Integrated planning and control method for autonomous driving considering user’s steering style

Vehicle driving safety is the urgent key problem to be solved of automobile independent development while encountering collision avoidance. It is also the premise and one of the necessary conditions of vehicle active safety. A new technique for vehicle collision avoidance was proposed. Based on the artificial potential field theory, the lane potential, the road potential function and the obstacle potential function as well as the velocity potential function of the vehicle were constructed. Then the potential function of the vehicle obstacle avoidance problem was constructed with the three potential functions above. The vehicle obstacle avoidance problem was then converted into an optimization problem. The trajectory of the vehicle in the obstacle avoidance process was obtained by solving the optimal control problem. The simulation results show that the proposed method can solve the collision avoidance problem and provide the lane keeping and lane change problem with theoretical support

Following an investigation undertaken by the publisher, we have determined that this paper was accepted on the basis of a compromised peer review process. We hereby retract the paper. The corresponding author has been notified of the retraction. The retraction statement can be found here: https://doi.org/10.1520/JTE20269997. In order to address the obstacle avoidance problem of driverless vehicles in hospital environment, a local path planning method based on model predictive control is proposed. Firstly, the potential field model of driving environment factors including obstacles, environmental vehicles, roads, and target points is established by using artificial potential field theory. Then, based on model predictive control algorithm combined with driving environment potential field, trajectory planning and tracking are transformed into a unified constrained optimization problem. The objective function and constraint conditions of local path planning for unmanned vehicles are designed, and roll is introduced to the dynamic optimization mechanism. The simulation results show that the error between the path planning and the expected path is less than 0.1 m, the time consumption is at least 3.3 s, and it has strong robustness, which can effectively solve the obstacle avoidance problem of local path of unmanned vehicles.

Considering the influence of lateral distance on consecutive vehicles, this paper proposes a new car following model based on the artificial potential field theory (APF). Traditional car following behaviors all assume that the vehicles are driving along the middle of a lane. Different from the traditional car following principles, this incorporation of APF offers a potential breakthrough in the fields of car following theory. The individual vehicle can be represented as a unit point charge in electric field, and the interaction of the attractive potential energy and the repellent potential energy between vehicles simplifies the various influence factors on the target vehicle in actual following behavior. Consequently, it can make a better analysis of the following behavior under the lateral separation. Then, the proposed model has been demonstrated in simulation environment, through which the space-time trajectories and the potential energy change regulation are obtained. Simulations verify that the following vehicle's behavior is vulnerable to be affected by lateral distance, where the attractive potential energy tends to become repellent potential energy as the longitudinal distance decreases. The search results prove that the proposed model quantifies the relations between headway and potential energy and better reflects the following process in real-world situation.

Optimal trajectory planning of 6 DOF manipulator using meta- heuristics integrated with artificial potential field theory

The Westinghouse AP1000™ nuclear power plant design uses several evolutionary and advanced components, systems and analysis methods in order to maximize plant operational safety and efficiency. One advanced component of the AP1000 is the integration of the MSHIM operation and control strategy within the plant design. As a summary, the MSHIM operation and control strategy is an operational philosophy that has evolved from the Constant Axial Offset Control (CAOC) strategy, which was originally developed for the current generation of Westinghouse PWRs. The term MSHIM is derived from the fact that reactivity control uses low worth (or gray) control rod banks as a “mechanical shim.” This is opposed to today’s PWRs, which depend largely on changes in the chemical shim (soluble boron) concentration in the reactor coolant in order to provide fine reactivity control. The MSHIM strategy is unique in that it makes use of two independently controlled rod groups to provide fine control of both the core reactivity and axial power distribution during a wide range of operational scenarios. In the AP1000, the MSHIM operation and control strategy has been fully integrated into the digital rod control system. Specifically, automatic control of core reactivity (or RCS temperature) is provided using four (4) banks of “gray” control rods and two (2) banks of traditional control rods, all moving in a defined overlap. Furthermore, automatic axial power distribution (i.e., ex-core ΔI) control is provided using a single, heavy bank of traditional control rods which move independently of the reactivity control banks. It has been demonstrated that fine control of core reactivity and axial power distribution control can be achieved during a wide range of operational scenarios while relying only upon the automatic rod control functionality. Changes in the concentration of the chemical shim within the reactor coolant can thus be limited to only that required to directly compensate fuel and/or burnable absorber depletion during a given fuel cycle. In the AP1000, the MSHIM operation and control strategy is complemented by the BEACON™ on-line core monitoring system. BEACON provides direct monitoring of power distribution related parameters such as departure from nucleate boiling ratio (DNBR), peak linear heat rate (PLHR), and shutdown margin (SDM). The integration of the BEACON monitoring system into the AP1000 plant increases operational flexibility by relaxing certain operational limits during BEACON operation. The net effect of BEACON integration, thus, is to maximize the ability of rod control under the MSHIM strategy to maintain reactor operation within the associated technical specification limits, even under adverse operational transients. This paper explores the robustness of the MSHIM operation and control strategy under a range of anticipated plant operational scenarios. Furthermore, this paper demonstrates the operational simplification associated with this strategy as it has been integrated into the AP1000 plant control systems.

The study provides the simple method of automatic lateral guidance control. In most of previous studies, control law about automatic guidance control is complex. We were able to simplify guidance control, converting non-holonomic system into holonomic system about lateral movement. The side-force-plate unmanned aerial vehicle (UAV) has capable of turning at low bank angle. The side-force-plate is a wing that is attached nearby the center of gravity. Utilizing characteristic of the side-force-plate, it is able to convert non-holonomic system into holonomic system. Specifically, we enabled UAV to lateral movement using rudder only, stabilizing roll movement by a controller stabilizing attitude. A LQG controller utilized for the sake of stabilizing attitude of UAV. It is able to guidance control utilizing a proportioning controller. In other words, we executed lateral guidance control, feedbacking guidance angular velocity multiplied gain to rudder angle. We verified efficacy of the guidance controller via a flight test.

Modern trackless train has the characteristics of long body and many articulated modules, and the steering control is extremely difficult. This paper first established its Adams dynamic model, and then designed a fuzzy PID controller to generate the yaw moment and rear wheel angle. So that the vehicle can track the trajectory of the first axle when turning. Finally, the control model was established in Matlab and simulated jointly with Adams model. The simulation experiments under step input and sinusoidal input were carried out. The results show that the active steering control strategy based on the combination of direct yaw moment and rear wheel angle can meet the requirements of vehicle steering stability and trajectory following.

With the increase of on-orbit maintenance and support requirements, the application of a space manipulator is becoming more promising. In actual operation, the strong coupling of the free-floating space robot itself and the unknown disturbance of the contact target caused a major challenge to the robot base posture control. Traditional Reaction Null Space (RNS) motion planning and control methods require the construction of precise dynamic models, which is impossible in reality. In order to solve this problem, this paper proposes a new Adaptive Reaction Null Space (ARNS) path planning and control strategy for the contact of free-floating space robots with unknown targets. The ARNS path planning strategy is constructed by the Variable Forgetting Factor Recursive Least Squares (VFF–RLS) algorithm. At the same time, a robust adaptive control strategy based on the Strategy Self-Adaption Differential Evolution–Extreme Learning Machine (SSADE–ELM) algorithm is proposed to track the dynamic changes of the planned path. The algorithm enables us to intelligently learn and compensate for the unknown disturbance. Then, this paper constructs a robust controller to compensate model uncertainty. A striking feature of the proposed strategy is that it does not require an accurate system model or any information about unknown attributes. This design can dynamically implement RNS path tracking performance. Finally, through simulation and experiment, the proposed algorithm is compared with the existing methods to prove its effectiveness and superiority.

In the development of actual vehicles, manufacturers usually adopt a simplified control strategy to ensure the reliability of the control strategy based on the application scenarios. There are two main working modes for the fuel cell system in fuel cell electric vehicles in China. One is the stepped power type, and the other is the following power type. Therefore, the analysis and comparison of these two typical working modes in the power test of fuel cell electric vehicles helps determine how the fuel cell system works in the actual vehicle and how to choose energy management strategies in different application scenarios. We do the actual tests to explore how the two typical control strategies perform in actual vehicles. These two typical control strategies show different characteristics in the same test. It shows that the energy management strategies should be adopted according to the application scenarios and optimization goals. In the stepped power control strategy, the fluctuation of the fuel cell system and the frequency of starting and stopping are significantly reduced, which is beneficial to the durability of the fuel cell system. Compared with the stepped control strategy, the fluctuation of the output power of fuel cell electric vehicles with the following power control strategy increased significantly. At the same time, a simplified state of charge (SOC) test method is proposed. Due to the particularity of the stepped power control strategy, the change of capacity can be used to replace the change of SOC. For the following power control strategy, the change of electric energy can be used instead of SOC changes.

This paper introduces some intelligent control strategies for marine craft. By looking at some existing problems in this area, e.g. the uncertainties and nonlinearities in ship dynamic model and time delay in ship actuator system, three types of control strategies are studied, namely, robust PID control for ship steering, adaptive fuzzy robust tracking control (AFRTC) for ship steering, and adaptive fuzzy Hinf control for ship roll stabilization. The effectiveness of the three control strategies are demonstrated by ship simulation. This paper is dedicated to the memory of Professor YS Yang for his pioneer work on robust adaptive fuzzy control of marine craft.

Design and development of sensor based Automatic steering control system for automobiles

We are interested in making and control a small sized two-wheels bike robot and we aim to balance the robot and to lead it to desired direction only with automatic steering control. Our research purpose is to make an original small sized bike robot and to move the robot for over 300 meters in indoor corridors under the automatic steering control only. We report the making of the original small bike robot and experiments. The dimension of the bike robot was designed as proportional to the real bicycle. Slalom motion and long distance motion were performed by steering control only.

The power to gas (P2G) technology can realize the large-scale storage of electric energy in the form of natural gas, so that the power system and the natural gas system have the ability to flow energy, and the degree of coupling between the power system and the natural gas system is deepened. As the coupling between the power system and the natural gas system continues to increase, an integrated energy system (IES) with the power grid as the core has emerged. However, under uncertain conditions, the current planning methods still cannot guarantee the optimal interests of each manufacturer, so a collaborative planning method for gas-electric systems based on non-cooperative game theory is proposed. With each energy unit and electricity and gas network companies as independent interest groups, and with the maximum annual net income as the optimization goal, establishing a comprehensive non-combination of wind turbines, gas turbines, electric-to-gas turbines, transmission lines and natural gas pipelines in the gas-electric integrated system linear programming model. Aiming at the uncertainty of wind power and load, an improved two-stage robust optimization method is proposed. Finally, the modified IEEE 39-node power system and 20-node natural gas system gas-electric network verify the application value of the model and algorithm.

As an important part of a multi-energy system, the energy hub (EH) accommodates a wide range of input sources and diversified load types. Optimising the equipment type and capacity of the EH is the basis for ensuring the safe and economic operation of the EH. In this context, the basic concepts and models of the EH are first outlined. Then, to reduce the user's electricity cost and user comfort as the optimisation goal, the tie line power constraint and the purchase and sale power state constraints are considered comprehensively.

In order to eliminate mutual negative effect of brake, steering and suspension system, a kind of layered coordinated control method based on multiple controllers is put forward. Framework of coordination control system of chassis is established, coordination strategy of upper controller and control strategy of lower controllers are designed. The upper controller is used mainly to receive operation information of driver, running state of vehicle and feedback information of lower controllers, and send coordination control strategy to lower controllers. The lower controllers include controller of electro mechanical braking system (EMB), controller of electric power steering system (EPS) and controller of active suspension system (ASS), which are used to receive decision instruction of upper controller, control actuators to accomplish control tasks and send execution situation to upper controller in time.