55 results about "Constraint control" patented technology

The invention belongs to the technical field of stage equipment boundary safety protection control, and particularly relates to a variable constraint control method for stage equipment based on risk perception and a dynamic safety domain. The characteristic that stage equipment is usually in a fixed application scene in the performance process is utilized, the inherent safety level and active protection capacity of a stage equipment system are greatly improved through tight combination of real-time collection and variable constraint, and therefore safer, more accurate and more smooth control is achieved. According to the method, a construction algorithm is embedded in software, a dynamic region division and segmentation threshold adjustment strategy is utilized, and a multi-stage braking redundancy cooperation mechanism is triggered, so that the anti-interference capability and fault tolerance performance of the control system are effectively enhanced, the implementation cost is low, a large amount of manpower and material debugging can be saved, and the system is suitable for large-scale popularization and application. And a high-precision and high-robustness safety control scheme is provided for large stage machinery such as a seat vehicle platform and a rotating stage.

The invention discloses an unmanned ship target tracking constraint control method based on an exponential time-varying performance function, and relates to the technical field of state tracking control, in particular to the technical field of performance constraint control, comprising the following steps: step (1), establishing an unmanned ship motion three-degree-of-freedom mathematical model; step (2): constructing an exponential time-varying function; (3) constructing an exponential time-varying performance function; (4) introducing a time-varying auxiliary function; (5) designing a transfer function; (6) designing a fixed time performance constraint heading controller based on an exponential time-varying performance function; (7) designing a fixed time performance constraint surging controller based on an exponential time-varying performance function; and (8) performing simulation verification. According to the method, mainly starting from the design of a novel time-varying performance function, the problem that the state error of the traditional performance function constraint control at the initial moment is limited by the performance boundary is solved, so that the transient performance and the steady-state performance of the state tracking error of the unmanned ship are remarkably improved; and the overall control performance of unmanned ship target tracking control is further improved.

A vehicle includes a vehicle engine, a steering control unit, an on-board sensor network and a navigational constraint control system. The vehicle engine generates a torque output of the vehicle. The steering control unit controls a steering angle of the vehicle. The on-board sensor network is programmed to detect external objects within a detection zone. The navigational constraint control system has a memory for storing a path index for the vehicle's navigation. The processor is programmed to determine a reference trajectory from the path index. The processor is further programmed to calculate navigational constraints for the determined reference trajectory to determine a nominal trajectory based on information detected by the on-board sensor network. The processor is programmed to control at least one of the vehicle engine and the steering control unit in accordance with the nominal trajectory.

This disclosure provides a method and system for selecting the site of pumped storage power stations based on spatial constraints and elastic buffers, relating to the field of data processing technology. The method includes: acquiring a set of spatial constraint elements corresponding to the pumped storage power station; determining the constraint control rules corresponding to each spatial constraint element in the set; applying range constraints to each associated spatial constraint element based on the constraint control rules; generating at least one elastic buffer corresponding to each spatial constraint element; determining engineering requirement indicators and geological assessment indicators; and filtering the elastic buffer based on the engineering requirement indicators and geological assessment indicators to obtain the target effective construction area. This solution enables differentiated management of different types of spatial constraint elements, thereby ensuring the safety of pumped storage power station construction, and allows for multi-dimensional filtering of elastic buffers to determine the target effective construction area, ensuring the accuracy and practicality of the target effective construction area.

The invention discloses a piezoelectric driving system constraint control method based on a predetermined time observer, and the method comprises the steps: designing a predetermined time interference observer in combination with a predetermined time performance function, and guaranteeing that an interference estimation error is converged to a bounded range within a predetermined time; a state conversion function is designed based on the obstacle Lyapunov function, so that the system output can also realize preset time output constraint under the condition that the initial state does not meet the constraint condition; a predetermined time adaptive controller is designed by using a neural network approximation technology, a dynamic surface control technology, a constraint control technology and a predetermined time interference observer technology, so that a closed-loop system realizes predetermined time stability. The problem that an existing disturbance observer cannot be used for preset time control is solved, and the assumption that initial conditions of constrained variables need to meet constraint conditions in constraint control is avoided.

The invention discloses a unified design method for a suboptimal controller of an aircraft system under multiple constraints, and the method comprises the steps: carrying out the modeling of an aircraft system and various constraint conditions in a control process; secondly, converting the aircraft system model into a form of an affine nonlinear system, and representing various constraints as state inequality constraints, input amplitude inequality constraints or input time delay constraints; then, respectively converting the state inequality constraint and the input amplitude inequality constraint into state equality constraints; meanwhile, a system containing input time delay is converted into a system without input time delay; then, establishing an unconstrained augmentation system comprising a no-input time-delay system and state equality constraints; and finally, designing a sub-optimal controller based on reinforcement learning for the unconstrained augmentation system by adopting an execution-evaluation network framework. By means of the multi-constraint control method, various constraints can be processed at the same time, and the multi-constraint control method is high in universality and can be used for diversified actual application scenes.

The present application relates to biped robot control technical field, especially relate to a kind of robust constraint tracking control method of biped robot based on parameter optimization.The present application uses improved inverted pendulum model, while making full use of the advantages of single mass model, still can reflect the important characteristics of biped robot, avoid a series of errors and interference problems due to model oversimplification.The key parameters of the improved inverted pendulum model are set to be variable in the present application, which is convenient for adjusting its dynamic characteristics.The present application designs a kind of robust constraint control method, considers the motion equation of the limited mechanical system of equality constraint and inequality constraint, and makes the control input satisfy Gauss principle and d'Alembert principle, so as to produce moderate control force in the real world to meet system performance.

The application discloses a mobile manipulator control method and device based on online learning and fuzzy neural dynamics, and relates to the technical field of mobile manipulator control. The method comprises the following steps: acquiring an actual pose of an end effector, a desired pose trajectory and joint speed; introducing an excitation signal formed after superimposing random noise, updating a current Jacobian matrix estimation value of the mobile manipulator; inputting each data into a fuzzy neural dynamic solver; the fuzzy neural dynamic solver is configured to take a quadratic form as an optimization objective, take a differential kinematics tracking equation as an equality constraint, and take a non-convex feasible region as an inequality constraint; and finally outputting a control signal of the joint speed obtained by solving the fuzzy neural dynamic solver to drive the mobile manipulator to move. The application solves the technical problems of low control precision of the mobile manipulator under the conditions of parameter uncertainty and non-convex constraints without an accurate prior model, and realizes high-precision model-free pose control.

The application relates to the field of automatic control of intelligent agricultural equipment, and particularly discloses a constraint control method for an intelligent mower based on fixed-time convergence. First, a kinematic model and a heading subsystem of a differential steering intelligent mower are established; a fractional time conversion function is constructed to complete time dimension conversion scheduling of the heading subsystem; a nonlinear mapping function is used to convert the constrained heading system into an unconstrained system; and finally, a nonlinear heading constraint controller based on the backstepping method is designed to realize fixed-time convergence. The application can guarantee that the heading angle converges to the expected value within a fixed time, and the constraint boundary is not exceeded throughout the whole process, thereby improving the response speed, control accuracy and operation safety of the heading control of the intelligent mower.

The application discloses a kind of transformer fault ride-through control method, system, equipment and medium, belong to the technical field of fault ride-through control, method includes: obtaining grid-connected voltage constructs observation model and solves stable phase;Multi-dimensional constraint model is constructed, locks amplitude when overcurrent and anchors phase, simultaneously triggers integral freezing mechanism.System includes state observation module, phase solving module, constraint model configuration module, instruction generation module, collaborative control module.The application constructs virtual magnetic flux observation model, uses integral filtering characteristic to filter out noise and analyzes high robustness synchronous phase;Combined with multi-dimensional constraint control model, lock current amplitude under current limiting condition and force anchor phase, simultaneously trigger integral freezing mechanism to block error accumulation.Thereby effectively solve the problem of transient synchronization instability, inhibit the control signal dithering, and eliminate the oscillation phenomenon in fault recovery period.

The invention discloses a performance constraint control method and system for multi-robot collaborative carrying of large workpieces. The method comprises the steps that firstly, a unit quaternion is adopted to establish a coupling dynamic model containing closed-chain constraint under a task reference coordinate system; secondly, designing a completely distributed finite time observer, and performing consistency estimation on a global reference trajectory only through neighborhood communication; secondly, designing a consistency indicator function based on the estimated value, gradually activating a performance constraint function only after an observation error is converged so as to apply transient and steady-state performance boundaries, and generating an expected motion state of each robot; and finally, designing a distributed robust adaptive controller to realize trajectory tracking. According to the method, singularity is avoided through quaternion modeling, controller design of a task reference coordinate system is achieved through rigid body transformation, dependence on a centroid coordinate system is avoided, the requirement for a priori track is eliminated through a distributed observer, constraint conflicts are avoided through a strategy of'feasibility first and then constraint ', and the robustness of the system is improved. And the safety, the precision and the robustness of collaborative carrying are effectively improved.

The application discloses a kind of active suspension nonlinear mapping constraint control methods based on fixed time, comprising the following steps: step 1: constructing nonlinear mapping function: by nonlinear mapping function, asymmetric time-varying constraint to system state variable is realized by coordinate conversion;The application is by constructing nonlinear mapping function to carry out coordinate conversion, and the constraint problem of original system state is converted into the bounded problem of new system state, while realizing asymmetric time-varying state constraint, avoid the limitation of feasibility condition to control design.On this basis, combined with fixed time stability theory to construct backstepping controller, so that closed-loop system realizes fixed time stability under time-varying asymmetric constraint condition, and its convergence time avoids dependence on initial state, so as to improve the rapidity, robustness and safety of active suspension system.

This invention relates to a management method, system, and electronic equipment for power grid systems, belonging to the technical field of power grid systems. The invention aggregates the electricity consumption data predicted by the load forecasting model of each edge node and introduces a constraint theory. Key constraint nodes are selected based on node importance and controllability. Non-constrained nodes synchronize data with the constraint nodes. Finally, based on the constraint optimization results and the electricity consumption data predicted by the load forecasting model of each edge node, the power supply in the target area is dynamically coordinated and optimized. Addressing the complexity of multi-node power grids, this invention introduces constraint control theory, selecting key constraint nodes based on node importance and controllability. Non-constrained nodes synchronize with the constraint nodes through a constraint matrix, significantly reducing the control dimension and communication burden. In practical applications, the online learning mechanism enables the controller to adapt to changes in grid topology and fluctuations in operating conditions in real time, achieving efficient frequency control.

The invention discloses a dual constraint control method, device and equipment of an unmanned aerial vehicle, a storage medium and a computer program product, and relates to the technical field of unmanned aerial vehicle control, and the method comprises the steps: building a model constraint optimization problem of model parameter estimation and a controller constraint optimization problem of controller parameter estimation based on an expected output signal of the unmanned aerial vehicle; constructing a first Lagrange function based on the model constraint optimization problem, and constructing a second Lagrange function based on the controller constraint optimization problem; performing dual conversion on the first Lagrange function to obtain a model parameter estimation value; performing dual conversion on the second Lagrange function to obtain a controller parameter estimation value; and calculating a target control quantity of the unmanned aerial vehicle based on the model parameter estimation value and the controller parameter estimation value, and controlling the unmanned aerial vehicle based on the target control quantity. The generated control quantity is determined through the Lagrange function and dual optimization, and the control performance of the unmanned aerial vehicle under the constraint condition is improved.

The invention relates to the technical field of cable welding, and discloses an in-cabinet cable self-adaptive welding device with an elastic restraint mechanism, the in-cabinet cable self-adaptive welding device comprises a supporting base, the top end of the supporting base is fixedly provided with a six-axis manipulator mechanism, and the top end of the six-axis manipulator mechanism is connected with an elastic restraint supporting mechanism and two restraint control mechanisms; by integrating the elastic constraint supporting mechanism and the constraint control mechanism, motion interference is effectively avoided, it is ensured that efficient and accurate welding operation is carried out in a compact electrical cabinet, and the risks of equipment collision shutdown and welding track deviation are reduced; and the elastic constraint supporting mechanism is combined with the six-axis manipulator mechanism, so that the dynamic adjustment and accurate fixation of the cable angle are realized. The first driving motor drives the positioning gear to rotate on the positioning gear ring, the elastic restraining base can flexibly rotate along the supporting ring, the cable is accurately adjusted to the needed angle, and the cable butt joint precision and consistency are improved.

The application discloses a robot contact force constraint control method based on a control barrier function, and an affine nonlinear system model containing contact force is constructed based on a kinematics model, a dynamics model and a contact force model of the robot, which has better dynamic performance compared with a single contact force model, the control barrier function is applied to robot contact force safety constraint control, compared with existing position safety constraint control methods, the application of the control barrier function in the robot field is widened, the control barrier function can be combined with various existing force-position control methods, has good contact force constraint effect, high flexibility, good real-time performance, strong robustness, simple application, and effectively improves the problem that traditional force-position control is difficult to constrain contact force.

This application relates to a dynamic safety domain prediction and adaptive constraint control method for human-robot collaboration in live-line work, applicable to the field of automatic control technology. The method includes: acquiring robot operating state data, human state data, and a spatial model of the live conductor; performing coordinate transformation and time alignment on the operating state data, state data, and spatial model to obtain a target data frame; determining the human's intent confidence level, predicting the human's actions, and obtaining the predicted position and prediction uncertainty information; constructing the human's future occupancy area; generating a dynamic safety domain and determining the target minimum safety distance; constructing control constraints based on the dynamic safety domain and the target minimum safety distance; modifying the acquired nominal control commands according to the control constraints to obtain target control commands, and controlling the robot's operation according to the target control commands. This method can improve the safety of robot operation control.

The invention provides a time constraint control method for multiple uncertainties of a p-normative system, and relates to modeling of the nonlinear system and signal bounded judgment lemma design with more loose parameter constraint. According to the method, the requirements of system stability control on high precision, high speed, low energy consumption and the like are comprehensively analyzed, and a controller algorithm is designed based on a Lyapunov theory system and by fusing a sign function, a Nussbaum function and a self-adaptive backstepping technology. The method comprises the following steps: firstly, establishing a p normative nonlinear system model with multiple uncertainties; introducing coordinate transformation, and designing a corresponding adaptive law and a controller algorithm by means of a backstepping technology, a sign function and a Nussbaum function; secondly, establishing an event triggering mechanism and a controller which meet the requirements of the p standard type nonlinear system; and finally, selecting a proper Lyapunov function, and proving the system stability by using a signal bounded judgment lemma and a finite time stability lemma. The method can be used for a ship steering system.

The invention relates to a steering under-constrained multi-axle vehicle sensitivity analysis and transverse dynamics constraint control method, which comprises the following steps of: calculating an ideal yaw velocity and a side slip angle when a multi-axle vehicle tracks an expected path according to expected path information, vehicle real-time position information and vehicle state information; establishing a multi-axle vehicle transverse dynamic model and a state tracking-oriented decoupling control model; calculating the sensitivity index of each rotation angle input to the yaw velocity and the side slip angle of the vehicle under different working conditions, analyzing the influence degree and the coupling relation of each rotation angle to the transverse dynamic performance of the vehicle, and obtaining a key control rotation angle; constructing an integral sliding mode state constraint controller based on the obstacle Lyapunov function; and according to a multi-axle vehicle turning angle signal output by the controller, an instruction is issued to the actuator, so that the turning angle of each axle is adjusted to a required angle, the motion state of the vehicle is changed, and tracking control is realized. The method can ensure safe and stable driving of the vehicle while realizing accurate tracking control of the multi-axle vehicle.

The invention relates to the field of unmanned aerial vehicle control technology, model prediction control and perception-control fusion, and discloses a four-rotor suspension load exponential stability hybrid perception constraint MPC control method comprising the following steps: constructing a hybrid dynamic model of a four-rotor-cable-load system, and uniformly considering dynamic coupling and multi-constraint conditions; designing an exponentially stable hybrid perception constraint MPC framework, constructing an optimal control problem containing hybrid dynamics constraints, and performing real-time iterative solution to generate a four-rotor reference trajectory; constructing a hybrid perception constraint system; designing a hybrid mode robust state estimation system; an MPC trajectory tracking execution framework adaptive to a mixed mode is developed, the method is adaptive to complex scenes such as dynamic infeasible trajectory tracking and man-machine interaction control, and tracking precision and sensing safety are both considered in high-speed and high-acceleration motion; and the application range and engineering application capability of the four-rotor suspension load system in actual tasks such as disaster response and infrastructure maintenance are expanded.

This invention discloses an inequality constraint control method for friction stir welding robots operating on complex curved surfaces. The method includes: acquiring the angular displacement of the robot's drive motor and the input torque of the load driven by the drive motor; and controlling the drive motor based on the angular displacement and input torque using a pre-established inequality constraint control model. This method, utilizing the pre-established inequality constraint control model, controls the drive motor based on its angular displacement and input torque. It enables the control focus to be on trajectory tracking when the angular displacement moves away from the boundary, guiding the angular displacement away from the boundary and towards the desired trajectory. This method exhibits high stability and robustness.

The application belongs to the technical field of robot control, and particularly relates to a mechanical arm soft and hard constraint control method based on compatible conflict signals, which comprises the following steps: step 1: joint information collection of the mechanical arm; step 2: dynamics modeling and soft and hard constraint modeling of the mechanical arm; step 3: generating compatible conflict signals according to the soft and hard constraint boundaries, and dynamically identifying the execution relationship between the constraints; step 4: setting a relaxation correction margin and corresponding polishing correction parameters based on the compatible conflict signals; step 5: giving a planning output feasible region of the mechanical arm, and designing a high gain controller by using the compatible conflict signals and barrier functions; and step 6: constructing a quadratic Lyapunov function, and analyzing the stability of the closed loop system by using the Lyapunov stability theory. The application realizes low complexity and high robustness of multi-constraint control, and provides more reliable control guarantee for the mechanical arm system in complex industrial applications.

A kind of nuclear power unit power regulation control scheme automatic generation method and system based on deep reinforcement learning, by constructing the hybrid surrogate model of fusion CNN, GRU and self-attention mechanism, the dynamic response of reactor is represented, PPO-Lagrangian training strategy network is used, the accurate constraint control of axial power deviation in the regulation process of conventional AO method is realized;With current AO and target AO as input, the preset power and control rod position full-process operation sequence that meets the safety constraint is automatically generated;On the basis of existing operation, the remaining sequence is continued to be written, and the constraint violation caused by existing operation is repaired, the strategy network based on MLP introduces normalized space sampling to maintain training exploratory, hard constraint is used in test stage to ensure operation safety;Lagrangian multiplier self-adaptingly balances control performance and constraint satisfaction.The AO deviation can be controlled within the target value ±1.0%, and the generation time is less than 1 second after training is completed, which can provide real-time decision support for operators.

The invention discloses a multi-target constraint control method based on thrust reduction of a wind generating set, and the method comprises the steps: firstly obtaining a measurement signal of the wind generating set as input, and taking a thrust target value calculated and determined in an overall design stage as a constraint condition; in the starting process of the wind generating set, a static generator power-pitch angle curve meeting the target thrust value constraint condition is calculated; the wind generating set obtains a generator power-pitch angle curve according to the current generator power in the normal power generation process, then a pitch angle is obtained through calculation, and the pitch angle is defined as the dynamic minimum pitch angle; and finally, the dynamic minimum pitch angle is transmitted to a variable pitch control link of the wind generating set, and a variable pitch demand instruction is issued after amplitude limiting operation. It can be guaranteed that the wind generating set operates in the optimal power generation state to the maximum extent, the power generation capacity of the wind generating set is effectively improved, meanwhile, control parameters are adjusted in real time according to changes of external wind resources, and adaptability in different environments is improved.

The invention discloses a field rheological actuating system, a texture, an intelligent mechanical arm system and a related use method, and relates to the technical field of intelligent mechanical electronics and precise motion control. Differentiated asymmetric geometric topology structure sections are arranged on the surfaces of relative movement components of the field rheological actuating system, space differentiated field intensity distribution and local saturation of an excitation field are induced, field intensity distribution is optimized through geometric topology structures, solidification of rheological media in a topology locking area is achieved, and a mechanical interlocking effect is established. Therefore, the structural static holding torque exceeding the yield limit of the medium is output without continuous power supply of the motor. A joint of the mechanical arm system is composed of the actuating system, and a local real-time solution and geometric constraint control strategy is adopted to achieve safety constraint of a far-end motion center. The problems that a traditional rheological joint is insufficient in static retentivity, a joint motor is overheated due to long-term stalling, and the remote operation safety is insufficient are effectively solved.

The application discloses an arbitrary differentiable geometric constraint virtual clamp, a dynamic control method and a system, wherein the arbitrary differentiable geometric constraint virtual clamp is characterized in that: in the case that the geometric form of the virtual clamp can be given in an analytical form and is at least second-order differentiable, the constrained geometric form only depends on the spatial position; a scalar constraint equation and a constraint control variable of the virtual clamp are defined, a joint Jacobian matrix of multiple constraints is constructed, a reference constraint control input is calculated by using PD control based on a constraint control expected value and a constraint control error value; the arbitrary differentiable geometric constraint virtual clamp dynamic control method is characterized in that: a null space control input of a mechanical arm is calculated based on a dynamic model, a reference constraint control input is calculated by using the virtual clamp, and an estimated torque is projected to a task space corresponding to a virtual clamp constraint and then compensated by using a disturbance observer. The virtual clamp provided by the application solves the problems of poor universality and heavy calculation burden, simplifies calculation and improves universality.

The application relates to the field of automatic control of intelligent agricultural equipment, and particularly discloses a constraint control method for an intelligent mower based on fixed-time convergence. First, a kinematic model and a heading subsystem of a differential steering intelligent mower are established; a fractional time conversion function is constructed to complete time dimension conversion scheduling of the heading subsystem; a nonlinear mapping function is used to convert the constrained heading system into an unconstrained system; and finally, a nonlinear heading constraint controller based on the backstepping method is designed to realize fixed-time convergence. The application can guarantee that the heading angle converges to the expected value within a fixed time, and the constraint boundary is not exceeded throughout the whole process, thereby improving the response speed, control accuracy and operation safety of the heading control of the intelligent mower.

The invention discloses an inequality constraint control method of a friction stir welding robot for a complex curved surface. The method comprises the steps that the angular displacement of a driving motor of the friction stir welding robot and the input torque of a load driven by the driving motor are collected; and controlling the driving motor according to the angular displacement and the input torque by using a pre-established inequality constraint control model. According to the method, the drive motor is controlled according to the angular displacement and the input torque of the drive motor by using the pre-established inequality constraint control model, when the angular displacement is far away from the boundary, the control focus is put on trajectory tracking, so that the angular displacement is far away from the boundary and moves towards an expected trajectory, and the method has the advantages of high stability and strong robustness.