291 results about "Virtual control" patented technology

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 invention discloses an autonomous surface ship elastic train formation control method based on reinforcement learning. The method comprises the steps of obtaining a virtual ship reference signal according to a constructed time-varying adjustment mechanism; obtaining error data of the following ship based on the virtual ship reference signal and the nonlinear mathematical model so as to construct a ship virtual control law, and carrying out filtering processing on the virtual control law in the advancing direction and the yawing direction of the ship so as to obtain a filtering signal; defining a dynamic error according to the filtered signal to obtain a dynamic error derivative, and adopting a neural network to approach the dynamic error derivative to obtain an optimized dynamic error derivative; constructing a weight updating law of the actor neural network and the critic neural network according to the error data; and based on the weight updating law, designing a formation controller and an adaptive law according to the optimized dynamic error derivative in combination with the dynamic error. According to the method, the technical problem that the existing method lacks perception and recognition of the communication state and cannot effectively realize adaptive compensation of model uncertainty and unknown environment disturbance is solved.

The invention provides an anti-disturbance unmanned aerial vehicle trajectory tracking control method, system and device and a medium. The method comprises the following steps: establishing a six-degree-of-freedom rigid body dynamic model of a four-rotor unmanned aerial vehicle; selecting an unmanned aerial vehicle feasible trajectory of the kinetic model as an expected trajectory, and introducing a coupling attitude; designing a position loop control law, generating a virtual control force based on a smooth terminal sliding mode control surface, and calculating an actual thrust; designing an attitude loop control law, representing an attitude error based on Lie group SO (3), constructing an attitude tracking controller with a stable global index, and outputting a control torque; constructing a four-order state observer to estimate the angular velocity and the angular acceleration of the coupling attitude, and replacing a true value with an estimated value to participate in control law calculation; thrust and control torque are converted into thrust input of the unmanned aerial vehicle, the unmanned aerial vehicle is driven to track an expected trajectory, and the problems that in trajectory tracking control of the four-rotor unmanned aerial vehicle, dependence on position acceleration measurement is high, noise is amplified through differential derivation, disturbance rejection is weak, and real-time calculation burden is large are solved.

The invention defines an Internet of Things containerization virtual PLC system based on star flash. The system comprises a cloud server, at least one fog end node, a star flash wireless communication module and field end equipment, two normal forms are converted: 1, a dynamic migration normal form of control logic is realized, and a PLC is not a static entity bound to specific hardware but a control unit capable of flexibly scheduling and seamlessly migrating among computing power nodes through containerization and thermal migration technologies, so that the system availability and the resource utilization rate are fundamentally improved; and 2, a wireless normal form of field communication initiatively establishes a star flash technology as a core communication link of a virtual PLC and field equipment, and a deterministic wireless link provided by the wireless normal form effectively solves the core bottleneck of uncontrollable time delay and reliability of the traditional wireless technology, so that industrial-grade control is possible to get rid of wired constraint. Through the synergistic effect of the two normal forms, the containerized virtual control system which is high in toughness and flexibility and extremely flexible in deployment, operation and maintenance is jointly formed.

The invention belongs to the technical field of EL system control, and discloses a preset performance control method considering dynamic and constraint of an execution mechanism. The method comprises the following steps: firstly, establishing a system dynamics model considering dynamic and input saturation constraints of an executing mechanism; then, designing an asymmetric tubular performance boundary to restrain a system tracking error, and defining a conversion error according to the system tracking error; meanwhile, a disturbance observer based on immersion and invariance is designed, and composite disturbance is estimated. Furthermore, a tubular preset performance controller is designed by adopting a backstepping method, a virtual control law and an expected torque are constructed, and a multi-state auxiliary system is introduced to compensate the input saturation influence. And finally, a control instruction is generated by integrating the auxiliary system state, the virtual control law, the expected torque and the interference estimation value, and the control instruction acts on the system after being processed by a saturation function. According to the method, actuator dynamics, input saturation and external disturbance can be processed at the same time, and tracking errors are ensured to strictly follow a preset performance boundary.

The invention provides an unmanned surface vehicle course tracking control method with signal quantization based on a double-expansion observer, and the method comprises the steps: building a third-order response type unmanned surface vehicle course control mathematical model according to the characteristics of a ship and the sea condition information of a surrounding environment; designing a double-expansion observer model for simultaneously estimating matched interference and non-matched interference in the ship course tracking control system and observing uncertain items and external interference in the ship control system; based on a backstepping method and a dynamic surface control algorithm, a course controller of the unmanned surface vehicle is designed, and the calculation complexity brought by a virtual control law is reduced; based on the Lyapunov stability theory, the stability of the designed unmanned surface vehicle course tracking control system with state quantization and input quantization is proved, all signals in a closed-loop system are consistent and bounded in a semi-global mode, and the tracking error is arbitrarily small by adjusting parameters of a controller.

The invention discloses a piezoelectric micro-positioning platform preset performance control method based on an extended state observer, and the method mainly comprises the steps: firstly, building a piezoelectric micro-positioning platform system model considering input hysteresis and unknown disturbance; secondly, designing an extended state observer based on a radial basis function neural network to estimate an unmeasurable state of the system and lumped disturbance containing input hysteresis; then, a preset performance function is used, so that the overshoot performance of the system is effectively improved; thirdly, in combination with a preset performance function, a first-order sliding mode differentiator and an expansion state observer, providing a virtual control law and an adaptive control law; and finally, a preset performance controller is utilized, a Lyapunov stability theory is combined, proper parameters are selected to ensure that the closed-loop system is kept stable within preset time, and tracking errors are controlled within a set error range.

The invention belongs to the technical field of robot control, and discloses a fuzzy adaptive control method and system for uncertain robot system constraints. A dead zone model is integrated into an uncertain robot kinetic equation, a robot system module is established, feedback joint displacement state information is output in real time through the robot system module, and unmeasurable speed and acceleration state information is processed through a filter module, a virtual controller module and a self-adaptive law module. And a virtual control signal and a fuzzy adaptive law parameter are obtained, and dynamic change information is obtained through a fuzzy logic system in a fuzzy adaptive controller module. According to the method, parameter uncertainty caused by unknown robot system parameters or uncertainty and dead zone characteristics caused by non-controlled object factors such as external disturbance are solved, and accurate tracking control of the system state under boundary constraint is realized.

The invention provides a motorcade active-disturbance-rejection control method and system with a variable time interval strategy. The method comprises the following steps: acquiring state information of each vehicle in a vehicle queue system; the leader vehicle and the following vehicle carry out information transmission; under the condition of considering external disturbance, a vehicle dynamics model referring to the Newton second law is established, and a variable time interval strategy is constructed; compensating unmodeled dynamic and external disturbances in the vehicle dynamics model by using a time-varying gain expansion state observer in an active disturbance rejection control technology, and constructing a virtual controller and an actual controller based on a backstepping method; and according to the constructed virtual controller and the actual controller, realizing position and speed synchronization of the following vehicle and the leading vehicle in the queue under the condition of considering unmodeled dynamics and external disturbance. According to the method, the non-smooth problem at the saturation threshold is solved, the fluctuation influence can be effectively reduced, the safety is guaranteed, and the passing efficiency is improved; and the problem of gain attenuation is solved while the high gain characteristic is reserved.

The invention relates to the technical field of intelligent control, and particularly discloses an intelligent control method and system for shell laser welding. The method comprises the steps that heat flow distribution characteristics on a welding path are collected to construct a heat saturation matrix; generating a transient thermal resistance factor adaptive to the current heat dissipation capability based on the thermal saturation matrix; carrying out advanced rolling prediction by utilizing the transient thermal resistance factor, and extracting a heat flow inflection point coordinate of which the rheological property of the molten pool is mutated; constructing a virtual control boundary independent of the physical inflection point; and when the welding displacement triggers the virtual control boundary, a pre-judgment type negative gain damping strategy is generated. The system comprises a heat flow collection module, a thermal resistance analysis module, a sudden change analysis module, a boundary construction module and a welding regulation and control module. According to the method, by constructing the advanced control strategy containing thermal hysteresis compensation, molten pool instability caused by heat accumulation can be restrained, and heat balance regulation and control in the welding process are achieved.

The invention relates to an accurate evaluation and dynamic optimization system for cerebral infarction ultra-early reperfusion treatment, in particular to the field of biomedicine.Heterogeneous image data are fused through multi-center federal learning, and a high-robustness standardized brain characteristic spectrum is constructed; the real-time physiological parameters are utilized to drive the dynamic graph network, and the pathological process of the ischemic penumbra evolved along with time is accurately simulated; a core infarction zone and half-dark band probability graph with reasonable spatial distribution is generated by introducing a multi-task classifier with mutual exclusion constraints; and finally, a virtual contrast perfusion image is generated in combination with the individual blood vessel conditions of the patient to perform personalized calibration, so that the accuracy and individualization level of the delineation of the penumbra are remarkably improved, more reliable and dynamic decision support is provided for a clinician to formulate an ultra-early reperfusion treatment scheme, and the risk of insufficient treatment or excessive treatment is effectively avoided.

The application relates to the technical field of multi-spacecraft cooperative control, and discloses a multi-spacecraft grouping consistency restraint control method and device under optimized FLS, which comprises the following steps: acquiring the network topology of a heterogeneous multi-spacecraft system and constructing a multi-subgroup directed communication topology network, constructing a spacecraft attitude control system model based on modified Rodrigues parameters; approximating unknown nonlinear terms in the model through a fuzzy logic system, constructing a fuzzy logic system based on a gradient descent algorithm and Armijo line search criterion; constructing a restraint control term and using a backstepping method to construct a virtual control law, combining the output of the fuzzy logic system based on the gradient descent algorithm and the Armijo line search criterion to construct an actual control input law, so that grouping consistency restraint control of the heterogeneous multi-spacecraft system is realized. The application can improve real-time approximation precision and adaptive step length adjustment capability while guaranteeing grouping consistency, and can enhance topology applicability and task cooperation flexibility.

This invention discloses a ship dynamic positioning anti-interference control method considering vertical dynamic optimization, comprising: establishing a four-degree-of-freedom nonlinear dynamic model of the ship and obtaining the error vector by combining the desired pose; defining a virtual control law by backstepping and processing the velocity error using a first-order filter; approximating the uncertainties in the model based on an improved Actor-Critic reinforcement learning framework and designing an interference observer to estimate external disturbances; calculating the compensated desired acceleration by combining the approximation output of the uncertainties, the estimated value of the external disturbances, and the velocity error; obtaining the thruster pitch ratio based on the desired acceleration and generating the final control command through a thrust distribution model. This invention can effectively handle model uncertainties and external environmental disturbances in ship dynamic positioning, especially optimizing vertical dynamic performance and improving control accuracy, response speed, and system robustness.

The application discloses a kind of anti-network attack's multi-vehicle safety platoon control method and system, the method first establishes multi-vehicle queue dynamics model;Second, design fuzzy state observer to estimate vehicle state and unknown nonlinear dynamics;Then, introduce funnel function to build time-varying performance boundary, and the double constraints of vehicle anti-collision and keep communication are converted into funnel constraints of spacing tracking error;Then, based on backstepping method and funnel performance error, design virtual controller and adaptive law, and obtain adaptive safety controller to obtain control input;Finally, through Lyapunov stability analysis, the tolerance threshold condition that system can still maintain final consistent bounded stable after suffering replay attack is quantitatively obtained.The application simplifies design through funnel control, avoids complex barrier lyapunov function, and for the first time clearly provides quantified anti-interference ability to replay attack, enhances the network security and practicality of multi-vehicle queue system.

The present application belongs to the technical field of trajectory tracking control of nonholonomic wheeled mobile robots, and specifically discloses a trajectory tracking control method and system for nonholonomic wheeled mobile robots. In the trajectory tracking process of the nonholonomic wheeled mobile robot, the present application method converges the position tracking error and the attitude tracking error to an arbitrarily small compact set near the origin within a limited time through steps such as designing an adaptive neural state observer, a finite-time command filter, an error compensation mechanism, a virtual control input, and an actual control signal. The present application not only avoids the calculation complexity explosion problem caused by repeated derivation of the virtual control signal in the traditional backstepping method, but also guarantees that the trajectory tracking error of the nonholonomic wheeled mobile robot converges to an arbitrarily small neighborhood within a limited time under the conditions of unknown nonlinear dynamics and unmeasurable speed, and all signals in the closed-loop system are ultimately bounded.

The invention discloses a suspension flight anti-swing control method for a quad-rotor unmanned aerial vehicle. Comprising the following steps: acquiring an expected position, a yaw angle, an actual position and an attitude angle of the quad-rotor unmanned aerial vehicle in real time, and acquiring a load swing angle in real time; compensating the expected position according to the load swing angle to obtain a compensated expected position; position control is carried out according to the actual position and the compensated expected position of the quadrotor unmanned aerial vehicle, a virtual control quantity is obtained, and the vertical virtual control quantity is expected vertical pulling force; performing attitude calculation according to the virtual control quantity to obtain an expected roll angle and a pitch angle; attitude control is carried out according to the expected attitude angle and the actual attitude angle, expected torque is obtained, then expected rotating speeds of the four rotor motors are obtained, and the four-rotor unmanned aerial vehicle is controlled according to the expected rotating speeds. The damping controller provided by the invention considers the coupling characteristic between the four rotors and the hanging load, so that the hanging system can effectively inhibit the load swing angle while accurately following the expected path.

The invention discloses a post-processing method and device for AUV positioning data, a medium and a program product. The method comprises the following steps: acquiring a first measuring point sequence and a second measuring point sequence of the AUV; wherein the first measuring point sequence is a positioning data set determined by a strapdown inertial navigation system, and the second measuring point sequence is a positioning data set determined by an ultra-short baseline underwater positioning system; performing jump point deletion on the second measuring point sequence, performing trajectory fitting, and determining a virtual control point based on a fitting trajectory; constructing a measurement section based on two adjacent virtual control points, and matching the measurement section with each first measurement point in the first measurement point sequence according to time; and for each measurement section, correcting the first measurement point in the measurement section according to the virtual control point to obtain a corrected measurement point, and determining a correction track of the AUV based on each corrected measurement point. According to the technical scheme, the correction of the AUV positioning data is realized by constructing the virtual control point, and the precision of the AUV positioning data is improved, so that the accuracy and applicability of an underwater task are met.

A recursive RISE control method and system for maglev train levitation systems is disclosed. The control method includes: constructing the dynamic equations and voltage balance equations of the electromagnets based on a single-point levitation system, and then constructing a dynamic model of the single-point levitation system accordingly; designing a virtual control law, and then designing a recursive RISE controller based on the backstepping method by combining the dynamic model of the single-point levitation system and the virtual control law; performing stability analysis on the RISE controller to obtain its stability conditions; and, based on satisfying the stability conditions, using the RISE controller to perform real-time control of the levitation gap of the maglev train levitation system. This invention has excellent anti-interference capabilities, reducing the impact of external interference or model uncertainty on levitation accuracy. Furthermore, by handling the nonlinear relationship between voltage and current through the backstepping method, this invention avoids the model mismatch problem caused by linearization.

Methods and systems for generating control systems that can recognize and preserve zone allocation constraints in a multiagent system are disclosed. The methods and systems provide for determining a given agent's state within its current zone allocation, transforming the given agent's state into an unconstrained representation (e.g., using a mia-diffeomorphic mapping), determining a virtual control signal for the given agent based on the unconstrained representation, transforming the virtual control signal into an actual control signal via an inverse function, and communicating the actual control signal to the given agent based on a role of the agent and a communication protocol of the system. Other aspects, embodiments, and features are also claimed and described.

The application discloses an autonomous water surface ship elastic train formation control method based on reinforcement learning, comprising the following steps: obtaining a virtual ship reference signal according to a constructed time-varying adjustment mechanism; obtaining error data of a following ship based on the virtual ship reference signal and a nonlinear mathematical model, so as to construct a ship virtual control law; performing filtering processing on the virtual control law of the forward direction and the bow swing direction of the ship to obtain a filtering signal; defining a dynamic error according to the filtering signal to obtain a dynamic error derivative, and using a neural network to approximate the dynamic error derivative to obtain an optimized dynamic error derivative; constructing a weight update law of an actor neural network and a critic neural network according to the error data; and based on the weight update law, designing a formation controller and an adaptive law according to the optimized dynamic error derivative combined with the dynamic error. The application solves the technical problem that the existing method lacks communication state identification and cannot effectively realize adaptive compensation for model uncertainty and unknown environmental disturbance.

The invention provides an active-disturbance-rejection fault-tolerant control method and system for aerial refueling of an unmanned aerial vehicle, and belongs to the technical field of aerial refueling anti-interference control, and the method comprises the steps: introducing a virtual control variable, building a six-degree-of-freedom motion equation of the unmanned aerial vehicle, converting the six-degree-of-freedom motion equation into an affine nonlinear model, and dividing the state variable of the unmanned aerial vehicle into five control loops; acquiring real-time position information of the refueling taper sleeve, generating a smooth docking reference trajectory by using a three-section method, and converting the expected position instruction into an expected position instruction of the mass center of the unmanned aerial vehicle; based on an ADRC algorithm, an LESO and a controller are designed for each control loop; generating a control signal of each control loop according to the virtual control variable; and in each stage of air refueling operation, adopting a mode fading algorithm to realize smooth switching between a guidance strategy and a controller in each stage, outputting a comprehensive control signal, outputting the comprehensive control signal to an unmanned aerial vehicle execution mechanism, and driving the unmanned aerial vehicle to track an expected position instruction of the mass center of the unmanned aerial vehicle. The safety of aerial refueling of the unmanned aerial vehicle is guaranteed.

The invention discloses a Delta robot trajectory tracking method based on fuzzy-RBF (Radial Basis Function) control. The Delta robot trajectory tracking method comprises the following steps: firstly, establishing a conventional dynamic model of a Delta robot; a virtual control signal is introduced, a sliding mode surface is constructed, and a control law of a dynamic surface sliding mode controller is designed to ensure the stability and convergence of the system. And constructing a specific fuzzy logic system for adjusting the control gain. A radial basis function (RBF) structure is embedded into a fuzzy membership function, and the center and width of the membership function are iteratively updated by adopting an online adaptive optimization algorithm based on gradient descent, so that dynamic self-learning and parameter adaptation of a fuzzy system are realized. Finally, the output of the designed fuzzy-RBF self-adaptive dynamic surface sliding mode controller acts on a robot joint driving system, and high-precision trajectory tracking control of the Delta robot end effector is successfully achieved. A simulation result verifies the effectiveness and robustness of the provided control method in the aspects of processing parameter uncertainty and external disturbance.

The application relates to the technical field of industrial automation control and dynamic simulation, and discloses a virtual-real simulation system with linkage of a centralized control operation platform and a 3D model, 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 accumulates energy consumption weights of all virtual controlled objects in transient motion to generate a global time scaling factor for real-time correction of the inertial time constant of the system. The dynamic model evolution unit introduces a hard limiting boundary by using a limiting link and calculates process variables. The virtual-real closed-loop feedback unit extracts a control deviation signal and drives physical instruments to generate nonlinear damping actions. The application establishes a global load modulation model based on energy constraints, and under the condition of low computing power without complex fluid network solving, makes the discrete control system spontaneously emerge nonlinear hysteresis characteristics conforming to physical energy conservation.

According to the semiconductor bonding equipment operation control method and the chip alignment virtual simulation control method provided by the invention, the bonding parameter range is determined by combining the user authority, the to-be-processed bonding chip parameter and the current operation state of the bonding equipment, the optimal bonding process parameter is output, and the input bonding process parameter is limited and adjusted; in combination with the process automation model, the bonding parameters fed back by the user click the corresponding operation interface component or are input into the corresponding frame, so that the learning time and the operation time of the user on the operation interface of the bonding equipment are shortened, and the efficiency and the accuracy of using the bonding equipment are improved; in the chip alignment step, the step length corresponding to each operation step is adjusted in combination with aligned precision simulation, the range in which a user can operate the chip to move in each precision alignment stage is changed, adjustment of the user in a higher-precision alignment stage does not affect a previous low-precision alignment result, meanwhile, adjustment of double focal lengths and relative angles is simulated, and the alignment precision is improved. Therefore, the efficiency of the chip alignment step in actual operation is improved.

An aspect of the present disclosure is directed to a system for dynamic provisioning of hardware instances via reprogrammable fabric provided by a reprogrammable hardware device (RHD). The system preferably includes a memory having a first instruction set disposed therein, the first instruction set for provisioning a hypervisor processing unit (HPU) instance (also referred to herein as an orchestrator instance) within the reprogrammable fabric of the RHD, and a startup sequence for execution by the HPU instance. The startup sequence of the HPU instance is preferably configured to cause provisioning of at least a first hardware instance within the second portion of the reprogrammable fabric of the RHD, and for provisioning an interface instance to allow for a physical hardware device of the host computer system to communicate with the first hardware instance via a virtualized communication channel.

This invention discloses a distributed optimization and safe formation control method for multiple robotic arms with nonlinear uncertainty. By establishing a dynamic model of the multi-robotic arm system with nonlinear uncertainty, a dynamic event triggering method with internal system information is constructed. Each robotic arm broadcasts its position information to its neighboring nodes only when the triggering condition is met. A predetermined reference trajectory is generated for each robotic arm system, converging to the global optimum and satisfying formation constraints. The position tracking error between the actual output of the robotic arm system and the predetermined reference trajectory at each moment is calculated. The virtual control law designed in the first step of the back-reasoning is used as the target to be optimized. A quadratic programming problem is constructed by combining the safety constraint boundary inequality built with the control obstacle function to obtain the safe virtual control law. In the second step of the back-reasoning, the velocity tracking error between the actual state of the robotic arm and the safe virtual control signal is calculated, constructing a back-reasoning controller based on the obstacle Lyapunov function. This invention overcomes the control instability risk caused by strong nonlinearity and achieves high-precision trajectory tracking.

The application provides an air conditioning water system control simulation system and method, the air conditioning water system control simulation system comprises a user interaction server, a virtual control system and a physical model of an air conditioning water system deployed on the same edge device, the physical model comprises a first substitution program for calling a target function and a second substitution program called by the target function; when the air conditioning water system control simulation is performed, the user interaction server acquires a control program corresponding to the target function written by a user and sends the control program to the virtual control system; and the virtual control system runs the control program based on the physical model to realize simulation test of the target function. Thus, the simulation test of the air conditioning water system is realized without physical simulation, so that the application can provide a reference for development of the water system control program, improve iteration efficiency of program development, verify reliability and stability of the control program in advance, and reduce the Bug rate in program development.

This invention relates to the field of industrial automation control technology, specifically to an automatic control system for a multi-station collaborative surface treatment equipment, comprising a process gene mapping module, a predictive trajectory interlock module, and a bus closed-loop feedback module. This invention constructs a process topology control chain, utilizes a virtual control entity and a global resource occupancy table for advance simulation on the control system clock axis, triggers a hardware / software interlock mechanism and generates a spatiotemporal decoupling control signal when occupancy conflicts are identified; and uses the bus closed-loop feedback module to verify the spatial consistency between the measured feedback vector and the virtual control entity, triggering emergency stop protection and forcibly reconstructing the control signal when the deviation exceeds the virtual-real mapping residual limit. This invention achieves global asynchronous parallel scheduling and closed-loop safety control of multiple tasks on the production line, effectively solving the problems of low collaborative efficiency and equipment resource deadlock.