DC and DC/DC converters and the performance of the proposed controller is validated through simulation checking the above para-meters.The simulation results confirm ANSM configuration is more reliable and efficient than the existing fuzzy and sliding mode control methods.

Adaptive sliding mode output tracking control based-FODOB for a class of uncertain fractional-order nonlinear time-delayed systems

An adaptive sliding mode control(ASMC) method, based on fractional-order disturbance-observer(FODOB), is presented for a class of fractional-order nonlinear time-delay systems(FONTDS) with uncertainties to solve the target output tracking problem.The external disturbances are estimated by FODOB, and the unknown internal perturbations of the system are adaptively estimated by sliding mode control(SMC). Furthermore, Gronwall's inequality approach is used to ensure that the output tracking error is uniformly bounded for FONTDS. Firstly, a fractional-order sliding mode control(FOSMC) based FODOB is proposed for a fractional-order linear time-delay system(FOLTDS). Secondly, combined with adaptive estimation, the ASMC of FONTDS is studied. Finally, a numerical example of FONTDS is used to verify the effectiveness of the proposed methods.

RFID unreliable data filtering by integrating adaptive sliding Window and Euclidean distance

Through improving the redundant data filtering of unreliable data filter for radio frequency identification（RFID） with sliding-window,a data filter which integrates self-adaptive sliding-window and Euclidean distance is proposed.The input data required being filtered have been shunt by considering a large number of redundant data existing in the unreliable data for RFID and the redundant data in RFID are the main filtering object with utilizing the filter based on Euclidean distance.The comparison between the results from the method proposed in this paper and previous research shows that it can improve the accuracy of the RFID for unreliable data filtering and largely reduce the redundant reading rate.

Adaptive Sliding-Mode Tracking Control for an Uncertain Nonlinear SISO Servo System with a Disturbance Observer

An adaptive sliding mode controller with a disturbance observer(ASMC-DO) is proposed for the control of a single-input and single-output(SISO) servo system which has uncertain parameters, nonlinear friction,disturbance and input saturation. It is difficult to choose the suitable value of the parameters. The newly designed adaptive method is used to reduce the effects of system time-varying parameters, such as the moment of inertia and the damp coefficient. The robustness of object is improved. A DO is selected to approximate the compound disturbance and to render the estimate error convergent in finite time. The stability and the convergence of the closed-loop system are proved by using the Lyapunov theory. Experimental results show that the proposed ASMC-DO can better satisfy the influence of variable parameters and external disturbance to the control precision of the SISO servo system than other two controllers. The effectiveness of the proposed controller is showed. The control input stability and robust performances of the input saturation system are enhanced and the chattering is reduced.

Fuzzy adaptive sliding mode controller for electrically driven wheeled mobile robot for trajectory tracking task

This paper presents a fuzzy adaptive sliding mode controller(FASMC)for electrically driven wheeled mobile robot for trajectory tracking task in the presence of uncertainties and disturbances.First,a finite-time kinematic controller is developed to compute the auxiliary velocity vector.Second,the FASMC,based on the nonlinear dynamic model of the robot and its actuators,is used to guarantee the stability and the convergence of the closed-loop system.Moreover,by employing the advantages of the fuzzy logic systems,the developed controller ensures the robustness of the system against dynamic disturbances and uncertainties,the smoothness of the computing voltage against the chattering phenomenon,and the optimal convergence of the velocity and posture errors.The Lyapunov theory is used to analyse the stability of this algorithm.In order to evaluate the effectiveness of the developed method,numerical simulations are done in the Mahlab/Simulink environment.

Bio-inspired Backstepping Adaptive Sliding Mode Control for Parallel Mechanism with Actuation Redundancy

This paper presents a bio-inspired backstepping adaptive sliding mode control strategy for a novel 3 degree of freedom(3-DOF) parallel mechanism with actuation redundancy. Based on the kinematic model and the dynamic model, a sliding mode controller is designed to assure the tracking performance, and an adaptive law is introduced to approximate the system uncertainty including parameters variation, external disturbances and un-modeled part. Furthermore, a bio-inspired model is introduced to solve the inherent chattering problem of sliding mode control and provide a chattering free control. The simulation and experimental results testify that the proposed bio-inspired backstepping adaptive sliding mode control can achieve better performance(the tracking accuracy,robustness, response speed, etc.) than the conventional slide mode control.

An adaptive sliding mode controller design to cope with unmatched uncertainties and disturbance in a MEMS voltage reference source

Tunable micro-electro-mechanical systems(MEMS)capacitors as the fundamental parts are embedded in MEMS AC voltage reference sources(VRS).Being concerned with the accuracy of the output voltage in the reference sources,it gets important to address uncertainties in the physical parameters of the MEMS capacitor.The uncertainties have the great inevitable potentiality of bringing about output voltage perturbation.The output deterioration is more remarkable when the uncertainties are accompanied by disturbance and noise.Manufacturers have been making great attempts to make the MEMS adjustable capacitor with desired rigorous physical characteristics.They have also tried to mitigate physical parameter veracity.However,ambiguity in the values of the parameters inescapably occurs in fabrication procedures since the micro-machining process might itself suffer from uncertainties.Employing a proportional integral(PI)adaptive sliding mode controller(ASMC),both terms of matched and unmatched uncertainties as well as the disturbance,are addressed in this work for the MEMS AC VRS so that a strict voltage is stabilized while the system is simultaneously subjected into uncertainties and exogenous disturbance.Cross-talk,some inertial forces,and electrostatic coercions may appear as matched and unmatched disturbances.Alteration in stiffness and damping coefficients might also take place as matched uncertainties due to variations in the fabrication process or even working environment.The simulation results in the paper are persuasive and the controller design has shown a satisfactory tracking performance.

Extended state observer-based finite-time adaptive sliding mode control for wheeled mobile robot

In this paper,an Improved Extended State Observer-based Finite-Time adaptive sliding mode control,is investigated for trajectory tracking control of a wheeled mobile robot.First,a novel finite-time adaptive sliding mode control,based on the fractional power of the sliding surface,is developed to deal with the chattering problem.Moreover,this strategy improves the conver-gence rate by adjusting online the switching part in sliding mode control.Second,an improved Non-linear ESO is employed to reconstruct and compensate for the unknown disturbances.To complete the trajectory tracking control,the kinematic algorithm is in troduced.Theoretically,the proposed control scheme converges within finite-time thanks to the Lyapunov method.Finally,numerical simulations show the efficiency of the designed controller.

Adaptive Proportional-Derivative Sliding Mode Control Law With Improved Transient Performance for Underactuated Overhead Crane Systems

In this paper, an adaptive proportional-derivative sliding mode control(APD-SMC) law, is proposed for 2D underactuated overhead crane systems. The proposed controller has the advantages of simple structure, easy to implement of PD control, strong robustness of SMC with respect to external disturbances and uncertain system parameters, and adaptation for unknown system dynamics associated with the feedforward parts. In the proposed APD-SMC law, the PD control part is used to stabilize the controlled system, the SMC part is used to compensate the external disturbances and system uncertainties,and the adaptive control part is utilized to estimate the unknown system parameters. The coupling behavior between the trolley movement and the payload swing is enhanced and, therefore, the transient performance of the proposed controller is improved.The Lyapunov techniques and the La Salle's invariance theorem are employed in to support the theoretical derivations. Experimental results are provided to validate the superior performance of the proposed control law.

Robust Adaptive Gain Higher Order Sliding Mode Observer Based Control-constrained Nonlinear Model Predictive Control for Spacecraft Formation Flying

This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.

Adaptive robust controller for supercavitating vehicle using guaranteed cost theory

Regarding to the problems that supercavitating vehicles have special characteristics from traditional underwater vehicles,robust control problem was studied in this paper for the supercavitating vehicles with mismatched uncertainties.The nonlinear dynamic model was improved.For mismatched uncertainties,the robust sliding mode function was proposed based on guaranteed cost theory,and sufficient condition for the existence was given in terms of linear matrix inequality (LMI).Continuous sliding mode controller was designed,with an adaptive technology which was used to estimate the unknown upper bound of mismatched uncertainties.Meanwhile,upper bound of parameter uncertainties was not required.Simulation results demonstrated that the system responds rapidly and has good robust stability.Due to application of guaranteed cost theory,the controlled plant is not only stable but also guarantees an adequate level of performance.Therefore,it provides theoretical references for further study on control problems of supercavitating vehicles.

Adaptive Controller Design for Dynamic Maneuvers of High Speed Underwater Vehicles

The control synthesis of the high-speed underwater vehicle faces many technical challenges due to its inherent structure and surrounding operational environment.In this paper,the dynamical behavior is firstly described through a bifurcation analysis to give some insights for robust control synthesis.Then a novel adaptive fractional-order sliding mode controller(AFOSMC)is realized to effectively manipulate the supercavitating vehicle against payload changes,nonlinear planing force,and external disturbances.The fractional order(FO)calculus can offer more flexibility and more freedom for tuning active control synthesis than the integer-order counterpart.In addition,the adaptation law has been presented to directly handle the payload change effects.The stability of the controlled vehicle system is proven via Lyapunov stability theory.Next,the dynamic performance of the proposed controller is verified through extensive simulation results,which demonstrate the control accuracy with faster responses compared with existing integer-order controllers.Finally,the proposed fractional order controllers can provide higher performance than their integer order counterparts with control algorithms.

Fault tolerant control for near space vehicle:a survey and some new results

A review on fault-tolerant control（FTC） for near space vehicle（NSV） is presented.First,the concept of near space is introduced,the background of NSV is emphasized,and the model characteristics of NSV in faulty case are investigated.Then,a comparison of different existing approaches is briefly carried out,and achievements on the current research in this field are also presented in the view of the practical application.Furthermore,several existing advanced FTC results for nonlinear flight control systems are given.Finally,the recent literature of NSV are presented to provide an overall view of future developments in this area.

Attitude tracking control of flexible spacecraft with large amplitude slosh

This paper is focused on attitude tracking control of a spacecraft that is equipped with flexible appendage and partially filled liquid propellant tank. The large amplitude liquid slosh is included by using a moving pulsating ball model that is further improved to estimate the settling location of liquid in microgravity or a zero-g environment. The flexible appendage is modelled as a three-dimensional Bernoulli–Euler beam, and the assumed modal method is employed.A hybrid controller that combines sliding mode control with an adaptive algorithm is designed for spacecraft to perform attitude tracking. The proposed controller has proved to be asymptotically stable. A nonlinear model for the overall coupled system including spacecraft attitude dynamics,liquid slosh, structural vibration and control action is established. Numerical simulation results are presented to show the dynamic behaviors of the coupled system and to verify the effectiveness of the control approach when the spacecraft undergoes the disturbance produced by large amplitude slosh and appendage vibration. Lastly, the designed adaptive algorithm is found to be effective to improve the precision of attitude tracking.