Control Method For Vehicle Research Articles

Robust predictive path-following control of autonomous ground vehicle with input delays

ABSTRACT This paper introduces a path-following control method for autonomous ground vehicle with significant input delays. First, a vehicle path-following model including input delay is developed. Then, a robust predictive controller design is developed, in which a delay estimator as well as a state predictor is adopted so that control law design as well as controller gain calculation can be conducted without considering the input delay. Thus, the controller synthesis work can be greatly simplified. Finally, comparative co-simulation tests with Matlab/Simulink and Carsim are presented to verify the efficiency as well as the performance of the proposed path-following control approach.

Study on multi-objective adaptive cruise control of intelligent vehicle based on multi-mode switching

Aiming at the problems of slow response, poor comfort and high fuel consumption of the existing adaptive cruise control system under complex operating conditions, a multi-objective adaptive cruise control method of intelligent vehicles based on multi-mode switching is proposed. Firstly, the overall scheme of the adaptive cruise control system is designed by using the hierarchical control structure, and the multi-mode switching strategy is designed by using the fuzzy control theory to realize the division and switching of the working modes during vehicle cruise. Secondly, based on the variable spacing strategy and longitudinal kinematics model, the multi-objective of safety, following performance, fuel economy and comfort is analyzed and carried out, and a quadratic multi-objective optimization function based on multi constraints is obtained. Then, the model predictive control algorithm based on particle swarm optimization (PSO) is used to transform multi-objective function into a standard form with predictive control increment as the optimization variable, and the optimal control rate is solved. Finally, the simulation experiment is carried out by setting three complex working conditions: the preceding vehicle uniform speed change, the preceding vehicle rapid speed change and the adjacent vehicle cut in. The results show that the proposed method can meet the requirements of safety, comfort and fuel economy, and can improve the adaptability and friendliness of intelligent vehicle cruise control system.

Adaptive multivariate reusable launch vehicles reentry attitude control with pre-specified performance in the presence of unmatched disturbances

This paper introduces a novel adaptive multivariable attitude control method for a reusable launch vehicle (RLV) to track desired attitude trajectories in the presence of unknown external disturbances and uncertainties. Unlike most existing designs that overlook mismatched disturbances, this method employs an adaptive finite-time observer (AFO) to estimate the unknown states. Based on the outputs of the AFO and the prescribed performance function, a time-varying adaptive gain that is not overestimated is designed to establish the adaptive multivariable attitude control for the RLV system. The simulations demonstrate that the proposed approach successfully guides the RLV to follow desired attitude signals despite the presence of unmatched disturbances and uncertainties.

Autonomous trajectory tracking control method for an agricultural robotic vehicle

Autonomous trajectory tracking control method for an agricultural robotic vehicle

A Longitudinal and Lateral Coordinated Control Method of Autonomous Vehicles Considering Time-varying Delay

A Longitudinal and Lateral Coordinated Control Method of Autonomous Vehicles Considering Time-varying Delay

A Formation Control and Obstacle Avoidance Method for Multiple Unmanned Surface Vehicles

This study introduces a method for formation control and obstacle avoidance for multiple unmanned surface vehicles (USVs) by combining an artificial potential field with the virtual structure method. The approach involves a leader–follower formation structure, where the leader autonomously avoids collisions using an artificial potential field based on the target’s position as a reference. It also determines the ideal position of each follower in the formation based on its own position, heading angle, and the formation structure. To effectively avoid obstacles and maintain formation, the follower selects the position of the target or its ideal position as a reference during movement, depending on whether it is being repelled by obstacles. Additionally, this paper modifies the attractive force model of the traditional artificial potential field method to restrict the maximum magnitude of the attractive force when encountering repulsive forces, thus expediting departure from obstacle areas. The dynamic characteristics of USVs are taken into account by constraining the maximum linear speed and angular speed. Formation stability is ensured by maintaining a constant speed for the leader, while the linear speed of the follower varies based on the distance to the reference object during movement. Simulation experiments demonstrated that this method can effectively avoid obstacles and maintain formation.

Reinforcement learning-based formation-surrounding control for multiple quadrotor UAVs pursuit-evasion games

This paper proposes a reinforcement learning-based formation-surrounding control method for multiple quadrotor unmanned aerial vehicles (UAVs) pursuit-evasion (MPE) games system subject to external disturbances. In the framework of the MPE games, the pursuers aim to equally surround the evaders which try to avoid being surrounded when forming the desired formation. By constructing position and attitude tracking error subsystems of quadrotor UAV, this paper proposes two control strategies which combines the feedforward control technique and reinforcement learning (RL) method. First, two novel cost functions are presented for the quadrotor UAV with external disturbances. Then, two control schemes based on RL have been developed to guarantee the stability of the tracking error subsystem. Subsequently, two critic-only neural networks (NN) weight update laws that only satisfy finite excitation conditions are proposed to estimate the optimal cost function. Furthermore, Nash equilibrium for multiple quadrotor UAVs is achieved by means of RL strategy to solve the Hamilton-Jacobi-Isaacs (HJI) equations. And the property of equally surrounding is proved for the first time by utilizing Euler's formula in this paper. Finally, the numerical simulation results are given to show the effectiveness and superior performance of the proposed control method.

An integration planning and control method of intelligent vehicles based on the iterative linear quadratic regulator

This paper proposes an integrated strategy of planning and control to address the poor quality of the generated trajectory by intelligent vehicles. The trajectory planner is designed based on the iterative linear quadratic regulator (ILQR) theory, taking into account the nonlinear dynamics of the vehicle in the trajectory planning layer. The planner directly outputs the control commands that act on the actuator, achieving the integration of planning and control. To improve the control performance of the trajectory planner under extreme operating conditions, a stability controller is developed using the sliding mode control method (SMC). Additionally, a torque distributor is designed to coordinate the control requirements of the trajectory planner and the stability controller, with the optimization goal of minimizing the tire loading rate. Finally, complex scenario tests are carried out under various working conditions to evaluate the performance of the integrated strategy. The results indicate that the integrated strategy outperforms the decoupled strategy in terms of control performance and exhibits better adaptability across various working conditions and scenarios. Even if the reference trajectory is unreasonable, the vehicle can still perform smooth, efficient, and comfortable obstacle avoidance and lane-changing maneuvers. By working in tandem, the stability controller and the trajectory planner can expand the planning and control boundaries of the system, thereby significantly enhancing the system's ability to respond to extreme working conditions.

Layered energy-saving speed planning and control method for electric vehicle on continuous signal lights road

Emergency start-stop in front of signal lights is one of the main reasons for additional energy consumption and ride discomfort of Electric Vehicle (EV). Existing research on this issue rarely takes into account both energy consumption and ride comfort. Therefore, the layered energy-saving speed planning and control method is proposed. The upper is the layer of energy-saving speed planning. This layer reduces energy consumption of EV by reducing the number of stops on continuous signal lights road and minimizing the range of speed change. On this basis, the sinusoidal variable speed curve is used to smooth the acceleration process to improve ride comfort. Finally, the energy-saving speed considering ride comfort is obtained. This layer makes up for the issue that existing research rarely takes into account both energy consumption and ride comfort of EV, and is an extension and innovation of existing research. The lower is the layer of Model Predictive Controller (MPC)-based speed control. Based on the longitudinal dynamics model of EV, the MPC-based speed controller is established to control EV to track the energy-saving speed. The controller is easy to understand and implement, and it is also suitable for other research on EV, which has certain application value. The simulation results show that under various working conditions, the maximum energy consumption of EV passing through continuous signal lights road without stopping is 604.29 kJ/km, and the minimum is 244.76 kJ/km. The energy consumption is lower than that of actual road test, and it can be saved by 23.18 % compared with the method in the same field. The maximum Root Mean Square of accelerations (RMSa) is 0.25 m/s2, and the minimum is 0.10 m/s2. The values of RMSa above are lower than 0.315 m/s2, which indicates that the ride comfort is good. The utilized method can reduce energy consumption of EV, improve its range and ride comfort, which has important reference significance for promoting the development of EV.

Risk-informed decision-making and control strategies for autonomous vehicles in emergency situations

This paper proposes risk-informed decision-making and control methods for autonomous vehicles (AVs) under severe driving conditions, where many vehicle interactions occur on slippery roads. We assume that the AV should approach a specific safe zone in case of vehicle malfunctioning. In normal situations, the driving behavior of the AV is based on the deterministic finite-state machine (FSM) that makes an appropriate real-time decision depending on the driving condition, which is efficient when compared with some conventional decision-making algorithms; alternatively, in emergency situations, the AV first has to be prevented the rear-end conflicts while the specific safe zone is simultaneously determined by evaluating the level of risk via two safety level indicators, i.e., Time-To-Collision (TTC) and Deceleration Rate to Avoid the Crash (DRAC). The safe path that guides the AV to avoid car crashes is generated based on the trajectory optimization theory (i.e., Pontryagin maximum principle), and the AV follows it based on the linear time-varying model predictive control (LTV-MPC), which ensures the AV’s lateral stability. We verify the effectiveness of the proposed decision-making and control strategies in various test scenarios, and the results show that the AV behaves appropriately according to the behaviors of surrounding vehicles and road condition.

An Integrated Control Approach for Shifting Process of Single-Axis Parallel Hybrid Electric Vehicle with a Multi-Speed AMT Gearbox

When a single-axis parallel hybrid electric vehicle (HEV) equipped with a multi-speed AMT gearbox is in its shifting process, the superposition of dynamic characteristics of multiple power sources and the intervention and withdrawal of AMT transmissions can easily cause significant vehicle longitudinal jerk. To achieve rapid and smooth output changes during the shifting process, this paper proposes an integrated multi-stage robust shifting control method for a single-axis parallel hybrid electric vehicles with a multi-speed AMT gearbox. First, models of key driveline components are constructed, and the shifting process is divided into five stages to provide a clear description of the control problem. Subsequently, we reproduce an integrated multistage robust control method to achieve favorable switching performance and control robustness under external disturbances. We propose a data-driven model predictive control strategy based on additional constraints in the torque unloading and recovery phases. Simultaneously, we present a joint control algorithm that integrates the optimal control and disturbance suppression in the speed synchronization phase. In addition, we develop a sliding mode auto-disturbance rejection control algorithm to achieve accurate position tracking of the shift actuator in the pickup and engage phases. Finally, simulations and bench tests are carried out to verify the effectiveness of the robust control method under different driving conditions. The results demonstrate that the proposed control method can not only coordinate the torque across different power sources and clutch while minimizing vehicle longitudinal jerk, shift time, and friction work, but also provides apparent robustness to model uncertainties and external disturbance. Therefore, the proposed method may offer a theoretical reference for the actual vehicle controller during shifting.

Autonomous charging docking control method for unmanned vehicles based on vision and infrared

Unmanned vehicle charging is part of the autonomous workflow of unmanned vehicles. Most existing unmanned vehicles mostly rely on manual battery change or manual charging, which cannot realize autonomous charging. In order to achieve simpler and safer autonomous charging for unmanned vehicles, this paper proposes a new intelligent unmanned vehicle autonomous charging docking method based on infrared guidance and vision assistance. Firstly, the autonomous charging device and intelligent charging stand for unmanned vehicles are designed, and for the unmanned vehicle, charging is not easy to align and easy to detach when charging. The camber-type electric core and charging adsorption device are designed, respectively, and the autonomous charging docking device is designed. Secondly, in order to ensure the accuracy of the docking between the unmanned vehicle and the intelligent charging stand, the unmanned vehicle autonomous charging method is proposed. The combination method of infrared and vision adjusts the posture of the unmanned vehicle. Finally, a protection method of autonomous charging docking based on ultrasonic ranging of unmanned vehicles is proposed. The communication and ranging modules on the unmanned vehicle and intelligent charging stand are designed to prevent mistouching and obstacle avoidance to ensure the safety of the system. The experiment results show that the docking method of this unmanned vehicle autonomous charging system is accurate, efficient, and safe, which can satisfy the demand for unmanned vehicle autonomous charging.

Research on high-speed railway vehicle emergency braking control based on rail surface foreign matter identification

In order to improve the operation stability of high-speed railway vehicles, an emergency braking control method for high-speed railway vehicles based on the identification of foreign matters on the track surface is proposed. The dynamic frame scanning method is used to build the image acquisition of abnormal objects on the high-speed rail track surface, and the visual sensor and vibration sensor are used to identify and process the features of foreign objects on the high-speed rail track surface. According to the abnormal feature extraction results, the command signal in case of foreign objects is transmitted to the terminal command library of the braking control system. According to the transfer switch of the emergency braking system to display the main emergency disposal output states such as the train emergency disposal information reception, emergency disposal level, emergency disposal type and other information, the joint control method of contact pressure distribution and non-uniform heat flux is adopted, and the joint control method of control system, drive system, disc friction system and signal acquisition system is adopted. The emergency braking control module is established to realize the emergency braking control of high-speed railway vehicles according to the feature recognition results of foreign matters on the rail surface. The test results show that the control module is less affected by the vehicle wheelbase characteristics, track structure characteristics and other factors when using this method for high-speed railway vehicle emergency braking control, and has a strong ability to identify the characteristics of foreign matters on the track surface, which improves the stability and real-time performance of emergency braking.

End-to-End Control Method for Unmanned Vehicle Based on Knowledge Distillation

In order to construct a lightweight end-to-end autonomous driving model, knowledge distillation technology is introduced into the construction of the model. The model is composed of a vehicle trajectory orientation marker point prediction algorithm and a motion control algorithm. The prediction algorithm uses the Resnet34 with high precision as a teacher network and the Squeezenet with fast speed as a student network. Based on the knowledge distillation technology, the prediction ability of the teacher network is transferred to the student network so that the student network can predict a marker point accurately and quickly. The control algorithm is constructed based on the integral-differential model, and the predicted marker point is converted into lateral control commands of a vehicle. Through the experimental analysis of the complexity of the model, prediction accuracy of the marker point, and actual vehicle deployment effect, it is verified that the proposed model can control a vehicle to drive accurately and uniformly along a lane line trajectory.

Steering angle sensorless control for four-wheel steering vehicle via sliding mode control method

This paper presents a new sensorless control method for four-wheel steering vehicles. Compared to the existing sensor-based control, this approach improved dynamic stability, manoeuvrability and robustness in case of malfunction of the front steering angle sensor. It also provided a software redundancy and backup solution, as well as improved fault tolerance. The strategy of the sensorless control is based on the sliding mode method to estimate the replacement of the front steering input from the errors between the vehicle’s measured and desired values of the vehicle’s sideslip angle and yaw rate. The simulation results demonstrate that the observer effectively estimated the front wheel steering angle at both low- and high-speed scenarios in the cornering and lane change manoeuvres. Furthermore, the sensorless control approach can achieve equivalent control performances to the sensor-based controller including a small and stable yaw rate response and zero sideslip angle. The results of the study offer a potential solution for improving manoeuvrability, stability and sensor fault tolerance of four-wheel steering vehicles.

Coordinated Control Design for Ethical Maneuvering of Autonomous Vehicles

This paper proposes a coordinated control design method, with which the autonomous vehicle is able to perform ethical maneuvers. The starting point of the provided method is a thorough analysis on the ethical concepts for autonomous vehicle control design methods. Using the results of the analysis, an own concept is provided based on some principles of Protestant ethics. The concept focuses on improving trust in vehicle control through clear rules and predictable vehicle motion, and it is in line with the state-of-the-art ethical vehicle control methods. Moreover, an optimal Model Predictive Control (MPC) design method is formed, in which the provided ethical concept is incorporated. The outputs of the optimal control are steering angle and velocity profile, with which the ethical maneuvering can be achieved. The contribution of the paper is a coordinated control design method, which is able to involve ethical principles. Moreover, the application of Protestant ethics in this context is also a novel achievement in the paper. The effectiveness of the method through different simulation scenarios is illustrated.

Robust Switched Velocity-Dependent Path-Following Control for Autonomous Ground Vehicles

This paper proposes a switched velocity-dependent path-following control method for autonomous ground vehicles under uncertain cornering stiffness and time-varying velocity. A switched polytopic linear-parameter-varying (LPV) model combining path-following and vehicle lateral dynamics is established, where the velocity-dependent parameters are divided into several switched regions. In each region, a trapezoidal polytope is adopted to describe the varying parameters. A global <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty}$</tex-math> </inline-formula> performance analysis is carried out for the switched polytopic LPV vehicle system based on the average dwell time approach with multiple Lyapunov functions. Based on the analysis, a switched velocity-dependent controller is synthesized to achieve a desired path-following performance by regulating the steering angle of the front wheels. The proposed switched path-following control specializes in handling large range of varying velocity, and achieves superior path-following performance compared with the conventional gain-scheduling control. Simulations are carried out for typical road maneuvers to illustrate the advantages of the proposed method. The results are also applicable to other LPV analysis and synthesis conditions involving time-varying parameters of large varying ranges.

Automatic Emergency Collision Avoidance of Straight-Crossing Intelligent Vehicle at a 90-Degree Intersection Based on Vehicle-to-Everything Technology

&lt;div&gt;In order to reduce collision at a 90-degree intersection, an automatic emergency collision avoidance control method for intelligent vehicles based on vehicle-to-everything (V2X) technology is proposed. Most of the existing automatic emergency braking (AEB) control algorithms are designed for a single high-friction road with reference to the European New Car Assessment Programme (Euro NCAP) evaluation procedures, and they do not consider changes in road friction. Thus, it may be difficult to avoid collision successfully on a low-friction road. Although some studies have considered the variation of road friction, they are only applicable to straight-line rear-end collisions and cannot be directly applied to intersections. In addition, most studies regard the vehicle only as a particle, ignoring the actual dynamic characteristics of the vehicle. The main contribution of this article is to present an AEB control strategy by V2X technology, which can make the intelligent vehicle avoid collisions at a 90-degree intersection effectively. The proposed time-to-collision (TTC) adaptive algorithm has considered various road surfaces, and its effectiveness is verified by the co-simulation of Matlab/Simulink, CarSim, and Prescan on a typical urban intersection road.&lt;/div&gt;

Formula omitted]-Synthesis robust coordinated control of variable speed wind power generators and electric vehicles to regulate frequency

Variable speed wind power generators (VSWPGs) can inevitably introduce power fluctuations and reduce the system inertia in modern power systems. On the other hand, VSWPGs also have certain frequency support ability due to the fast control characteristics of the power electronics in the converters. Therefore, it is urgently required for VSWPGs to regulate the frequency of the power system. Taking into consideration the internal and external uncertainty in the power systems and that frequent regulation actions of VSWPGs might lead to mechanical failures and aggravate the aging process of the wind power generators, a coordinated control method of VSWPGs and electric vehicles (EVs) for frequency regulation on the basis of μ-synthesis control is proposed in this paper. The EVs are modeled as energy aggregators, the VSWPGs are modeled under the derating control using the small-signal analysis method, and the dynamic frequency response model for the system with uncertainty is then built. Considering the power system parametric uncertainty, a μ-synthesis controller is implemented to tackle the coordinated control problem of VSWPGs and EVs regulating system frequency by means of the D-K iterative method. Then the comparisons through time-domain simulations are conducted to verify the presented coordinated strategy is able to overcome influence of uncertainty on system frequency and also has better dynamic frequency performance.

Adaptive fault‐tolerant attitude tracking control for hypersonic vehicle with unknown inertial matrix and states constraints

AbstractThis paper proposes an adaptive fault‐tolerant control (FTC) method for hypersonic vehicle (HSV) with unexpected centroid shift, actuator fault, time‐varying full state constraints, and input saturation. The occurrence of unexpected centroid shift has three main effects on the HSV system, which are system uncertainties, eccentric moments, and variation of input matrix. In order to ensure the time‐varying state constraints, a novel attitude state constraint control strategy, to keep the safe flight of HSV, is technically proposed by a time‐varying state constraint function (TVSCF). A unified controller is designed to handle the time‐varying state constraints according to the proposed TVSCF. Then, the constrained HSV system can be transformed into a novel free‐constrained system based on the TVSCF. For the variation of system input matrix, input saturation and actuator fault, a special Nussbaum‐type function is designed to compensate for those time‐varying nonlinear terms. Additionally, the auxiliary systems is designed to compensate the constraint of system control inputs. Then, it is proved that the proposed control scheme can guarantee the boundedness of all closed‐loop signals based on the Lyapunov stability theory. At last, the simulation results are provided to demonstrate the effectiveness of the proposed fault‐tolerant control scheme.