60 results about "Observer based" patented technology

This disclosure provides an adaptive STSMC hierarchical control method for depth tracking of an underwater vehicle. The method includes: using an adaptive line-of-sight guidance algorithm to estimate the vehicle's angle of attack in real time and obtain an expected pitch angle; employing a nonlinear interference observer based on a sliding mode surface error to detect unknown interference; and applying an STSMC controller with adaptive saturation compensation to determine the expected control rudder angle from the sliding mode surface error, the expected pitch angle, and the observed interference. The adaptive saturation compensation corrects the rudder angle based on the saturation deviation, which is determined by the previously calculated expected control rudder angle and the actual output rudder angle at the previous moment. By introducing an adaptive saturation compensator in the dynamic control layer, the issue of rudder angle saturation is mitigated, thereby enhancing both control performance and stability.

The invention discloses a predetermined time expansion state observer generation method and an observation error convergence method, which are applied to the technical field of aerospace, and comprise the following steps: constructing a controller for a second-order nonlinear system according to an all-drive system theory; converting the second-order nonlinear system according to the controller to obtain an all-drive system based on the main controller; wherein the main controller is a controller for controlling the all-wheel-drive system; designing a predetermined time expansion state observer based on the total disturbance and observation error of the all-wheel-drive system; wherein the predetermined time expansion state observer is an observer which limits the upper bound of convergence time of the observer based on a predetermined time parameter. Compared with most existing extended state observers which can only ensure asymptotic convergence and finite time or fixed time convergence, the observer generated based on the predetermined time extended state observer generation method can ensure that the observation error converges within the predetermined time, so that the converged predetermined time is more stable; and the user experience is improved.

The invention relates to a permanent magnet synchronous motor improved fractional order sliding mode active-disturbance-rejection control method based on an improved fractional order super-spiral sliding mode observer, and the method specifically comprises the steps: firstly, building a mathematical model of a PMSM in an alpha-beta and d-q coordinate system, designing an improved fractional order super-spiral sliding mode disturbance observer, and estimating the unknown disturbance in a system in real time; and finally, optimizing a steepest function and designing a fractional order tracking differentiator in combination with a fractional order calculus principle. A nonlinear state error feedback law is constructed, nonlinear calculation is carried out on the proportion, differential and integral of an error signal, and the anti-interference capability, the response speed and the control precision of the controller are improved; and combining a fractional order tracking differentiator, a fractional order state observer and a nonlinear feedback control law, and designing a fractional order sliding mode active-disturbance-rejection controller. According to the method, system buffeting is effectively weakened while the convergence speed is increased, and the robustness of the controller under load disturbance is effectively improved.

The invention discloses a vector six-rotor aircraft full-state control method based on a high-order dynamic model, and belongs to the field of vector rotor aircraft tracking control. The invention aims to solve the problems of poor angular acceleration estimation accuracy and low precision of the existing vector rotorcraft control method based on a jerk dynamics model. According to the invention, an angular acceleration observer based on a high-order dynamic model and a full-drive system theory is designed, effective estimation of an angular acceleration signal can be realized without depending on external sensor equipment, and high-precision and high-speed tracking of the position attitude of the six-degree-of-freedom vector six-rotor aircraft can be realized. The method is mainly applied to the pose tracking of the six-degree-of-freedom vector six-rotor aircraft.

This invention discloses a control method and system for a dual-link manipulator based on a neural network observer, comprising the following steps: Step 1. Establishing a dynamic model of the dual-link manipulator under external attacks and disturbances; Step 2. Establishing a neural network observer based on the dynamic model; Step 3. Establishing a control scheme for the dual-link manipulator based on reinforcement learning, the dynamic model, and the neural network observer; Step 4. Performing adaptive safety control of the dual-link manipulator based on the control scheme within the backstepping framework; This invention observes attacks and disturbances caused by unknown factors, as well as rapidly changing attacks and disturbances; Through a performance index function, the controller enables the control of the dual-link manipulator; The technical solution of this invention utilizes the learning ability of reinforcement learning algorithms and employs gradient descent to design an adaptive update rate for the Actor-Critic neural network, enabling the approximate controller to approximate the actual controller.

The invention discloses a method and a device for designing a multi-anti-interference incremental backstepping observer based on specified time, and belongs to the technical field of signal tracking and processing. The method comprises the following steps: establishing a system dynamics model containing time-varying disturbance and model uncertainty items; scaling the tracking error and the estimation error by using a scaling function so as to realize the accurate convergence of the system state and the disturbance estimation within the specified time T; combining the scaled error, introducing an incremental backstepping control thought, and designing an incremental backstepping observer capable of processing model uncertainty and multiple disturbances at the same time; under the condition that the total disturbance and the derivative thereof are assumed to be bounded, stability analysis is carried out through a Lyapunov function, and constraint conditions of system stability convergence are deduced; and finally, verifying the effectiveness and superiority of the observer under various input and disturbance working conditions through simulation. The method is suitable for a high-dynamic and time-sensitive precision control system.

The invention relates to the technical field of unmanned ship safety control, and discloses an anti-spoofing-attack self-adaptive sliding mode control method and system for an unmanned ship and a medium, and the method comprises the steps: S1, constructing an unmanned ship T-S fuzzy model under the spoofing attack and external disturbance; s2, designing a dual-adaptive sliding mode observer based on the unmanned ship T-S fuzzy model constructed in S1; s3, designing a sliding mode controller based on S1 and S2; and S4, forming a closed-loop control system based on S1-S3 to perform sliding mode control: integrating the unmanned ship T-S fuzzy model constructed in S1, the dual-adaptive sliding mode observer designed in S2 and the sliding mode controller designed in S3 to form the closed-loop control system, and realizing sliding mode control. According to the method, the dynamic suppression capability of the composite threat can be remarkably improved, precise compensation of a spoofing attack signal and external disturbance of the ocean is realized, high-precision zero-flutter control is realized under the coexistence of the spoofing attack and the external disturbance, and an autonomous control solution with safety, robustness and real-time performance is provided for the unmanned ship.

The invention discloses a robot anti-interference control method based on a neural network interference observer, and the method specifically comprises the following steps: 1, building a robot dynamics model containing external interference, and constructing a state space model; step 2, establishing a fixed time interference observer based on a radial basis function neural network, and performing external interference estimation on the robot kinetic model; and step 3, a fixed time sliding mode controller is designed based on the interference estimation result, and fixed time control under the condition of external interference is realized. According to the robot anti-interference control method based on the neural network interference observer, the interference is accurately and rapidly estimated by using the fixed time interference observer, the convergence of the system state in the fixed time is realized by combining the fixed time sliding mode controller, and the feedforward compensation and feedback suppression of the interference are combined, so that the system stability is improved. The method has the advantages of simple implementation mode, high interference estimation precision and high response speed.

The invention is suitable for the field of vehicle automatic control, and provides a reconfigurable vehicle cooperative control method of a dual-predictive controller, and the method comprises the steps: designing a reconfigurable vehicle observer based on extended Kalman filtering, and dynamically adjusting a state vector and a system matrix dimension to adapt to the increase and decrease of a module; establishing a distributed vehicle dynamics model and a model library, dynamically configuring the degree of freedom according to the number of modules, and realizing configuration mapping through a parameterized interface; and a layered coupling controller is constructed, an upper-layer model predicts, controls and outputs total longitudinal force and additional yawing moment, and a lower-layer quadratic programming dynamically distributes driving moment to each hub motor. According to the method, a state perception-model reconstruction-control optimization closed loop is formed, cooperative control with small state error and multi-target dynamic balance is realized, and the method is suitable for reconfigurable vehicles in emergency rescue, polar region exploration and other scenes.

The embodiment of the present application relates to the technical field of computer software, and discloses a multilingual dynamic switching method based on an observer mode and related devices, the method comprising: when a program starts, a resource management module asynchronously loads translation resources of a default language and preloads commonly used language resources to a cache, and a mapping relationship between text keys and translation resources is established; each interface control is registered to an observer registration module as an observer, and a layered control tree of the observer is formed; when a user switches languages, the resource management module loads target language resources; a difference detection module compares differences between texts, and identifies an observer set that needs to be updated; an event bus module publishes layered update events according to the observer set that needs to be updated and a current interface state; and an update strategy module controls the observer layer that needs to be updated to execute the update of the interface control according to the layered update events and the target language resources. The embodiment of the present application realizes efficient, intelligent and extensible multilingual dynamic switching of an interface.

The application provides a vehicle suspension state parameter estimation method and device, and relates to the technical field of intelligent control of vehicle suspension, and the method comprises the steps of: constructing an interactive state observer based on at least two physical characteristic parameters of a vehicle suspension; determining prior state prediction parameters corresponding to each sub-observer based on a previous model probability and a transition probability matrix corresponding to each sub-observer; updating the prior state prediction parameters of each sub-observer based on current observation data corresponding to each sub-observer to obtain posterior state estimation parameters of each sub-observer; adaptively determining a current forgetting factor corresponding to each sub-observer based on the current observation data, an observation matrix and the prior state prediction parameters of each sub-observer; and fusing the current model probability, the posterior state estimation parameters and the current forgetting factor corresponding to all sub-observers to obtain a current overall state parameter estimation value corresponding to the interactive state observer. The application can improve the estimation accuracy of the suspension state parameters.

The invention relates to a large-diameter bearing quenching optimization method and system based on interactive multi-model estimation. The method comprises the following steps: determining state parameters of a quenching process; through the state parameters and a holosymmetric polytope method, an integrated nonlinear system is constructed; obtaining a linear expression of the nonlinear system through a Taylor expansion method with remainder terms; based on the linear expression, at least determining prediction equations of the two observers; calculating a weight and a set membership estimation initial value of each observer based on a preset interactive fusion rule and the historical state parameter value; calculating a residual set of each observer based on the prediction equation and the set membership estimation initial value of each observer; updating the weight of each observer in real time according to the residual set and the probability model; and calculating an estimated value of the nonlinear system through an interactive fusion rule. According to the method, through multi-model probability interaction and linearization of the set membership set, the accuracy and robustness of quenching control of the large-diameter bearing are improved.

The application discloses a humanoid robot obstacle-crossing reinforcement learning control method based on DCM constraint, an external force observer based on hyperbolic tangent sliding mode compensation is designed for quickly estimating external force impact, and is used for estimating external force impact suffered by the robot; a motion divergence quantity (DCM) model considering external force influence is established based on a traditional linear inverted pendulum model, and a reward function based on DCM optimization is designed to improve stability. On this basis, a multi-dimensional reward function covering dynamic leg lifting height reward, foot landing area reward, obstacle-crossing reward and the like is designed to prevent training from falling into local optimum. In view of the problems of slow training speed and excessively high calculation cost in the simulation environment where a visual sensor is used to identify the terrain, a sampling point grid based on terrain height is designed to improve the perception accuracy and real-time performance of the system on complex obstacle terrains.

This invention provides a fault-tolerant encirclement control method and system for uncertain multi-agent systems. The method includes: constructing information interaction relationships between the leader and followers, and among the followers themselves, using a directed topology graph; establishing several leader system models and follower system models with unknown inputs; designing a distributed observer based on the leader system model; designing a follower state observer and establishing an actuator fault adaptive law model; establishing a tracking error model based on the distributed observer and solving the steady-state part of the controller; establishing a follower auxiliary system model, designing a performance index function, and obtaining the optimal transient control strategy expression; implementing an online iterative algorithm using a neural network to approximate the optimal transient controller part; and using a closed-loop control system to achieve encirclement control of the multi-agent system. This invention solves the technical problems of poor applicability, low robustness, and errors between control data and actual conditions.

The embodiment of the invention relates to the technical field of computer software, and discloses a multi-language dynamic switching method based on an observer mode and a related device.The method comprises the steps that when a program is started, a resource management module asynchronously loads a translation resource of a default language and preloads a common language resource to a cache; establishing a mapping relationship between the text key value and the translation resource; each interface control serves as an observer to be registered to the observer registration module, and a hierarchical control tree of the observer is formed; when a user switches languages, the resource management module loads target language resources; the difference detection module compares the differences between the texts and identifies an observer set needing to be updated; the event bus module issues a hierarchical update event according to an observer set needing to be updated and a current interface state; and the updating strategy module controls the observer needing to be updated to hierarchically execute updating of the interface control according to the hierarchical updating event and the target language resource. According to the embodiment of the invention, efficient, intelligent and extensible multi-language dynamic switching of the interface is realized.

The invention discloses an autonomous reconstruction method for an abnormal operation state of an aviation turbine engine, and relates to the technical field of health management and intelligent control of aviation engines, and the method comprises the steps: constructing a physical model of operation state evolution; determining a predicted value of a running state variable at the current moment based on the physical model of running state evolution; constructing a second-order expansion state observer of the state evolution power system based on the predicted value of the operation state variable at the current moment by adopting a super-spiral sliding mode control algorithm; constructing a Lyapunov function based on a second-order extended state observer; when the Lyapunov function meets a preset condition, determining a sliding mode control law; constructing an abnormal state autonomous reconstruction observer based on a sliding mode control law; and determining an estimated value of the abnormal operation state of the aviation turbine engine at the current moment based on the abnormal state autonomous reconstruction observer. According to the method, the problem that the abnormal operation state is difficult to reconstruct accurately due to uncertain factors is effectively solved.

This invention relates to the field of vehicle automatic control and provides a cooperative control method for reconfigurable vehicles using dual predictive controllers. The method includes: designing a reconfigurable vehicle observer based on extended Kalman filtering, dynamically adjusting the state vector and system matrix dimensions to adapt to module additions or subtractions; establishing a distributed vehicle dynamics model and model library, dynamically configuring degrees of freedom according to the number of modules and implementing configuration mapping through a parameterized interface; and constructing a hierarchical coupled controller, where the upper-level model predicts and controls the output of the total longitudinal force and additional yaw moment, while the lower-level quadratic programming dynamically allocates the driving torque to each hub motor. This invention forms a closed loop of "state perception - model reconstruction - control optimization," achieving cooperative control with small state errors and multi-objective dynamic balance, suitable for reconfigurable vehicles in scenarios such as emergency rescue and polar exploration.

The invention relates to the technical field of spacecraft control, and provides a spacecraft rendezvous control method based on a disturbance observer and related equipment, and the method comprises the steps: constructing a kinetic model of orbit rendezvous of a target spacecraft at an earth-moon translation point, and designing the disturbance observer based on the kinetic model; defining a cost function based on the system state quantity of the target spacecraft, and constructing an action controller of the target spacecraft according to the cost function; calculating a control interference estimated value of the target spacecraft according to the interference observer, and calculating an optimal control value according to the action controller; and calculating a final control value of the target spacecraft based on the control interference estimated value and the optimal control value, and performing orbit intersection control on the target spacecraft based on the final control value. According to the method, the spacecraft rendezvous control precision can be improved.

The application discloses a kind of cluster unmanned plane fixed time quick adaptive fault-tolerant cooperative control method, first, design a kind of elasticity distributed fixed time observer based on topology switching signal, for accurately estimating virtual leader state and weakening the influence of denial-of-service attack.Second, by combining power integrator technology with topology switching signal, for follower unmanned plane affected by unknown actuator fault, construct fixed time adaptive fault-tolerant cooperative control protocol, so that the cluster unmanned plane system can still realize trajectory tracking in fixed time under the condition of actuator fault and denial-of-service attack coexistence.Finally, by radial basis function neural network, online approximation of composite nonlinear disturbance is realized, more accurate cooperative control is realized.The application can be applied to cluster unmanned plane formation fault-tolerant cooperative control under actuator fault and denial-of-service attack.

The invention relates to the technical field of motor control, in particular to a switched reluctance motor sensorless control method, which adopts a sliding mode observer based on a variable boundary layer to replace an original position sensor of a system, and adopts an improved sigmod function to replace a traditional sign function, so that the boundary layer is variable, buffeting is reduced, and the stability of the system is improved. The device is suitable for adjustment under various working conditions. Besides, the invention further provides a novel approaching law which is characterized in that the approaching rate changes along with the change of the position of the sliding mode, the time needed by the system state quantity to reach the sliding surface can be shortened, and buffeting generated when the system state quantity reaches the sliding surface can be effectively reduced.

The application discloses a thruster fault identification method and device based on a sliding mode observer. The method comprises the following steps: designing a sliding mode observer based on a spacecraft dynamics model; calculating real three-axis angular velocities of the spacecraft in a current control period based on gyro outputs of the spacecraft system; estimating estimated three-axis angular velocities of the spacecraft in the current control period based on the sliding mode observer; determining a residual function in the current control period based on the real three-axis angular velocities and the estimated three-axis angular velocities; determining whether a thruster fault exists in the current control period based on a relationship between the residual function and a preset threshold; if the thruster fault exists, calculating an estimated thruster fault matrix in the current control period based on the residual function, and calculating an included angle between the estimated thruster fault matrix in the current control period and each column of a predetermined thruster fault matrix, and determining a thruster corresponding to a column with the minimum included angle as a fault thruster. The application can locate the fault to each thruster.

The application relates to the technical field of spacecraft control, and provides a spacecraft rendezvous control method based on an interference observer and related equipment, the method comprising the following steps: constructing a dynamic model of target spacecraft rendezvous on a geosynchronous orbit, and designing an interference observer based on the dynamic model; defining a cost function based on system state quantities of the target spacecraft, and constructing an action controller of the target spacecraft according to the cost function; calculating a control interference estimation value of the target spacecraft according to the interference observer, and calculating an optimal control value according to the action controller; calculating a final control value of the target spacecraft based on the control interference estimation value and the optimal control value, and performing orbit rendezvous control on the target spacecraft based on the final control value. The method can improve the precision of spacecraft rendezvous control.

The application is directed to the problem of fault-tolerant formation control of fuzzy multi-leader UAV system. A fault-tolerant formation control method based on reduced-order observer is proposed, including: using T-S fuzzy model to model the multi-leader UAV system; transforming the original system into a reduced-order form, and then deriving an augmented form; designing a reduced-order fault observer based on the intermediate variable for the reduced-order augmented system to estimate the state of the follower UAV, process fault and system uncertainty; using the relative state information to design a tracking fault-tolerant formation controller, taking the estimation of process fault and system uncertainty as compensation term; designing adaptive parameters for the reduced-order fault observer and the tracking fault-tolerant formation controller; verifying the performance of the reduced-order fault observer and the tracking fault-tolerant formation controller; the application can more prominently deal with the nonlinear and uncertain control problem, while reducing the calculation amount and improving the efficiency of distributed decision-making.

This invention relates to a full-state control method for vector hexacopter aircraft based on a high-order dynamics model, belonging to the field of vector hexacopter tracking control. The invention addresses the problems of poor accuracy and low precision in angular acceleration estimation found in existing vector hexacopter control methods based on jerk dynamics models. This invention designs an angular acceleration observer based on a high-order dynamics model and full-drive system theory, enabling effective estimation of angular acceleration signals without relying on external sensors. This allows for high-precision, high-speed tracking of the position and attitude of a six-DOF vector hexacopter aircraft. This invention is primarily applied to attitude tracking of six-DOF vector hexacopter aircraft.

The application provides a low-speed position sensorless control method based on an observer considering convergence effect q Firstly, a permanent magnet motor current model is used to construct q a shaft current sliding surface; then, a sliding mode observer based on the shaft current model of the sliding surface is designed to accurately estimate the rotor speed and integrate the rotor position. Affected by the convergence effect, when the observer is used for low-speed operation, large load mutation can cause motor stalling, and then cause the loss of signals for the observer, and the output speed and position disorder. Therefore, a table compensation strategy based on deep symbolic regression and data filling is provided, large load mutation data is generated based on small load mutation data, so that the position error can be compensated in real time, and the stalling problem caused by the convergence effect is eliminated. The application not only realizes noiseless low-speed position sensorless control, but also solves the stalling problem caused by the convergence effect under the condition of low-speed large load mutation.

This invention discloses a design method for a cooperative target pose observer based on a novel potential function, used for real-time position and attitude estimation of cooperative targets in space. Common pose estimation methods typically include static and dynamic methods. Dynamic methods combine observation information with the system's kinematic or dynamic information, and under the same conditions, usually yield better estimation results than static methods. As a dynamic estimation method, the observer is valued for its simple structure and ease of application. Addressing the problem of the limited variety of potential functions commonly used in current pose estimation observers, this invention, based on existing potential functions, proposes a method for constructing an observer based on a novel potential function. This method can be used for synchronous relative pose estimation during operations by a space robotic arm on a cooperative target. The observer derived from the novel potential function designed in this invention not only possesses the same theoretical stability characteristics as existing observers but also demonstrates better estimation performance in practical applications.

This application discloses a time-varying formation tracking method and system for multi-agent systems based on the internal model principle, relating to the field of disturbance suppression. The method includes: initializing all relevant parameters; designing two observers based on the relevant parameters to estimate the state and input of the unknown leader, ensuring observation is completed within a preset convergence time; designing an internal model dynamic compensator; determining the time-varying formation tracking error based on the state estimation result of the unknown leader; determining the formation tracking compensation term based on the multi-agent system parameters; determining the adaptive estimation update law based on the time-varying formation tracking error; and determining the final control law based on the input estimation result of the unknown leader, the internal model dynamic compensator, the time-varying formation tracking error, the formation tracking compensation term, and the adaptive estimation update law. This application, by designing a distributed preset-time observer and an internal model-based controller, can realize time-varying formation tracking in multi-agent systems with unknown disturbances and non-autonomous leaders.

The invention provides a water-air amphibious unmanned aerial vehicle compound control method based on motion state separation and multi-target distribution. The method comprises the steps of constructing a motion mathematical model and a disturbance model of an unmanned aerial vehicle, and designing an expansion observer based on state separation. Designing a nonlinear mapping rule to optimize the target inclination angles of different modes of the unmanned aerial vehicle; and designing a multi-objective cost function, solving an expected thrust and an expected inclination angle by using an improved genetic algorithm, and calculating an output thrust and a blade rotation angular velocity of each motor. The extended state observer based on state separation accurately estimates slowly changing lumped disturbance which is composed of persistent force / torque such as water flow and wind power and really needs to be compensated by a controller by augmenting an oscillatory motion state; through a multi-target cost function, the problem of single energy consumption minimization is controlled and distributed, so that the inclination angle tracking precision and the thrust change smoothness are achieved; and a high-quality global optimal solution is found at a higher probability by improving the genetic algorithm.

The application discloses an unmanned ship safety tracking control method for data forgery attack, and belongs to the technical field of intelligent control. A kinematics and dynamics model of an unmanned ship and a neural network approximation function are constructed; an observer based on an adaptive neural network is constructed, and then an observation error is obtained; a virtual kinematics control law is designed, a position tracking error model is constructed; a speed error dynamic model is constructed; a safety control compensation mechanism for compensating a control input is designed, and then a safety control compensation signal is obtained; a false control signal observer is designed to obtain a false control signal observation error; a dynamic tracking control law is constructed; the dynamic tracking control law is substituted into the speed error dynamic model, and then a speed vector error is obtained; a control input is generated according to the obtained speed vector error; and the control input is transmitted to an actuator of the unmanned ship through a communication network for execution. The application has stronger attack resistance, and the system has strong adaptability and control stability.

This disclosure provides an adaptive STSMC hierarchical control method for depth tracking of an underwater vehicle. The method includes: using an adaptive line-of-sight guidance algorithm to estimate the vehicle's angle of attack in real time and obtain an expected pitch angle; employing a nonlinear interference observer based on a sliding mode surface error to detect unknown interference; and applying an STSMC controller with adaptive saturation compensation to determine the expected control rudder angle from the sliding mode surface error, the expected pitch angle, and the observed interference. The adaptive saturation compensation corrects the rudder angle based on the saturation deviation, which is determined by the previously calculated expected control rudder angle and the actual output rudder angle at the previous moment. By introducing an adaptive saturation compensator in the dynamic control layer, the issue of rudder angle saturation is mitigated, thereby enhancing both control performance and stability.