Differential Steering Research Articles

A 50μW Fully Differential Interface Amplifier With a Current Steering Class AB Output Stage for PPG and NIRS Recordings

This presents a low-power fully differential optical sensor interface amplifier for photoplethysmography (PPG) and near infrared spectroscopy (NIRS) recordings. The proposed amplifier employs a stacked current reuse input stage that provides a DC biasing voltage for the photodiode, reducing the parasitic capacitance. The output stage exploits a fully differential current steering class AB topology with a self-regulated common mode voltage, providing a $70\mu \text{A}$ input current range with minimized quiescent current. Moreover, the interface amplifier can be reconfigured as either single-ended mode suitable for photo detectors biased at a high voltage or fully differential mode for those biased at a low voltage. This amplifier is implemented in a standard $0.18\mu \text{m}$ CMOS process and characterized experimentally. Measurement results show that, with a 1.5V supply, the amplifier can provide up to 1V biasing voltage for the photodiode and consumes a static power of around $50\mu \text{W}$ . It achieves a dynamic range of 97dB in fully differential mode with an input referred noise of 67pArms in 32Hz band and 102dB in single -ended mode with an input referred noise of 582pArms.

Robust H∞ Takagi–Sugeno fuzzy output-feedback control for differential speed steering vehicles

This paper studied the modelling and control of four-wheel independently driven electric vehicles using differential speed steering. The Takagi–Sugeno fuzzy modelling approach represents the nonlinearities of the four-wheel independently driven electric vehicle state variables in several system models. The proposed controller design is a robust Takagi–Sugeno fuzzy output-feedback control based on a fuzzy Lyapunov function approach. More precisely, the Lyapunov function is chosen to be dependent on the membership functions. Sufficient conditions for the existence of the robust Takagi–Sugeno fuzzy controller are given in terms of linear matrix inequality constraints. The designed parameters are tested by simulating the four-wheel independently driven electric vehicles under varying operating conditions. The simulation results underscore the robustness and disturbance rejection importance of the proposed controller, which is then contrasted to better highlight the improved performance of the proposed approach over a fixed robust controller design.

Biomechanical Relationships Between Manual Wheelchair Steering and the Position of the Human Body's Center of Gravity.

The purpose of this investigation was to analyze the impact of differential steering of a wheelchair with a pushrim on changes in the position of the body's center of gravity. The method assumed measuring the wheelchair trajectory and the body's center of gravity and determining the transverse relocation of the measured body's center of gravity in relation to a point on the wheelchair trajectory. Twenty-seven measurement tests which demonstrated various wheelchair trajectories were carried out within the investigation. The trajectories were 10 to 15 m long and involved moving forward (test 2), reversing (test 3), turning left (test 1) and right (test 4). The factor of deviation of the center of gravity of human body from the wheelchair trajectory was determined for selected characteristic turning maneuvers. The measured values ranged from 51 to 192 mm. The impact of the wheelchair trajectory on the position of the body's center of gravity was demonstrated as a result of this investigation. Consequently, a trajectory deviation factor for relocation of the human body weight on one side of the wheelchair has been demonstrated.

Coordinated Chassis Control of 4WD Vehicles Utilizing Differential Braking, Traction Distribution and Active Front Steering

This paper proposes a coordinated chassis control (CCC) utilizing four-wheel differential braking, electronically controlled real-time four-wheel drive (4WD) and active front steering (AFS), aiming to improve the driving performance and handling stability during cornering. First, the performance of the single system is tested; then the hierarchical-structure control algorithm is designed: a supervisory controller to monitor vehicle states and determine the desired yaw rate, upper-level controller to decide the desired longitudinal forces and the desired yaw moment based on the driver intention and the consideration of vehicle stability, and the control allocation layer to distribute the actual control inputs to the actuators applying an optimal control allocation algorithm. Simulations of moderate driving/aggressive deceleration scenarios and a comprehensive test on a handling road are conducted to validate the effectiveness of the proposed control algorithm. The results of the simulations suggest that the proposed algorithm can effectively improve the driving speed in limit cornering without losing lateral stability, and reduce the tire dissipation energy compared with other control algorithms such as the electronic stability control system, the four wheel independent brake system and an integrated chassis control system proposed in a previous research.

Design and Implementation of the Maze Patrolling with Three Branch Roads by the Smart Car Based on 51 Single Chip Microcomputer

With the rapid development of technology, the application of artificial intelligence technology in life is becoming more and more extensive, and intelligent robots play an important role in life. A smart car that can carry out the maze patrolling of three branch roads is designed. This smart car is mainly controlled by the STC89C52 chip and driven by the L298N chip. In this work, the ground information is firstly collected and transformed by the 4-channel TCRT5000 infrared reflection sensor module. Then, TCRT5000 infrared reflection sensor module converts the collected ground information into digital signals and transmits them to the main control chip. Finally, the recognition of the road and the control command such as go forward, turn left and turn right can be implemented through the main control chip. The power system of the smart car is composed of the L298N motor drive module and two DC motors. The main control chip controls the rotation speed and steering of the two DC motors separately, and uses the principle of differential steering to achieve left and right steering. The design uses sensor technology and uses C language for programming, so that the car automatically recognizes the three-way road. This design can be used in driverless vehicles and artificial intelligence related fields.

Position Control of a Mobile Robot through PID Controller

Abstract In this paper, the implementation and tuning steps of the PID controllers were proposed for the position control of a mobile robot with differential steering. The purpose of this robot was the participation in a European amateur robotics contest, the mobile robot being developed in the Engineering Faculty of Sibiu, Department of Industrial Machines and Equipment. After a brief introduction of the mobile entertainment robot, followed by description of the robot’s different components and traction principles, several principles of tuning the PID controller for the mobile robot are presented. The paper ends with some general conclusions based upon the results obtained from studying the research and considering all the ideas that were introduced.

Research On Differential Steering Control Strategy Of Distributed Electric Drive Vehicle

Research On Differential Steering Control Strategy Of Distributed Electric Drive Vehicle

Differential steering-based electric vehicle lateral dynamics control with rollover consideration

This article investigates the differential steering-based schema to control the lateral and rollover motions of the in-wheel motor-driven electric vehicles. Generated from the different torque of the front two wheels, the differential steering control schema will be activated to function the driver’s request when the regular steering system is in failure, thus avoiding dangerous consequences for in-wheel motor electric vehicles. On the contrary, when the vehicle is approaching rollover, the torque difference between the front two wheels will be decreased rapidly, resulting in failure of differential steering. Then, the vehicle rollover characteristic is also considered in the control system to enhance the efficiency of the differential steering. In addition, to handle the low cost measurement problem of the reference of front wheel steering angle and the lateral velocity, an [Formula: see text] observer-based control schema is presented to regulate the vehicle stability and handling performance, simultaneously. Finally, the simulation is performed based on the CarSim–Simulink platform, and the results validate the effectiveness of the proposed control schema.

Control Method of Differential Power Steering for Port Locomotive Obstacle Avoidance under Emergency

Tian, J.; Liu, C. and Chen, N., 2018. Control method of differential power steering for port locomotive obstacle avoidance under emergency. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 531–539. Coconut Creek (Florida), ISSN 0749-0208.At present, there is not much space in the port area and the differential power steering control method is often used in locomotive obstacle avoidance under emergency. The method does not take into account the effect of tire slip and actuator torque limitation on locomotive drive braking during the avoidance under emergency, which only relies on the differential control, that is limited in improving steering stability. Based on the establishment of the dynamic model of the controlled object as well as the nonlinear tire model, the constraints of the locomotive driven by the ground characteristics of the port area, the tire slip and the actuator torque are considered, and the design is based on the differential Power steering controller. According to the deviation of yaw rate and yaw rate of center of mass, the related control characteristic quantity is determined, and the result is the control target to improve the steering performance of the locomotive. The actual locomotive test results showed that the proposed controller design method reduces the brake deceleration of the port locomotive in the process of emergency braking, which achieves the best slip ratio effect, shortens the braking distance, improves the braking efficiencyof the locomotives and improves the port traffic safety.

Design of Automated Guided Vehicle for Conveying Objects

STC90C516RD + microcontroller was chosen as the core controller of AGV. The magnetic line was detected by Hall sensor, the tracking function of AGV is realized, the ultrasonic ranging function was used to avoid obstacles, and the differential steering of the car was realized by using the output PWM wave, after installation and debugging, AGV can basically achieve the requirement of conveying objects.

A Novel Integrated Stability Control Based on Differential Braking and Active Steering for Four-axle Trucks

Differential braking and active steering have already been integrated to overcome their shortcomings. However, existing research mainly focuses on two-axle vehicles and controllers are mostly designed to use one control method to improve the other. Moreover, many experiments are needed to improve the robustness; therefore, these control methods are underutilized. This paper proposes an integrated control system specially designed for multi-axle vehicles, in which the desired lateral force and yaw moment of vehicles are determined by the sliding mode control algorithm. The output of the sliding mode control is distributed to the suitable wheels based on the abilities and potentials of the two control methods. Moreover, in this method, fewer experiments are needed, and the robustness and simultaneity are both guaranteed. To simplify the optimization system and to improve the computation speed, seven simple optimization subsystems are designed for the determination of control outputs on each wheel. The simulation results show that the proposed controller obviously enhances the stability of multi-axle trucks. The system improves 68% of the safe velocity, and its performance is much better than both differential braking and active steering. This research proposes an integrated control system that can simultaneously invoke differential braking and active steering of multi-axle vehicles to fully utilize the abilities and potentials of the two control methods.

Fault‐tolerant path‐following control for in‐wheel‐motor‐driven autonomous ground vehicles with differential steering

AbstractOver the past several decades, the automobile industry has denoted significant research efforts to developing in‐wheel‐motor‐driven autonomous ground vehicles (IWM‐AGVs) with active front‐wheel steering. One of the most fundamental issues for IWM‐AGVs is path following, which is important for automated driving to ensure that the vehicle can track a target‐planned path during local navigation. However, the path‐following task may fail if the system experiences a stuck fault in the active front‐wheel steering. In this paper, a fault‐tolerant control (FTC) strategy is presented for the path following of IWM‐AGVs in the presence of a stuck fault in the active front‐wheel steering. For this purpose, differential steering is used to generate differential torque between the left and right wheels in IWM‐AGVs, and an adaptive triple‐step control approach is applied to realize coordinated lateral and longitudinal path‐following maneuvering. The parameter uncertainties for the cornering stiffness and external disturbances are considered to make the vehicles robust to different driving environments. The effectiveness of the proposed scheme is evaluated with a high‐fidelity and full‐car model based on the veDYNA‐Simulink joint platform.

Integrated hierarchical control strategy of active suspension and differential assisted steering system for electric-wheel vehicle

In order to solve the performance decrease of riding comfort and handling stability caused by the increase of unsprung mass for the electricwheel vehicle, an integrated hierarchical control strategy is proposed based on differential assisted steering system (DASS) and active suspension system (ASS). Here, the upper controller is designed to coordinate the overall control strategy and determine the control weight of the two subsystems by the fuzzy control algorithm. Afterwards, for the lower controllers, the linear quadratic optimal algorithm is taken in the differential steering system to determine the additional yaw moment, and the active disturbance rejection control is used in the active suspension system to suppress body vibration and improve riding comfort. The simulation results show that the proposed hierarchical control can effectively improve the riding comfort and handling stability of the electric-wheel vehicle.

Integrated Control With DYC and DSS for 4WID Electric Vehicles

This paper investigates the front-wheel differential steering system (DSS) for a four-wheel independent-drive (4WID) electric vehicle (EV) with a steer-by-wire (SBW) system in case of the steering failure. The nonlinear dynamic model of differential steering vehicle (DSV) is established and the stability regions at different adhesion coefficients are determined based on the theory of phase plane. The traditional front-wheel steering vehicle is selected as the reference model. The direct yaw moment control (DYC) aiming to restore the vehicle to the stability region, and the DSS control aiming to achieve the normal steering function based on the theory of model reference sliding mode control, are researched and applied to the nonlinear dynamic model successively. The direct yaw moment and differential driving torque of the front-wheel needed for the vehicle stability and DSS are obtained respectively. The simulation results show that the proposed integrated control can simultaneously ensure the differential steering and vehicle stability of the nonlinear vehicle on different adhesion coefficient roads.

Integrated hierarchical control strategy of active suspension and differential assisted steering system for electric-wheel vehicle

Integrated hierarchical control strategy of active suspension and differential assisted steering system for electric-wheel vehicle

Coordinated control for path following of two‐wheel independently actuated autonomous ground vehicle

This study investigates the path following control problem about distributed-drive self-driving vehicle through coordinated control of the autonomous front-wheel steering and the differential steering control, to improve the tracking performance. On the basis of the model predictive control algorithm and vehicle dynamic model, the preview time adaptive control of path following is proposed to realise path following with changing preview time in straight and turning conditions. Considering the characteristics of the distributed-drive self-driving vehicle, the differential torque control is utilised based on the reference heading angle to realise trajectory tracking under the condition of constant torque demands. To integrate the advantages of the two methods, coordinated control of trajectory tracking based on the autonomous steering and differential steering is performed by setting the weight coefficients method. MATLAB co-simulation with Carsim and road testing validation are executed, and both demonstrate that the coordinated control strategy can not only effectively improve the response speed and flexibility of steering, but also improve the reliability and accuracy of trajectory tracking.

Differential Steering Control of Four-Wheel Independent-Drive Electric Vehicles

This paper investigates the skid steering of four-wheel independent-drive (4WID) electric vehicles (EV) and a differential steering of a 4WID EV with a steer-by-wire (SBW) system in case of steering failure. The dynamic models of skid steering vehicle (SSV) and differential steering vehicle (DSV) are established and the traditional front-wheel steering vehicle with neutral steering characteristics is selected as the reference model. On this basis, sideslip angle observer and two different sliding mode variable structure controllers for SSV and DSV are designed respectively. Co-simulation results of CarSim and Simulink show that the designed controller for DSV not only controls the yaw rate and sideslip angle of DSV to track those of the reference model exactly, but also ensures the robustness of the controlled system compared with the designed controller for SSV. And the differential driving torque needed to realize the differential steering is much smaller than that for skid steering, which indicates the possibility of the differential steering in case of steering failure.

Lane keeping of autonomous vehicles based on differential steering with adaptive multivariable super-twisting control

Abstract This paper investigates the lane keeping control for four-wheel independently actuated autonomous vehicles. To guarantee the vehicle safety when the active-steering motor entirely fails, the steering manoeuvre is realized by the differential drive assisted steering (DDAS) that is generated by the differential moment between the front wheels. A novel adaptive multivariable super-twisting control strategy is proposed to realize the control objective in finite time, considering the multiple unknown and mismatched disturbances of the steering system with the chattering effect removed. In the sliding surface, a nonlinear function is designed to adaptively change the damping ratio of the closed-loop system so as to improve the transient performance of the lane keeping control in the faulty steering condition. The controller design has avoided the use of the lateral velocity which is usually hard to measure in practice. Instead, the lane keeping errors and their time derivatives are estimated with a high-order sliding mode observer based on a vision system. The finite-time convergence of the closed-loop system is proved by the Lyapunov method. Results of CarSim-Simulink simulations with the proposed control strategy compared with a tradition sliding mode controller based on a high-fidelity and full-car model have verified the effectiveness and robustness of the proposed controller in the lane keeping control via DDAS with the guaranteed high performance.

Robust H∞ Output-Feedback Yaw Control for Vehicles with Differential Steering

This paper examines the problem of designing a robust H∞ output-feedback yaw controller with both input and output constraints for four-wheel independently driven in-wheel electric vehicles (EVs) with differential steering. Specifically, the controller aims are to ensure the stability and improve the performance of the EV despite variations in the road adhesion coefficient, longitudinal velocity, and external disturbance. Based on the linear matrix inequalities approach, sufficient conditions for the existence of an H∞ output-feedback controller for linear systems with polytopic uncertainties, and input and control output constraints, are derived. Then those sufficient conditions are utilized to design an H∞ output-feedback yaw controller that guarantees the robust performance and stability of an EV over a wider range of road conditions. Finally, the capability of the developed controller is simulated on a vehicle model with uncertain road conditions and longitudinal velocities.

Coupling Control Strategy of Force and Displacement for Electric Differential Power Steering System of Electric Vehicle With Motorized Wheels

This paper presents a coupling control strategy of force and displacement for an electric differential power steering (EDPS) system to improve steering maneuverability and handling stability of electric vehicles with motorized wheels. In order to investigate mutual influences between vehicles and drivers, models of the EDPS system, the vehicle, the tire as well as the actuate motor are introduced. Then, by analyzing key factors that affect the interaction between vehicles and drivers, the optimum hand wheel torque of the EDPS system is developed and actualized by torque difference between two front wheels based on the ${\text{H}}_{2}{\text{/ H}}_{{{\infty }}}$ control method. In addition, a yaw rate control method is schemed to diminish the yaw moment interference to vehicles caused by the torque difference between two front wheels, and μ-synthesis theory is applied here to improve the yaw rate tracking performance as well as attenuate influences of system uncertainties and disturbances. Finally, simulations by MATLAB/Simulink and hardware-in-the-loop experiments based on dSPACE are conducted and effectiveness of the proposed control strategy is demonstrated by simulation and experiment results and numerical analyses.