119 results about "Kinetic control" patented technology

The invention discloses a chassis coordination control method and system based on tire side deviation state evaluation, and relates to the technical field of four-wheel steering four-wheel drive vehicle dynamics control. The method comprises the steps that an expected front wheel rotation angle is determined based on an expected steering wheel rotation angle input by a driver, and a front wheel rotation angle is determined; further determining a feed-forward front wheel steering angle, a feed-forward rear wheel steering angle and an additional yaw moment based on feed-forward control and feedback control, determining a first tire slip angle and a second tire slip angle based on a road adhesion coefficient, and further determining a wheel torque control weight, a feedback front wheel steering angle control weight and a feedback rear wheel steering angle control weight; and further determining a driving yaw moment, a feedback front wheel steering angle and a feedback rear wheel steering angle, determining a total longitudinal force based on an expected longitudinal acceleration input by a driver, and performing four-wheel torque distribution based on the total longitudinal force and the driving yaw moment to obtain a four-wheel driving torque. The driving stability of the vehicle under the limiting working condition can be improved.

The invention discloses a learning-based composite layered anti-interference control system and method suitable for a large-windward-area unmanned aerial vehicle, is used for realizing robust wind resistance control of the large-windward-area unmanned aerial vehicle, and aims at the flight characteristics of large windward area and sensitivity to external wind field change in a vertical take-off and landing stage. A wind speed estimation method without an additional sensor is provided, modeling of external disturbing force is realized in combination with a Gaussian process regression algorithm, and compensation of the disturbing force is realized by using quaternion-based model prediction control, so that the influence of an external change wind field on the dynamics of the large-windward-area unmanned aerial vehicle is reduced, and the trajectory tracking precision is remarkably improved. A backstepping controller based on SO (3) is designed in an attitude control loop, a nonlinear disturbance observer is integrated, and active compensation of external disturbance torque and robust tracking control of attitude are realized. Based on the technical characteristics, a complete dynamic control link capable of estimating and feeding back compensation disturbance in real time is further constructed.

The invention relates to the technical field of automobile dynamics control, in particular to an ambulance suspension intelligent agent based on deep reinforcement learning and an optimization method thereof, and the optimization method comprises the steps: S1, initializing an evaluation network and a control strategy network; s2, adopting a swarm intelligence algorithm to initialize a population; s3, the number M of evolution generations of the controller and the time step T of each generation are set, in each time step, the initial fitness of the controller is set to be 0, and the fitness of the controller is updated according to the reward value and the auxiliary reward of the current time step; s4, after each intergeneration is finished, updating the population according to the fitness by adopting a swarm intelligence algorithm, and training the evaluation network and the control strategy network to update network parameters; and S5, after M generations of evolution are completed, screening out the controller with the highest fitness from the controllers, and setting the network parameters corresponding to the controller in the control strategy network. The invention is at least beneficial to improving the adaptability of the ambulance to different working conditions.

An intelligent chassis drift collision avoidance control method and system and an electronic and electrical architecture. The method comprises: performing quantitative analysis on collision avoidance requirement information by means of an obstacle envelope method so as to obtain obstacle envelope data; calculating a normal operation infeasible state domain of the obstacle envelope data on the basis of a vehicle dynamics model; performing safety analysis on the basis of the normal operation infeasible state domain, so as to determine, on the basis of a safety analysis result, whether to start an extreme collision avoidance operation; and if it is determined that the extreme collision avoidance operation is started, performing autonomous decision-making control of a vehicle on the basis of extreme dynamics control input data generated by a chassis domain control platform, so as to achieve drift collision avoidance. The method can give full play to the collision avoidance potential of vehicles, and improve the emergency response capability and backup level of intelligent vehicles.

The invention belongs to the technical field of distributed electric drive modular transport vehicle planning and control, and particularly relates to a distributed electric drive modular transport vehicle obstacle avoidance planning control method and device. The specific process of the method comprises the steps that two front shafts and two rear shafts which are close to each other are equivalent to two equivalent shafts respectively, two e-SPMT units are used for equivalence, and a monorail dynamic model is established; determining a collision boundary and establishing a collision constraint condition design, establishing a cost function including a swept area, a distance to an obstacle and path smoothness, and optimizing the cost function to obtain an expected path meeting the collision constraint condition; on the basis of the expected path and kinematic constraints, an expected speed and a yaw velocity corresponding to each path point in the expected path are generated; taking the expected speed and the yaw velocity as state quantities, and generating a dynamics control quantity according to the monorail dynamics model; the dynamic control quantity is distributed to each wheel longitudinal force and turn angle.

The invention discloses a comprehensive simulation method for splitting failure of a Brazilian disk under dynamic and static actions. The method comprises the following steps: establishing a Brazilian disk finite element model and defining material parameters; performing dispersion crack treatment on the model through a phase field variable and a crack density function; selecting a branch path according to a load type (static / dynamic); the static branch constructs an energy functional and a displacement-phase field control equation based on an F-M variation principle, and the dynamic branch deduces a dynamic control equation through a Lagrange energy functional and a Hamiltonian principle; a displacement field and a phase field are updated through finite element discretization and Newton-Raphson iteration solution; cyclic loading is judged through convergence until the load is applied, and finally the crack propagation process and the mechanical response are visually output. According to the method, integrated simulation of dynamic and static loads is realized through a unified phase field dispersion framework, the problem of model incompatibility in a traditional method is solved, and the crack propagation prediction precision is remarkably improved.

The invention discloses a rotor craft aeroelastic stability prediction method, and relates to the field of rotor dynamics, the method comprises the following steps: constructing a nonlinear aeroelastic dynamics control equation, and determining dynamics sensitive parameters; constructing an input sample data set; obtaining an output sample data set based on the input sample data set and the nonlinear aeroelastic dynamics control equation; constructing a sample data set based on the input sample data set and the output sample data set; constructing an initial aeroelastic stability prediction model based on the de-noising diffusion probability model; training the initial aeroelastic stability prediction model by adopting the sample data set to obtain an aeroelastic stability prediction model; acquiring the working condition of the rotorcraft in real time to determine the value of the dynamic sensitive parameter of the rotorcraft; inputting the values of the dynamic sensitive parameters into the aeroelastic stability prediction model to obtain a corresponding modal damping ratio; and determining the aeroelastic stability of the rotorcraft based on the modal damping ratio. According to the method, the aeroelastic stability of the rotorcraft can be accurately predicted.

The present application relates to a kind of four-legged robot single leg sliding mode control method based on interference observer, belong to robot control technical field.First, the trajectory of four-legged robot single leg in swing phase is established;Then, the kinematic model of four-legged robot single leg is established, to realize the conversion of foot target position and corresponding joint angle;On this basis, non-singular terminal sliding mode controller is designed to deal with the dynamics control under the condition of no interference;Finally, combined with sliding mode controller and interference estimation, the final composite control strategy is designed, the stable tracking of robot joint angle is realized, so as to improve the anti-interference performance of single leg system.The present application utilizes the combination of finite time interference observer and non-singular terminal sliding mode controller, designs a kind of composite controller, to improve the foot trajectory tracking accuracy and system robustness of four-legged robot, eliminate the uncertainty caused by external disturbance and modeling error suffered by robot.

The present application relates to a trajectory tracking method, device and mobile robot based on voltage control. The method establishes a kinematic model and a first dynamic model of the mobile robot under unknown longitudinal slip and lateral slip; establishes a second dynamic model of the drive motor; obtains an overall dynamic model based on the first dynamic model and the second dynamic model; obtains an outer-loop control loop based on the kinematic model and the kinematic control module; realizes the posture tracking of the mobile robot based on the outer-loop control loop; obtains an inner-loop control loop with voltage as the control input of the overall dynamic model based on the dynamic control module and the overall dynamic model; uses a linear extended state observer based on the inner-loop control loop to estimate and compensate for the introduced lumped disturbance, and designs an anti-disturbance rejection controller to make the current speed of the mobile robot converge to the expected speed generated by the kinematic control module, so as to realize accurate trajectory tracking of the mobile robot and improve the motion control performance of the mobile robot.

The invention discloses an intelligent automobile active obstacle avoidance control system and method suitable for complex road conditions. The system comprises a multi-source road condition sensing fusion module, a dynamic risk assessment and decision module, an obstacle avoidance path planning module, a vehicle dynamics control module, a man-machine interaction and emergency takeover module and a system state monitoring and fault diagnosis module. According to the invention, the problem of unreliability of a single sensor in rainy days, congestion and other scenes is solved through multi-source sensor fusion, and the sensing precision is ensured; a multi-factor risk assessment model avoids misjudgment of single distance judgment, and the decision more conforms to actual safety requirements; path planning is combined with vehicle dynamics constraint, closed-loop control ensures accurate path tracking, and the vehicle is prevented from being out of control.

The application provides an electric unmanned ship trajectory tracking method, device, equipment, medium and product, and relates to the field of electric unmanned ships. Based on the current position of the electric unmanned ship, the coordinate error and the heading error of the electric unmanned ship are determined. The coordinate error and the heading error are input into a kinematics controller to obtain a virtual speed instruction. The virtual speed instruction is input into a dynamics controller to obtain a virtual thrust instruction. Based on the virtual thrust instruction, a target control instruction is determined and sent to the electric unmanned ship. The above steps are cyclically executed under the condition that the tracking is not completed until the tracking is completed. The kinematics controller and the dynamics controller share a fixed time gradient template, and the cost function of the kinematics controller contains an energy consumption control index. The application adopts a two-layer controller structure and shares a fixed time gradient template, and sets an energy consumption control index in the cost function corresponding to the kinematics controller, so that fixed time convergence and energy consumption suppression can be realized.

This invention proposes a dual-closed-loop control method for the dynamics of a magnetically levitated energy storage flywheel rotor based on LADRC (Laser-Adjustable Dynamic Control) to achieve stable levitation and dynamic control of the flywheel rotor. First, mathematical models of each degree of freedom of the flywheel rotor and a linearized model of the power amplifier-electromagnet coil are established in the magnetic bearing coordinate system. Then, the electromagnetic coupling terms, gyroscopic coupling terms, and imbalance terms in the flywheel rotor mathematical model are defined as external disturbances. Mathematical models of the flywheel rotor and power amplifier-electromagnet coil used for controller design are derived, and a second-order LADRC controller for the position loop and a first-order LADRC controller for the current loop are designed. Finally, the parameters of the position loop and current loop controllers are tuned using the pole placement method. Simulation results show that this dual-closed-loop control strategy can effectively decouple the degrees of freedom of the flywheel rotor under static and high-speed levitation conditions. Compared with PID control, it has better dynamic characteristics and stronger anti-disturbance capability. This is of great significance in ensuring the stable and reliable operation of the magnetically levitated energy storage flywheel rotor.

An automotive electronic longitudinal dynamics control system of a motor vehicle comprising a powertrain comprising a propulsor electronically controlled by an electronic engine control module and an automatic transmission electronically controlled by an electronic automatic transmission control module to transmit mechanical power generated by the propulsor to drive wheels of the motor vehicle and comprising an automatic gearbox having a plurality of gears with corresponding gear ratios. The electronic automatic transmission control module is designed to output data indicative of a currently engaged gear and a next engaged gear that will be engaged after the currently engaged gear. The electronic engine control module is designed to receive data indicative of an engine torque request and to responsively control the propulsor based on the received engine torque request to cause the propulsor to output an engine torque equal to the requested engine torque. The automotive electronic longitudinal dynamics control system is designed to:receive from the electronic automatic transmission control module data indicative of the currently engaged gear and the next engaged gear that will be engaged after the currently engaged gear;receive a reference longitudinal acceleration to be followed and a measured longitudinal acceleration;compute an engine torque request for the electronic engine control module based on a longitudinal acceleration error indicative of a deviation of the measured longitudinal acceleration from the reference longitudinal acceleration, on a control law and on the currently engaged gear and the next engaged gear.

This invention discloses an iterative learning path tracking control method for USVs based on virtual potential field guidance, comprising: establishing a nonlinear mathematical model of the USV; obtaining the gravitational model and repulsive model of the virtual potential field; obtaining the guidance model of the USV; obtaining the kinematic controller of the USV system; obtaining the dynamic controller of the USV system, and controlling the USV system. This invention's iterative learning path tracking control method for USVs based on virtual potential field guidance, by establishing the gravitational and repulsive models of the virtual potential field of the USV model, incorporates an obstacle avoidance mechanism that considers the shape of the obstacle itself into the guidance algorithm. This solves the problem that most existing adaptive control obstacle avoidance algorithms treat obstacles as point masses, making the obstacle avoidance mechanism of this invention more reliable and enhancing the autonomous collision avoidance performance of ships.

The present application provides a parameter identification method, device, electronic device and storage medium for a robotic arm, and relates to the field of robotic arm control technology. The method includes: obtaining the dynamic inertia parameters, nonlinear friction parameters, joint motion information and dynamic total torque of the robotic arm; splitting the dynamic total torque according to the dynamic inertia parameters, nonlinear friction parameters and joint motion information to obtain split inertia torque and split friction torque; according to the split inertia torque and split friction torque, cyclically iteratively optimizing the dynamic inertia parameters and nonlinear friction parameters until the preset convergence conditions are met; obtaining the target dynamic inertia parameters and target nonlinear friction parameters when the preset convergence conditions are met, and the target dynamic inertia parameters and target nonlinear friction parameters are used to dynamically control the robotic arm. The present application can identify dynamic inertia parameters that conform to physical characteristics and nonlinear friction parameters that better fit joint friction.

The invention discloses a method for analyzing time-frequency characteristics of collision vibration by using a segmented B-spline wavelet collocation method, which comprises the following steps of: (1) establishing a dynamic equation for wavelet discretization, discretizing a dynamic control equation of a collision-vibrator system by using a 4-order B-spline wavelet basis function, and establishing a nonlinear algebraic equation set about a wavelet coefficient; (2) carrying out segmented iterative solution on the time domain, dividing the whole time domain into a plurality of sub-time periods which are connected in sequence, and carrying out iterative solution on the nonlinear algebraic equation set in each sub-time period to obtain a global wavelet coefficient; and (3) analyzing the time-frequency characteristics, and directly calculating energy distribution based on the wavelet coefficient to realize time-frequency joint characterization. The invention aims to provide a method which can fuse solution of system response and extraction of time-frequency characteristics in a unified mathematical framework, and realizes high-precision time-frequency joint characterization by directly solving wavelet coefficients, thereby overcoming inherent defects of an existing two-step method.

This invention relates to the field of automotive autonomous driving control technology, specifically to a software architecture, chassis domain controller, and chassis domain system for autonomous driving. The information layer acquires vehicle fault commands and emergency stop commands. The motion coordination layer triggers vehicle fault modes and emergency stop modes, and acquires emergency stop control signals and longitudinal and lateral vertical control signals. The dynamics control layer acquires dynamics control target quantities based on the emergency stop control signals or longitudinal and lateral vertical control signals; the fault-tolerant control layer performs fault-tolerant control based on vehicle fault information. The actuator control layer converts the dynamics control target quantities and fault-tolerant control target quantities into actual control signals to control the actuators. This software architecture, designed from a centralized perspective, achieves decoupled development of software and hardware, centrally processes all information, and uniformly integrates and schedules functions. It comprehensively considers vehicle, driver, fault, and cross-domain interaction, improving vehicle control accuracy and operational safety.

Aiming at the motion control problem of the under-actuated disc-shaped underwater unmanned vehicle in a complex marine environment, a kinematics model, a dynamics model and a six-degree-of-freedom motion model considering the existence of ocean current are established, and the six-degree-of-freedom model is decoupled into a horizontal plane model and a vertical plane dynamics control model; based on a backstepping method and a sliding mode variable structure algorithm, a depth adaptive backstepping sliding mode controller and a heading angle adaptive backstepping sliding mode controller are respectively designed. In each motion control process, self-adaptive parameters of the heading angle self-adaptive backstepping sliding mode controller and the depth self-adaptive backstepping sliding mode controller are updated through the self-adaptive control rate, updating results of the respective self-adaptive parameters are corrected by using the mapping function, infinite integral increase of the self-adaptive parameters is prevented, and the self-adaptive control rate is improved. And the stability of the system is enhanced. The self-adaptive backstepping sliding mode controller designed by the invention has more excellent control performance and robustness, can better adapt to a complex marine environment, and can realize accurate control of the disc-shaped underwater unmanned vehicle.

The application discloses a high-speed train basic resistance online estimation method, device, equipment and medium, relates to the field of track traffic control and high-speed train dynamics control, and the method comprises the following steps: constructing a multi-particle longitudinal dynamics equation of a high-speed train based on the internal coupling force of the high-speed train; designing an adaptive observer based on the multi-particle longitudinal dynamics equation; the adaptive observer comprises a state estimation equation, a parameter adaptive law, an auxiliary variable dynamic equation, a gain matrix updating law and a basic resistance equation; and the basic resistance of the high-speed train is estimated online based on the adaptive observer, so that the basic resistance estimation values of each carriage of the high-speed train are obtained. The application can effectively estimate the basic resistance online and asymptotically, significantly reduces the test cost and improves the robust performance, does not need to rely on complex offline tests, and has both high precision and strong robustness.

The invention discloses a road surface unevenness recognition method and device based on a physical information neural network, a medium and a vehicle, and relates to the field of road recognition, and the method comprises the steps: combining a kinetic equation of a suspension system with a neural network, and constructing a neural network model based on physical information; acquiring acceleration data of the suspension system on the to-be-identified road surface; adopting a neural network model based on physical information to obtain a pavement elevation recognition result based on the acceleration data; and representing the road surface unevenness by adopting a road surface elevation recognition result. According to the method, the complexity of an algorithm can be reduced, meanwhile, the physical interpretability is improved, richer road surface information is provided for dynamic control of a suspension system, and then the driving smoothness and riding comfort of a vehicle are improved.

The invention relates to the related technical field of the fields of man-machine cooperation, rehabilitation assistive devices and wearable robots, in particular to a five-connecting-rod knee joint exoskeleton device which comprises a thigh assembly (1), a transmission assembly (2) and a shank assembly (3), and the thigh assembly (1) comprises an output motor (101), a power output rod (102), a thigh binding piece (103), a thigh sliding block (104) and a thigh guide rod (105). The transmission assembly (2) comprises a first connecting rod (201), a second connecting rod (202), a third connecting rod (203), a fourth connecting rod (204), a fifth connecting rod (205) and an auxiliary connecting rod (206), and the shank assembly (3) comprises a shank binding piece (301), a shank sliding block (302), a shank guide rod (303) and a sensing unit (304). The five-connecting-rod knee joint exoskeleton device is based on the mechanical structure design of a five-connecting-rod mechanism, advanced control strategies such as multi-sensor fusion and impedance control are combined, and the nonlinear track of a sliding rotation center in the bending and stretching process of the knee joint of the human body is highly fitted in kinematics; meanwhile, the exoskeleton can adaptively provide assistance or damping according to the gait characteristics and the motion intention of the user by adjusting the output torque and flexibility in real time on the aspect of dynamic control, so that the naturalness, comfort and safety of man-machine interaction are effectively improved; therefore, diversified application requirements of rehabilitation training, walking assistance, man-machine cooperation and the like can be better met.

The application discloses a kind of matching and mismatched interference under unmanned ship preset time control method and system, comprising the following steps: establishing the nonlinear motion model of unmanned ship under matching and mismatched interference;Design preset time adjustment function, the dynamic evolution process of system error is regulated;Kinematic disturbance observer and dynamics disturbance observer are designed to online estimate matching interference and mismatched interference;According to interference estimation information, construct kinematic controller, filter and dynamics controller, realize the robust preset time tracking control of reference trajectory of unmanned ship.The method proposed in the application can realize the online observation and compensation of multi-source disturbance, ensure that the system tracking error and disturbance observation error converge within the preset time, and the convergence time is adjustable, while having the advantages of continuous smooth control input, strong anti-interference ability and high engineering realizability, which can improve the control performance and reliability of unmanned ship in complex sea conditions and time-sensitive tasks.

The invention discloses a flexible robot dynamics control device based on Lie group symmetry and a modeling method. The device comprises a rigid connecting rod, a flexible rod and a flexible hinge which are connected in series, a fiber grating sensor is spirally arranged on the flexible rod, and a signal conditioning module, an FPGA (Field Programmable Gate Array) data processing module, a Lie group conservation control module and a CAN (Controller Area Network) bus are linked with an executing mechanism. According to the method, a rigid-flexible coupling equation is built through a Lagrangian-Hamiltonian mixed method, SE (3) a conservation quantity is exported through a Lie group, a LiefVIN network is solved, and the model is corrected through a double-dynamic self-adaptive mechanism. Full-dimensional deformation monitoring is achieved, the vibration prediction error is smaller than or equal to 3%, the trajectory tracking error is smaller than or equal to 0.08 mm, the dynamic solving speed is larger than or equal to 1000 times per second, the method is suitable for multiple scenes, and the problems that existing modeling precision is low, sensing is incomplete, and control real-time performance is poor are solved.

This invention discloses a kinetically controlled method for preparing hierarchical porous molecular sieves, belonging to the field of catalyst preparation technology. It employs a two-step crystallization method: first, nucleation occurs at low and ultra-low H2O / SiO2 molar ratios; then, after the low-temperature phase, water is added, followed by rapid growth at high temperature and high H2O / SiO2 molar ratios. The solid-phase and liquid-phase crystallization mechanisms in the synthesis system work in succession to prepare hierarchical molecular sieves. This invention, without adding any mesoporous pore-forming agents, only modulates the crystallization temperature and the H2O / SiO2 molar ratio of the synthesis system to kinetically control the crystallization mechanism, resulting in molecular sieves with higher catalytic performance than those obtained using traditional methods. Furthermore, it overcomes the drawbacks of traditional hierarchical porous molecular sieve preparation processes, such as high cost, high calcination energy consumption, poor mesopore connectivity, and severe contamination from pore-forming agents.

The invention provides a dynamics control method and device of a robot, electronic equipment, a computer readable storage medium and a computer program product. The method comprises the steps that according to a linear motor and a closed chain structure, a first constraint relation between the length of the linear motor and the included angle of adjacent connecting rods in the closed chain structure is determined; according to the multiple connecting rods in the closed chain structure, the second constraint relation between the included angle and the rotating angle of the adjacent connecting rods in the closed chain structure is determined, and the rotating angle is the angle of the closed chain structure driven by the linear motor to rotate around the rotating joint; solving by combining the first constraint relationship and the second constraint relationship to obtain a conversion relationship between the thrust of the linear motor and the torque of the rotary joint; and according to the conversion relation, the real-time thrust of the linear motor is converted into real-time torque acting on the rotary joint, and the robot is controlled based on the real-time torque. According to the application, accurate mapping from the thrust of the linear motor to the rotating torque can be realized, and the dynamic control requirement of the robot is met.

The embodiment of the invention discloses an unmanned ship surrounding hierarchical game control method under unreliable communication, and the method comprises the steps: considering the unreliable communication conditions that tracking target information is not completely known and intermittent communication and false data injection (FDI) exist at the same time, and employing a specified time elastic Nash equilibrium target state estimator which converges under the intermittent communication; the method ensures that the estimated pose of the target can be converged to a saddle point according to the specified time and performance under intermittent communication, and on the basis, a specified performance guidance law under the specified time is designed, the longitudinal reference speed and the heading reference speed of the unmanned ship are obtained to establish a cost function, and then a Hamilton-Jacobian-Axaxi equation is established, so that the attitude of the target can be estimated. Obtaining an ideal optimal dynamic control law and optimal false data; and carrying out approximation by adopting a Critic neural network learning structure to obtain an ideal optimal dynamic control law after approximation and optimal false data after approximation.

The invention discloses a commercial vehicle transmission system equivalent rotational inertia calibration and mass real-time estimation method, and relates to the technical field of vehicle dynamics control. Identifying the product of the equivalent merging coefficient K1 of the rolling resistance and the ramp resistance and the current mass mk and the air resistance coefficient K2 under the no-load state of the vehicle; and under the acceleration working condition, based on the obtained K1mk and K2 values, the equivalent transmission system rotational inertia Ii and the servicing no-load mass mk are identified. And in a quality real-time estimation stage after leaving a factory, updating the sum of products with the current mass mtotal in real time in a constant-speed driving segment. And in an acceleration working condition, Ii calibrated before leaving a factory is implanted into the kinetic model as a fixed parameter, and based on the updated mtotal sum value, the current total mass mtotal is directly solved through the relation between the driving force and the acceleration. According to the method, the strong coupling problem of the rotational inertia and the mass during estimation is thoroughly solved, and the real-time performance, precision and reliability of mass estimation in the vehicle running process are remarkably improved.

The invention discloses a TB14 titanium alloy wire preparation method based on recrystallization kinetics control, and belongs to the technical field of high-quality titanium alloy materials. The method comprises the steps that one-heating-number cast ingot cogging forging and three-heating-number tempering are adopted, and a forging stock is prepared; the forging stock is subjected to two-heating-number deformation rolling, and a hot-rolled coil is obtained; performing recrystallization heat treatment on the hot-rolled coil to obtain a wire blank; and drawing and reducing the diameter of the wire blank to obtain the wire. The transverse microstructure and the longitudinal microstructure of the prepared TB14 wire rod are recrystallized and are uniform, the average grain size of the wire rod is about 30 microns, the grain sizes are 6-7 grades respectively, various indexes of the TB14 wire rod for aviation fasteners are met, and certain surplus is reserved.

The application discloses a preset time control method and system for a wheeled mobile robot under multiple disturbances, and comprises the following steps: establishing a nonlinear motion model of a wheeled mobile robot under matched and unmatched disturbances; designing a preset time adjustment function to regulate and control the dynamic evolution process of system errors; designing a kinematic disturbance observer and a dynamic disturbance observer to online estimate the matched and unmatched disturbances; and constructing a kinematic controller, a filter and a dynamic controller according to the disturbance estimation information, so as to realize robust preset time tracking control of the wheeled mobile robot on a reference trajectory. The method provided by the application can guarantee the convergence of system errors within a preset time without relying on the ideal no-slip assumption, has the advantages of adjustable convergence time, continuous and smooth control input, strong anti-interference ability and high engineering realizability, and improves the anti-interference performance of the robot in a complex dynamic environment and the reliability of a time-sensitive task.

The invention relates to a method for placing a motor vehicle (1) having an electrical power supply system (7) in a safe state in the event of an impact, in which an impact detection program is carried out and the electrical power supply system (7) of the motor vehicle is switched off when an impact is detected. In this case, the following steps are carried out:-providing a driver assistance system (2) having an environmental sensor system (3) for monitoring at least part of the surroundings of the motor vehicle,-providing a driving dynamics control system (4) having at least one acceleration sensor (5), using an environment sensor system (3) of the driver assistance system (2) to monitor whether an object (6) is present in at least part of the surroundings of the motor vehicle (1), if an object (6) is detected by means of the environment sensor system (3), checking whether a risk of collision with the object (6) is present, and if it has been determined that the risk of collision has been present, restarting the driver assistance system (2). If the acceleration sensor (5) outputs a defined threshold value, activating the defined collision warning time window ([delta] t), querying the acceleration sensor (5) within the collision warning time window ([delta] t), and detecting a collision if the acceleration sensor (5) output of the driving dynamics control system (4) exceeds the defined threshold value.