724 results about "Virtual control" patented technology

The invention provides a real-time transmission method and system based on internet-of-things sensing data in a digital twinborn scene, and the method comprises the steps: collecting and processing vibration spectrum data, pressure gradient change data and temperature distribution data of equipment in an industrial production line, generating a preprocessing data package, carrying out the analysis to obtain an equipment state fingerprint feature and an environment working condition label, and carrying out the real-time transmission of the environment working condition label. A target virtual control parameter and a target error compensation amount are generated by using a dynamic parameter correction loop of the digital twin, an actual material flow state is generated in combination with material flow rate data, an optimization strategy sequence of multi-device collaborative operation is generated by using a distributed computing architecture, and the optimization strategy sequence is converted into a track compensation parameter of an end effector in the device; in combination with the target error compensation amount, data closed-loop transmission is carried out; according to the invention, millisecond-level time domain matching of vibration, pressure and temperature data and material flow velocity is realized through a dynamic timestamp alignment mechanism of 5G edge computing nodes, and the problem of synchronization error accumulation of traditional internet-of-things sensing data is solved.

The invention relates to the technical field of factory management. The intelligent factory management method based on digital twinning comprises the following steps: performing dynamic identification and analysis processing on a multi-source heterogeneous communication protocol of factory equipment to obtain a standardized data stream; constructing a three-dimensional digital twinborn model comprising an equipment state and a technological process; generating a virtual control instruction according to an analog control strategy in the three-dimensional digital twin model; sandbox security verification processing is carried out on the virtual control instruction, and a compliance instruction set is screened out; converting the compliance instruction set into a protocol format supported by the target equipment, generating a reverse control instruction and issuing the reverse control instruction to the physical equipment; performing closed-loop feedback optimization processing according to the difference between the execution result of the physical equipment and the prediction result of the three-dimensional digital twinborn model, so as to solve the problem that the digital twinborn model lacks real-time sensor data injection and dynamic behavior constraint embedding, ensure that the model can reflect the real state of the equipment, and improve the real-time performance of the equipment. And the reliability and the execution security of the virtual control instruction are improved.

The invention relates to the technical field of unmanned aerial vehicles, in particular to a low-power-consumption star flash control module applied to an unmanned aerial vehicle and a dummy pilot control method. The method comprises the following steps: acquiring an original control instruction of a real flying hand, and converting the original control instruction into an encrypted pulse signal containing a dynamic key; fusing a frequency spectrum camouflage signal simulating the environment background of a dummy pilot into the encrypted pulse signal, and then transmitting the encrypted pulse signal to the dummy pilot in a self-adaptive frequency hopping mode; synchronously analyzing the dynamic key at a dummy flying hand end and stripping the frequency spectrum camouflage signal to generate a virtual control track matched with the real operation behavior characteristics; and reversely modulating an actual response signal of the unmanned aerial vehicle based on the virtual control track, so that the unmanned aerial vehicle executes an action and forms dynamic error compensation with the virtual control track. According to the invention, a real flying hand can be effectively protected from electronic reconnaissance positioning and attack of an enemy, and the concealment is improved.

The invention discloses a data-based predefined time heterogeneous multi-agent formation collision avoidance method. The method comprises the following steps: establishing a nonlinear heterogeneous multi-agent system; designing a bimodal artificial potential field function to perform dynamic obstacle avoidance and prevent regional escape; establishing a self-adaptive robust controller used for generating an obstacle avoidance safety motion trail of the root leader; designing a self-adaptive formation zooming mechanism of the leader, and constructing a predefined time affine observer of the follower based on the self-adaptive formation zooming mechanism; designing a unified obstacle function; constructing a virtual control law for processing tracking errors based on the unified obstacle function; designing a neural network estimator; designing controllers of the leader and the follower according to the virtual control law; and forming a collision avoidance decision of the heterogeneous multi-agent formation based on a self-adaptive robust controller, a predefined time affine observer, a neural network estimator and controllers of the leader and the follower. According to the method, safe, efficient and robust cooperative control of the formation in a complex environment is realized, and the safety and task execution efficiency of the heterogeneous multi-agent formation in a limited and unknown environment are remarkably improved.

The invention provides a quadrotor unmanned aerial vehicle suspension swing suppression flight control method based on a DDPG. The method comprises the steps that a kinetic model of a quadrotor unmanned aerial vehicle suspension system is established; performing input shaping processing on an expected reference track signal by using a ZVD input shaper; the unmanned aerial vehicle suspension system is decoupled into position control of a position loop and attitude control of an attitude loop by adopting a cascade trajectory tracking control strategy, and a fuzzy PID controller of the position loop is designed based on a fuzzy theory; the shaped track signal is input into a fuzzy PID controller, and parameters of the PID controller are adjusted on line; performing attitude settlement on the virtual control quantity output by the fuzzy PID controller, and inputting the virtual control quantity into an active disturbance rejection controller; roll, pitch, and yaw torque control quantities are generated based on the virtual control quantity of the attitude loop and the control quantity generated by the DDPG-based tilt angle controller. Under a complex external interference environment, a preset track is tracked with high precision, load swing is effectively suppressed, reliable execution of a transportation task is successfully guaranteed, and meanwhile, the control precision and the anti-interference capability of the system are remarkably improved.

The invention relates to the technical field of industrial distributed control system architecture, and discloses a dual-redundancy design method for a virtual controller VDPU, which comprises the following steps of: deployment of a four-network-port redundant network architecture: dividing four physical network ports into two groups of independent channels, and simultaneously configuring a network link automatic switching mechanism, the working states of the four network ports are monitored in real time, then double isolation of a physical layer and a protocol layer is achieved, and an independent heartbeat transmission channel is established; main / standby heartbeat monitoring and switching control: the main / standby controller periodically interacts state information packets through a special heartbeat channel, and establishes a three-level fault determination mechanism at the same time to perform seamless main / standby switching; a multi-mode data synchronization mechanism is implemented, namely initialization synchronization, increment synchronization during operation and exception recovery synchronization are started, separation of heartbeat signals and data synchronization can be realized through two groups of independent channels, and the fault-tolerant capability and the switching efficiency of the system are improved, so that the operation stability of the system is guaranteed.

The invention relates to the technical field of aerocar mode switching, and discloses a distributed driving aerocar self-adaptive fault-tolerant control method for actuator multimode failure, which comprises the following steps: constructing a unified six-degree-of-freedom dual-mode state space model; residual signals are generated based on extended Kalman filtering and a sliding-mode observer, and fault types and positions are positioned in real time through a lightweight classifier; the method comprises the following steps: extracting residual time-frequency features, identifying hard faults by using a lightweight convolutional neural network, quantifying soft fault degrees through an incremental support vector machine, fusing multi-source information based on a Bayesian network to output fault types, levels and confidence coefficients, and introducing an incremental learning mechanism to realize self-evolution of a diagnosis model; a virtual control instruction is generated by adopting hierarchical sliding mode control, thrust and torque distribution of remaining actuators is optimized based on a dynamic quadratic programming algorithm, control parameters are adjusted online in combination with a Lyapunov adaptive law, aerodynamic interference and model uncertainty are inhibited, attitude stability and trajectory tracking in air-ground mode switching are guaranteed, and the method has the advantages of being high in reliability and high in reliability. And the fault-tolerant performance and the operation safety of the hovercar in the air-ground mode switching process are obviously enhanced.

The invention relates to the technical field of mechanical arm control, in particular to a self-adaptive fuzzy fixed time control method based on an output-limited mechanical arm, and the method comprises the following steps: S1, constructing a mechanical arm dynamic model; s2, setting constraint conditions of an output state of the mechanical arm dynamic model; s3, defining a tracking error and a virtual control law of the mechanical arm dynamic model; s4, on the basis of output state limitation and fixed time control, an actual control law is designed to serve as input of the mechanical arm dynamic model, and an adaptive law is constructed; and S5, a three-level logarithmic obstacle Lyapunov function is constructed, the three-level logarithmic obstacle Lyapunov function is combined with the virtual control law, the actual control law and the self-adaptive law step by step and substituted into the virtual control law, the actual control law and the self-adaptive law, and then it is guaranteed that the output state of the mechanical arm dynamic model does not exceed the preset safety boundary according to the actual fixed time control lemma. According to the invention, high-precision trajectory tracking can be realized on the premise of ensuring safe operation of the mechanical arm.

The invention discloses a fully-mechanized coal mining equipment group sensing-control integrated twinning device and method, and relates to the technical field of coal mine intelligent mining digital twinning. The method comprises a sensing information driving mode, a physical instruction driving mode and a dual-driving mode. When the sensing information driving mode lacks physical instruction information, real-time sensing data of the hydraulic support are collected, sensing-control integration is achieved, and the shape is consistent; the physical instruction driving mode is used for speculating a current posture through a speed parameter training model and an optimal force training model when sensing information is lost, so that virtual-real synchronization is realized; and the dual-drive mode is used for realizing real-time consistent action and regulation of the virtual monitoring model and the virtual control model according to an adaptive control strategy when the physical instruction transmission path and the sensing information transmission path are both intact. According to the method, high-fidelity actions of the virtual control model and the virtual monitoring model can be driven through the physical entity, and virtual reconstruction of the working space is completed in the virtual space.

The invention discloses an intelligent regulation and control method for a power battery positive electrode binder production process, and the method comprises the steps: synchronously collecting multi-dimensional process parameters such as temperature, viscosity and the like and performance indexes such as particle size distribution, bonding strength and the like, carrying out the normalization, denoising and time sequence alignment processing, and fusing hydrodynamic simulation and historical data to construct an initial parameter coupling model; identifying a parameter influence weight through an attention mechanism neural network, generating a decoupling factor matrix to reconstruct a parameter space, and establishing a virtual control channel; executing constrained gradient descent multi-objective optimization in the channel, generating a regulation and control instruction, and reversely mapping the regulation and control instruction into an equipment executable parameter; according to the method, performance indexes and optimization targets after regulation and control are continuously compared, model parameters are updated, retraining is triggered when deviation exceeds a threshold value, regulation and control precision and process stability are guaranteed, and the real-time performance of parameter regulation and control, the collaborative optimization capability and the quality consistency of the production process are remarkably improved.

The invention provides an exoskeleton robot self-adaptive control method and related equipment, and relates to the technical field of exoskeleton robots. The method comprises the following steps: acquiring motion information and position information of each movable joint in the exoskeleton robot; inputting the motion information and the position information into a pre-trained angle prediction model to obtain a target angle of each movable joint; the difference value between the target angle and the actual angle output by the exoskeleton controller serves as an angle error; constructing a virtual control quantity based on the angle error; the virtual control quantity is combined with motion parameters of the exoskeleton robot to be input into a disturbance observer, and estimated disturbance is generated; the angle error, the virtual control quantity and the estimated disturbance are input into an adaptive neural network controller, and the control torque of each movable joint is obtained; and based on the control torque of each movable joint, generating a control signal of each movable joint. The method and the device have good control precision.

The invention discloses a large-span truss hoisting and splitting system and method based on digital twinning, and belongs to the technical field of building construction, and the system comprises a physical entity unit, a data acquisition and transmission unit, a digital twinning model unit, a function service and data analysis unit and an application and interaction unit. According to the invention, through real-time sensing of a physical entity state, multi-source data fusion transmission, high-precision digital twinning modeling, intelligent simulation analysis and decision optimization, and fusion of multi-modal man-machine interaction, a virtual control system which is in whole-course synchronous mapping and bidirectional interaction with a physical entity is constructed; according to the method, real-time visual monitoring, trend prediction and risk early warning of the hoisting and splitting process can be achieved, scheme preview and dynamic optimization are supported, virtual-real fusion operation guidance is achieved through the AR technology, and the safety, precision and efficiency of hoisting and splitting operation of the large-span truss are improved.

The invention discloses a ship formation autonomous obstacle avoidance control method based on offset intervention guidance. The method comprises the steps of obtaining a nonlinear mathematical model of a three-degree-of-freedom ASV; acquiring a smooth reference path for USV ship formation according to the virtual ship L1VS, and acquiring a ship obstacle avoidance virtual reference path according to the obstacle avoidance virtual ship VS in combination with a DWA algorithm; designing a kinematics virtual control law of the USV ship formation based on the constructed offset intervention guidance mechanism; on the basis of the constructed dynamic event triggering mechanism, a robust neural damping technology is combined, and a robust kinematics error is obtained according to the kinematics error of the USV ship formation; and designing an adaptive robust command filtering controller according to the robust kinematics error so as to realize autonomous obstacle avoidance control of the ship formation. The problems that according to a traditional ship formation control method, when a collision avoidance task in an unknown water area is executed in a complex marine environment, information of moving and fixed obstacles cannot be obtained in time, and communication load balancing and obstacle avoidance control precision cannot be effectively achieved are solved.

The invention discloses a unified management system and method for a virtual controller, and the system comprises a controller registration module which is used for initializing a controller registration array, checking whether the number of network IO registration reaches an upper limit or not, traversing the controller registration array, searching vacancies, and recording new instance information; the instance mapping module is used for mapping the successfully registered controller indexes into a controller information array and updating the registration number; the multi-thread security module is used for realizing concurrent security access in a registration process through a mutual exclusion lock; and the communication management module is used for creating a read management module, a write management module and an alarm management module, processing different types of data and carrying out heartbeat monitoring and data forwarding through a port. The technical problems that when a plurality of virtual controllers work cooperatively, control tasks of the virtual controllers are difficult to coordinate efficiently, so that the system performance is reduced, and even control conflicts or data loss may occur are solved.

The invention relates to a non-linear multi-unmanned vehicle system self-triggering time-varying formation control method, which comprises the following steps: constructing a second-order dynamic model for a non-linear multi-unmanned vehicle system, and describing communication between unmanned systems through a directed topological structure; a backstepping method is adopted, a virtual controller is introduced, and a leader-follower formation error system under the triggering condition is constructed; designing influence weights of communication resources and control performance, and respectively constructing an optimization model based on virtual input and formation distributed position errors and an optimization model based on real input and tracking formation speed errors; solving an approximate solution of a corresponding Hamiltonian-Jacobi-Bellman equation through a simplified reinforcement learning method, and sequentially obtaining an optimal virtual control protocol and an optimal reality control protocol; similarly, determining a self-triggering prediction condition; and finally, under the condition of self-triggering prediction, the multi-unmanned vehicle system not only realizes time-varying formation, but also balances communication resources and control performance.

The invention relates to the technical field of robot control, and discloses a mechanical arm specified performance fault-tolerant control method based on a fuzzy logic system, and the method comprises the steps: building a kinematics and dynamics model and a fault model of an agricultural robot; establishing a relative error dynamic equation between the actual position and the expected position; designing a specified performance function, and constraining the tracking error within an expected range by using the specified performance function; on the basis, designing a virtual control law by using a backstepping method under the condition of meeting error constraints; designing an adaptive control law by adopting a fuzzy logic system based on an uncertain item, unknown environment interference and a fault model in the kinetic model; a specified performance controller is designed based on a virtual control law, fuzzy logic adaptive control and full-state feedback agricultural robot, and specified performance fault-tolerant control of the agricultural robot is realized. The stability proves that the tracking error of the agricultural robot converges to any small neighborhood near zero within fixed time.

The invention relates to a rigid spacecraft attitude control method and system based on finite time constraint, and belongs to the technical field of spacecraft attitude control. Comprising the following steps: respectively constructing a spacecraft attitude control system model and a finite time convergence performance function containing a preset time constant; according to the finite time convergence performance function, dynamic attitude constraint is applied to the system state of the spacecraft attitude control system model; converting the attitude constraint into differential homeomorphic mapping of an unconstrained space; obtaining an error conversion variable according to differential homeomorphic mapping; and designing a virtual control law and constructing an error compensation module according to the error conversion variable, and designing an actual control input law according to the virtual control law and the error compensation module. According to the method, rapid convergence of the spacecraft attitude within the preset time is ensured, the dynamic response precision of the spacecraft in the rapid attitude maneuver process is remarkably improved, the control period delay is effectively avoided, and the power consumption is reduced.

The invention discloses a finite time position tracking and synchronous control method and device and a medium, and belongs to the technical field of dual-motor drive servo system control. The method comprises the following steps: constructing a dynamic model of the dual-motor-driven servo system; position tracking errors, speed synchronization errors and acceleration synchronization errors are defined, speed and acceleration states serve as cross feedback variables to be input into the dynamic model, and error signals are generated; introducing a filter and a compensation item through a preset dynamic surface control algorithm to generate a virtual control signal; constructing a finite time adaptive controller based on the error signal and the virtual control signal, and generating a motor control input signal; and estimating and compensating parameter uncertainty and nonlinear gap disturbance of the dual-motor-driven servo system in real time so as to update parameters of the adaptive controller. By means of the method, the technical effects of high-precision position tracking, dynamic synchronization and high-robustness control can be achieved in the dual-motor drive servo system.

The invention provides a multi-unmanned aerial vehicle distributed fault-tolerant control method, an unmanned aerial vehicle control method and an unmanned aerial vehicle control system, and belongs to the technical field of unmanned aerial vehicles. A position ring distributed fault-tolerant controller and an attitude ring distributed fault-tolerant controller are constructed in combination with a multi-unmanned-aerial-vehicle position ring virtual control law and a multi-unmanned-aerial-vehicle attitude ring virtual control law, and fault-tolerant processing is performed on the flight path of the fault unmanned aerial vehicle through the position ring distributed fault-tolerant controller; the fault unmanned aerial vehicle can keep tracking an expected trajectory; fault-tolerant processing is carried out on the attitude of the faulted unmanned aerial vehicle through the attitude ring distributed fault-tolerant controller, so that the faulted unmanned aerial vehicle can maintain a stable attitude angle, thereby ensuring that the whole unmanned aerial vehicle cluster system can operate safely and stably.

A system for controlling a vehicle combination comprising a tractor unit and at least one trailing unit is disclosed. The system has a target generator to determine a virtual control input for the vehicle combination based on a reference input for the vehicle combination. A power manager determines a power allocation input for the vehicle combination based on the reference input and a power capability of one or more units of the vehicle combination. A combination control allocator determines a control input for the vehicle combination based on the power allocation input and the virtual control input.

The invention discloses a two-degree-of-freedom helicopter optimal tracking controller design method based on disturbance observation, and relates to the technical field of two-degree-of-freedom helicopter control, and the method comprises the steps: considering the internal uncertainty and external disturbance of a system, and constructing a two-degree-of-freedom helicopter system equation; a pre-defined time nonlinear disturbance observer is introduced to estimate disturbance, coordinate transformation is constructed based on a dynamic surface control technology, a pre-defined time filter is introduced, a two-degree-of-freedom helicopter system model is decomposed into two stages of subsystems, and an optimal performance function is constructed for each subsystem. And designing an optimal virtual controller and a predefined time trajectory tracking controller. The controller designed by the invention can ensure that all signals of the whole two-degree-of-freedom helicopter are bounded within the preset time, can effectively improve the transient performance and the steady-state performance of the two-degree-of-freedom helicopter, and can ensure that the two-degree-of-freedom helicopter can still quickly and accurately track a reference trajectory within the preset time after being disturbed.

The invention relates to an indoor airship-oriented finite time trajectory tracking control system, platform and method, the system comprises an airship dynamic model, a disturbance estimation module, a sliding mode filter and a self-adaptive controller, the airship dynamic model is formed by constructing a motion stipulation inertial coordinate system and an airship body coordinate system of an airship; the disturbance estimation module estimates unknown disturbance based on a double-layer neural network according to an airship dynamic model and updates the network in real time; the sliding mode filter estimates the influence of noise on the motion speed of the airship according to the unknown disturbance condition of the airship and updates the network in real time; the adaptive controller adjusts the virtual control input of the airship motion trail by controlling the convergence condition of the tracking error within the finite time; according to the method, the disturbance problem caused by uncertainty and dead zones in the airship and the deviation problem of speed signal estimation caused by noise are solved.

The invention relates to the technical field of cooperative control, in particular to an adaptive event triggering fixed time consistency control method for a multi-agent system, which comprises the following steps of: S1, constructing a nonlinear high-order multi-agent system mathematical model with uncertain dynamics; s2, constructing a Lyapunov function containing an uncertain parameter lower bound based on coordinate transformation; s3, designing an adaptive event trigger controller with a positive bounded function by using a backstepping control method, wherein the adaptive event trigger controller comprises a virtual controller, an adaptive law and an event trigger mechanism; and S4, through stability analysis, it is proved that the high-order nonlinear multi-agent with the uncertain dynamic state can achieve actual fixed time output consistency, Zeno behaviors are avoided, and the self-adaptive event triggering fixed time consistency control method of the multi-agent system has the advantages of being high in practicability and easy to popularize. The problem of actual fixed time output consistency of a high-order nonlinear multi-agent system is solved, and an existing actual fixed time output consistency result is popularized.

The present invention belongs to the field of lifting equipment control technology, and specifically relates to a dynamic modeling method and control method for double-bridge lifting equipment. The dynamic equations of a five-degree-of-freedom double-bridge crane are constructed using the Lagrangian method, and the geometric constraint relationships between trolley I and trolley II in the direction parallel to the bridge and the vertical direction are constructed. The dynamic model of the double-bridge crane is constructed by combining the dynamic equations and the geometric constraint relationships, and the dynamic model is transformed into a general model. Based on the general model, a first error function is constructed based on the difference between the actual position and the expected position, and a virtual controller is constructed based on the first error function. A second error function is constructed based on the virtual controller, and an actual controller is constructed based on the first error function, the virtual controller, and the second error function. This technical solution models the system as a whole through the constraint relationship between the two trolleys, taking the mass of the hook into consideration during the modeling process, and solving the singularity problem.

The invention belongs to the field of automatic control, and particularly relates to a nonlinear system dynamic gain global trajectory tracking control method based on a self-adaptive neural network observer, which comprises the following steps: converting an uncertain nonlinear system model with unknown interference according to the requirement of output feedback control to obtain a first nonlinear system model; enabling an unknown nonlinear continuous function in the first nonlinear system model to be expressed as a function only containing an output signal and other system state estimation values; performing approximate approximation on an unknown nonlinear continuous function in the first nonlinear system model by using the first radial basis function neural network vector to obtain a second nonlinear system model; designing a second radial basis function neural network vector to construct a dynamic gain state observer of the second nonlinear system model, and obtaining an estimated value of a system state and an estimated value of an unknown nonlinear continuous function in the model; according to an inversion control method, defining a dynamic system tracking error index containing an intermediate virtual control signal, designing a Lyapunov function, and obtaining a change rate of a dynamic gain, a weight adaptive update rate of a second radial basis function neural network vector, and a control rate of the intermediate virtual control signal and a system input signal; different from most existing nonlinear system control methods, the method combines a novel dynamic gain neural network observer with an inversion controller with dynamic gain, and provides a robust global trajectory tracking control solution for a dynamic system operating under uncertain conditions.

The invention provides a heterogeneous motorcade prediction control method based on a path information protection mechanism, and relates to the technical field of network connection unmanned vehicle cooperative control and intelligent traffic. Firstly, a path information protection mechanism is provided for preventing an alien invading vehicle from tracking a motorcade and ensuring the safety of motorcade path information. In addition, a predictor model is established to improve the estimation performance of the adaptive law, and a variable gain nonlinear expansion state observer is designed to approach and compensate the total disturbance. Then, by introducing a variable-gain hyperbolic tangent tracking differentiator, the problem of'complexity explosion 'caused by repeated derivation of a virtual controller in a backstepping method is avoided; and finally, a distributed prediction cooperative controller is constructed, and stable and safe driving of the whole heterogeneous network connection fleet is ensured.

The invention relates to the technical field of industrial automation control and dynamic simulation, and discloses a centralized control console and 3D model linkage virtual-real simulation system, which comprises a control signal sampling interface, a load response modulation unit, a dynamic model evolution unit and a virtual-real closed-loop feedback unit, the load response modulation unit performs energy consumption weight accumulation on all the virtual controlled objects in transient action to generate a global time scaling factor so as to correct an inertia time constant of the system in real time; the dynamic model evolution unit introduces a hard limiting boundary by using an amplitude limiting link and calculates a process variable; the virtual-real closed-loop feedback unit extracts a control deviation signal and drives a physical instrument to generate a nonlinear damping action, and by establishing a global load modulation model based on energy constraint, a discrete control system spontaneously emerges a nonlinear hysteresis characteristic conforming to physical energy conservation under the low calculation power condition without complex fluid network solution.

The present invention provides a satellite flexible vibration suppression attitude control method. By adopting the idea of cascading input-to-state stability design, an attitude angle closed-loop control and an angular velocity tracking control form a cascaded system. The attitude controller is designed in a hierarchical manner. A second-order command filter is used to assign saturation constraints for tracking the virtual angular velocity and the virtual control quantity. The control method has the characteristics of small computational load and easy implementation in engineering. The flexible vibration suppression attitude controller realizes the smoothing processing of the angular velocity tracking command and the actuator control command by configuring the constraint amplitude, damping coefficient, and natural oscillation frequency of the command filter, so that the maximum angular velocity and angular acceleration of the satellite are constrained, and the angular acceleration of the excitation source of the satellite flexible attachment is limited. During the large-angle attitude maneuver, the satellite is constrained by the second-order saturation command filter, and the angular acceleration becomes zero after reaching the maximum angular velocity, and the vibration of the flexible attachment is suppressed.

The invention provides a simulation test method and device for an automatic driving algorithm, computer equipment and a medium. The simulation test method comprises the following steps: constructing a simulation test scene; inputting the virtual sensor data into an automatic driving algorithm to obtain a virtual control instruction; when a driving traffic participant corresponding to the driving vehicle is associated with a preset behavior model, simulating a first dynamic response of the driving vehicle to the virtual control instruction in the simulation test scene; determining first simulation test data based on the first dynamic response and a corresponding preset reference response; when the driving traffic participant corresponding to the driving vehicle is associated with a non-preset behavior model, simulating a second dynamic response of the driving vehicle to the virtual control instruction in the simulation test scene; determining second simulation test data based on the second dynamic response and a corresponding preset reference response; and determining target simulation test data based on the first simulation test data and the second simulation test data. Therefore, the simulation test efficiency of the automatic driving algorithm is effectively improved.

The invention discloses a self-adaptive finite time fuzzy safety control method for a flexible joint mechanical arm, which comprises the following steps that a flexible joint mechanical arm state space model influenced by spoofing attack is established, and a control signal comprises an unknown time-varying parameter and an unknown bounded attack function; introducing a Nussbaum function meeting a preset limit integral property; designing a control method based on a finite time stability principle, and ensuring that a system state converges to a bounded residual set within finite time; a fuzzy logic system is adopted to approach an unknown nonlinear function in the mechanical arm model; defining an error variable through coordinate transformation, and constructing a parameter which exponentially decays along with time; constructing a Lyapunov function containing the exponential decay parameter, and designing a virtual control function, a controller and a parameter adaptive law based on the function; and the Nussbaum function is constructed to be used for processing the unknown time-varying parameters. According to the invention, the influence of spoofing attacks on state signals can be reduced.