16 results about "Constraint control" patented technology

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 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 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.

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.

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 discloses a kind of saturated optimization model-free adaptive control methods, systems, equipment and storage medium for MIMO system, obtain the input data and output data of MIMO system, establish the dynamic linearization data model containing pseudo-gradient matrix;Using projection algorithm with penalty mechanism and reset mechanism to update the pseudo-gradient matrix online;According to discrete quasi-sliding surface and backstepping method, combine the dynamic linearization data model, solve the unconstrained ideal control increment by reverse algebra;According to the amplitude constraint and rate constraint of MIMO system actuator, establish a linear inequality constraint set about control increment, use the unconstrained control increment as reference quantity, construct the quadratic objective function containing tracking error term and control increment weighting term;Using Hildreth algorithm to solve iteratively, obtain the actual control increment that satisfies constraint;According to actual control increment, update control input and apply to MIMO system.

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 relates to the technical field of robot control, in particular to a dual-arm robot based on offline reinforcement learning and combined with an online fine-tuning method, which comprises a left mechanical arm, a right mechanical arm and a control system, the control system integrates an offline strategy generation module, an online limited fine-tuning module, a safety constraint control module and a dual-arm cooperative modeling unit; the offline strategy generation module generates a safe initial control strategy based on historical data, the online limited fine-tuning module performs online correction of the initial strategy within a limited range, the safety constraint control module performs real-time constraint control of actions in the whole process, and a cooperative modeling mechanism of a dual-arm joint state and action space is constructed. Under the premise of ensuring the operation safety of the dual-arm robot, the training interaction cost of the control strategy is significantly reduced, the problem of insufficient generalization ability of the offline strategy is solved, the cooperative control precision of the dual arms and the environmental robustness are greatly improved, and the application is suitable for complex assembly, cooperative carrying and other dual-arm cooperative operation scenes.

The application discloses a double-handle external parameter calibration and fusion method and system based on detachable combination, belongs to the technical field of virtual reality and augmented reality, and is used for solving the technical problems that in the existing handle tracking technology, the external parameter is unknown or needs offline calibration, the rotation accuracy is easily limited and drift accumulation, and there are error abnormities in the handle combination mode. The method comprises the following steps: performing normalization cross-correlation calculation between a first angular velocity measurement sequence and a second angular velocity measurement sequence; if the handle is determined as the combination mode, performing constraint control based on the rotational motion between the first handle and the second handle and performing constraint control based on visual observation; performing residual error joint fusion processing on the rotational motion constraint result related to the two IMU gyroscope measurements; performing observation unified control processing on the visual observation constraint result based on shared feature points; and if the handle is determined as the separation mode, performing independent tracking control on the first handle and the second handle.

The application discloses a steam turbine start-stop phase speed constraint control method based on artificial intelligence, wherein the method comprises the following steps: generating a start-stop working condition vector according to real-time working condition parameters and historical start-stop segments; calculating a thermal stress limit, an overspeed upper limit and a critical dwell limit based on the start-stop working condition vector, and forming a twenty-four-dimensional speed segment safety boundary corresponding to a speed segment; inputting the start-stop working condition vector and the speed segment safety boundary into a diffusion type speed segment time decision network to generate a six-dimensional segment passing time draft meeting the safety boundary constraint; when the draft triggers the thermal stress limit, the overspeed upper limit or the critical dwell limit, generating a segment passing time final draft and a target speed time trajectory; in the segment speed constraint control architecture, generating the allowed speed interval and the acceleration target of each speed segment, calculating the valve opening degree instruction, and correcting the valve opening degree instruction to ensure that the trajectory constraint is met when the real-time speed triggers the allowed speed interval or the critical dwell limit.

This invention discloses a design generation system and method based on collaborative constraints of a multi-dimensional corpus for Nanjing brocade. It constructs a multi-dimensional hierarchical corpus for Nanjing brocade, and labels multimodal data related to Nanjing brocade design at semantic, syntactic, and pragmatic levels, establishing cross-level association rules. Based on this, semantic feature vectors, syntactic constraint parameters, and pragmatic constraint parameters are extracted to construct core element feature vectors and a multi-level collaborative constraint parameter set. These are then introduced into a design generation engine for multi-level constraint control. A pragmatic feasibility verification mechanism performs closed-loop correction on the generated results until cultural semantic consistency, structural and technological rules, and application conditions are met before outputting the design scheme. This invention achieves collaborative control of semantic expression, structural rules, and application feasibility in the Nanjing brocade design generation process, ensuring the accuracy of cultural transmission and improving design efficiency and the feasibility of results.

This application discloses a method, apparatus, equipment, medium, and product for dual-constraint control of water level and power, belonging to the field of hydropower station control technology. The method includes: at the beginning of a single control cycle, real-time acquisition of the hydropower station's operating status data and receiving data from the superior energy management system; updating the hydropower station's state model library and using the state model library to predict the future water level change trend in the prediction time domain; based on the updated state model library, solving the water level and power coordination control optimization problem under dual constraints within a single control cycle to obtain the optimal power sequence in the future prediction time domain; extracting the optimal power corresponding to the current control cycle from the optimal power sequence as a power adjustment command to adjust the output of the turbine generator unit; and repeating the above method within a sliding time window based on the feedback of the new real-time operating status data after entering the next control cycle to achieve closed-loop rolling predictive control.

This application relates to a dual-constraint control method, system, device, and medium for distribution network regulation. The method includes: constructing a distribution network regulation knowledge graph by integrating the process rules of the dispatching and control platform with the physical rules of the distribution automation system; constructing a regulation simulation environment integrating a physical simulation engine and a rule query interface based on the knowledge graph; training a deep reinforcement learning agent to obtain the trained deep reinforcement learning agent; and based on the trained deep reinforcement learning agent, parsing the target operation ticket into an initial action sequence, and simulating and deducing the initial action sequence in conjunction with the current real-time state of the power grid, outputting safety assessment results and optimization suggestions. This method, by constructing a knowledge graph and simulation environment, and training a deep reinforcement learning agent, achieves full-sequence simulation and intelligent evaluation of operation tickets, thereby improving the safety, compliance, and operational efficiency of distribution network remote control operations and effectively avoiding the risk of illegal operations.

This invention relates to a method for controlling random constraints based on simulation command-line parameters or files. The method includes: declaring at least one random constraint controlled by preset parameter variables in a verification environment implemented in SystemVerilog; independently compiling the verification environment to generate compilation results; starting the simulation based on the compilation results and passing preset-formatted random constraint control information to the simulation tool via the simulation command line, the control information specifying the target value of the preset parameter variables; automatically parsing the random constraint control information passed from the simulation command line during simulation execution; and determining the constraint activation mode based on the current value of the preset parameter variables when the verification environment performs randomization. This invention can effectively reduce the time required for modifying random constraints and recompiling during verification convergence, with the time-saving effect being even more significant in large-scale verification projects.