230 results about "Equilibrium control" patented technology

The invention discloses a temperature correction method and system for a hot press, and particularly relates to the technical field of hot press temperature control, and the method comprises the steps: obtaining and preprocessing multi-dimensional operation data, including a temperature time sequence, pressure setting and material attributes; constructing a coupling model based on the multilayer neural network, and predicting temperature distribution of different process stages; performing sensor drift compensation, analyzing temperature deviation characteristics, judging whether sensor drift or material thermal diffusion abnormity exists or not, and generating a local distortion mark; determining a compensation mode according to the distortion mark, and starting a local compensation mode or a global balance control mode if the distortion is recognized as over-limit distortion; and comparing with the output of the coupling model, verifying the temperature correction effect, and if the deviation is reduced and the distortion mark is converged, outputting a stable temperature correction result. The problems of temperature distortion and sensor drift are effectively solved, and the long-term precision and stability of the hot press under complex working conditions are improved.

The invention discloses an intelligent cooperative switching control system and method for multi-path valve runners, and the method comprises the steps: collecting all-condition operation data of a multi-path valve system, extracting valve switching characteristic parameters, and building a runner mapping relation between paths; a cascade action chain containing time sequence dependence is constructed based on the mapping relation and the switching characteristics, and the action sequence and the trigger condition of each drift diameter are determined; by analyzing the pressure distribution and the flow velocity change in the cascade action chain, predicting the water hammer strength and designing a reverse pressure wave parameter, and generating a water hammer counteracting control instruction; high-low pressure area distribution in the flow field is identified, a flow field complementary cooperation scheme is constructed, and a pressure balance control strategy is generated; analyzing a pressure wave propagation path to determine a superposition elimination point, extracting pressure pulse resonance characteristics and generating time sequence control parameters; and the sequential control parameters are matched with the cascade action chain, synchronous control nodes are determined through delay compensation, and a time-sharing control sequence is generated to achieve intelligent cooperative switching of the multi-drift-diameter valve flow channels.

The invention discloses a quadruped robot motion control method and system based on reinforcement learning, and the method can simulate and analyze the motion behavior of a quadruped robot in a virtual environment through building a simulation model of the quadruped robot, remarkably reduces the research and development cost, remarkably shortens the research and development period, converts a balance control problem into a Markov decision process, defines a state, an action and a reward function, and improves the reliability of the quadruped robot. A more intelligent and adaptive balance strategy can be realized, a deterministic strategy gradient algorithm and a simulation model are adopted for interactive training, an efficient balance control strategy can be obtained, robot behaviors are adjusted in real time to keep balance, a walking task is decomposed into two sub-tasks of foothold selection and gait generation by utilizing a hierarchical control idea, and the walking efficiency is improved. Through reinforcement learning, walking flexibility and stability of the robot on irregular terrains are improved, the irregular terrains are built on a simulation platform for experimental verification, robot performance can be safely and repeatedly evaluated, and a strategy is further optimized.

The invention discloses an intelligent heat supply two-network balance control method and system based on fuzzy reinforcement learning, and the method comprises the steps: obtaining real-time operation parameters which comprise the return water temperature, the heat load and the environment temperature; based on the real-time operation parameters, preliminarily generating a preliminary adjusting quantity of the opening degree of the valve; operation data are analyzed in real time, fuzzy rule parameters are adjusted according to feedback of the reinforcement learning module, and the fuzzy rule parameters comprise priority weights and membership functions of return water temperature deviation; and according to the preliminary adjustment effect, a deep learning algorithm is utilized to construct a state-action space equation, an energy consumption design reward function is considered, the priority weight is further optimized and fed back to a dynamic optimization module of a fuzzy rule, and secondary adjustment of the valve opening degree is output to an execution mechanism. The problems that a traditional fuzzy control method cannot adapt to complex working condition changes in the operation of the heat supply two-network, the adjusting strategy lags behind, the adjusting effect is not accurate enough, and the adjusting efficiency and energy consumption are affected are solved.

A balance control method for a wheel-legged robot is provided. The robot includes a moving wheel, n links, and n rotating joints, the moving wheel being connected to a first link through a first rotating joint of the n rotating joints, and the n links being connected in series through n−1 rotating joints other than the first rotating joint, n being a positive integer greater than 1. The method includes: acquiring a state quantity of the wheel-legged robot at a first moment; determining dynamics model parameters according to a dynamics equation of the wheel-legged robot and the state quantity at the first moment; establishing a sliding surface according to the state quantity at the first moment; calculating rotation torques of the n rotating joints according to the sliding surface and the dynamics model parameters; and controlling the rotating joints according to the rotation torques of the n rotating joints.

The invention discloses an intelligent balance control method and system for the temperature of a die-casting die, and relates to the technical field of temperature control, and the method comprises the steps: collecting the temperature monitoring time sequence information of the die-casting die; performing anomaly analysis on the die-casting die temperature monitoring time sequence information based on the die-casting die baseline temperature time sequence information, and when a die-casting die temperature anomaly coefficient is greater than or equal to a temperature anomaly coefficient threshold, optimizing a medium temperature attribute and a medium flow attribute to generate a first medium optimization temperature and a first medium optimization flow, and the medium temperature control assembly and the medium flow control assembly are controlled. The technical problem that in the prior art, the temperature and flow of an output medium of a traditional water temperature machine are fixed values, temperature changes in actual production cannot be met, and consequently the die temperature control precision is low is solved, flexible control over the die-casting die temperature through the interactive water temperature machine is achieved, and the die-casting efficiency is improved. And the die temperature control precision of the die-casting die is improved.

The invention provides an unmanned aerial vehicle flight attitude self-adaptive imbalance control method, device and equipment, and aims to accurately obtain an ideal control track and recognize a beneficial imbalance mode to generate a controllable imbalance strategy library by constructing a reverse track analysis and controllable imbalance strategy generation mechanism. A dynamic balance reference establishment and track reconstruction technology is adopted to construct an unbalance-recovery control track, and dynamic response characteristics are accurately obtained; an unbalance recovery space-time manifold construction and topology analysis technology is introduced, a core unbalance control feature set is extracted through space-time folding transformation, and unbalance control key parameters are determined; establishing an unbalance-recovery mapping rule and self-adaptive parameter fusion mechanism, balancing the control effect and the safety requirement, and generating a disturbance control parameter and a self-adaptive mapping parameter; a real-time control output regulation mechanism is constructed to generate a flight control signal in combination with reverse unbalance combined control and a multi-axis cooperative control mechanism; finally, a self-adaptive unbalance control system is formed, and precise unbalance control over the attitude of the unmanned aerial vehicle is achieved.

The invention discloses a balance control scheduling method and system based on distributed new energy, and the method comprises the steps: obtaining power grid parameters, and constructing a time-space characteristic model of multi-type adjustable resources and a distributed scheduling frame based on the obtained parameters; based on the space-time characteristic model and the distributed scheduling framework, establishing a distributed new energy participation power grid adjustable and controllable resource group internal cooperation strategy; establishing a distributed new energy participation power grid dispatching collaborative interaction and balance optimization control strategy according to the collaborative strategy; and realizing active / reactive coupling balance collaborative optimization of the high-permeability distributed new energy access power grid based on a collaborative strategy and an optimization control strategy. According to the invention, the utilization rate of new energy can be improved, cooperative work of multiple types of adjustable and controllable resources is realized, the flexibility and stability of a power grid are improved, dynamic adjustment of a power system is realized, and optimal matching of power supply and demand at different time and space scales is ensured.

The invention provides a gate valve pressure balance control method and device, electronic equipment and a storage medium, and relates to the technical field of gate valve pressure control. The method comprises the steps of monitoring a gate valve control signal and a pressure difference between two sides of a gate valve; calculating a gate valve control signal change rate according to the gate valve control signal, and setting a control signal amplitude threshold value and a change rate threshold value; according to the gate valve control signal change rate, the control signal amplitude threshold value and the change rate threshold value, the gate valve switching action is predicted; based on the predicted gate valve switching action, according to the pressure difference of the two sides of the gate valve, the number of balance channels needing to be opened when the pressure balance is achieved on the two sides of the gate valve is judged; the controller is controlled in advance to open the corresponding number of balance channels to balance the pressure on the two sides of the gate valve. According to the gate valve pressure balance control method, the problem that in the prior art, the response speed is insufficient in the aspect of gate valve pressure balance control is solved, and the effects of remarkably improving the pressure balance response speed and effectively restraining hydraulic impact and vibration are achieved.

A balance control method and apparatus (1600) for a wheel-legged robot (200), a device, and a storage medium. The method is executed by a computer device (101). An n-order inverted pendulum model as which the wheel-legged robot (200) is equivalently represented comprises: wheels (1016), n connecting rods and n rotating joints; first connecting rods (1026, 1110) are equivalently derived from at least two leg mechanisms (1022, 1024) of the wheel-legged robot (200), and the wheels (1016) are equivalently derived from moving wheels (1012, 1014) respectively connected to the at least two leg mechanisms (1022, 1024). The method comprises: step 1310, acquiring an actual state quantity of the wheel-legged robot (200) at a first moment; step 1320, calculating an equivalent state quantity at the first moment on the basis of the actual state quantity at the first moment; step 1330, establishing a sliding mode surface on the basis of the equivalent state quantity at the first moment; step 1340, determining a force and torque instruction of the whole body joint on the basis of a dynamic equation of the sliding mode surface and the equivalent state quantity at the first moment; and step 1350, at a second moment, respectively controlling the n rotating joints on the basis of the force and torque instruction. The method is adapted to a wheel-legged robot (200) in movement, facilitating improvement of the robustness of balance control.

The invention relates to the technical field of grid-connected inverter control, and discloses a grid-connected inverter model predictive control method based on a neutral-point potential fluctuation control factor, in the process of controlling a grid-connected inverter by using model predictive control, firstly, an SVPWM method and the model predictive control method are combined, the design of an objective function is simplified, and the model predictive control factor is optimized; the optimal switch sequence can be selected only by calculating the midpoint potential deviation; secondly, neutral-point potential balance control is realized in spatial modulation, a large sector is further divided into a plurality of small sectors, the position of the small sector where a reference voltage vector is located is determined, a switch sequence is selected from the determined small sectors for traversal, the traversal frequency is reduced, and the calculation efficiency is improved; and finally, designing a midpoint potential control factor, and greatly reducing the content of high-amplitude common-mode voltage on the premise of ensuring the balance of the midpoint potential. Moreover, the overall control structure is clear and easy to implement, and the dynamic performance and the steady-state tracking performance of the controller are both improved.

The invention relates to the technical field of robots, in particular to a robot stability and balance control method based on an embedded depth fusion algorithm, and the method comprises the following steps: S1, sensor data collection: configuring a plurality of sensors to collect the motion state and environment information of a robot in real time; s2, dynamic scene understanding: performing real-time analysis on the acquired sensor data, and identifying potential obstacles and changes in the environment; s3, cooperative control based on behavior prediction: predicting future behaviors of a plurality of robots, and dynamically adjusting a cooperative strategy; and S4, real-time feedback adjustment: comparing the current state of the robot with a preset stable state through a multi-level feedback mechanism, and intelligently adjusting a control strategy based on real-time environment change and task requirements. According to the invention, the adaptability and task execution efficiency of the system are improved, and more intelligent and flexible cooperative work can be realized in a complex scene.

The invention discloses a non-coaxial two-wheeled unmanned platform trajectory tracking hierarchical control method and system, and relates to the technical field of intelligent robots, and the method comprises the steps: obtaining the real-time pose information and coordinate information of an unmanned motorcycle in the driving process; inputting the pose data and the coordinate information into a vehicle-mounted calculation unit, and correcting the driving deviation of the non-coaxial double-wheel system on the premise of ensuring the stability of the vehicle based on a double-closed-loop trajectory tracking control strategy so as to track an expected trajectory; an off-line expected trajectory, a trajectory tracking controller, a self-balancing controller, an unmanned motorcycle system kinematics model and an unmanned motorcycle system dynamics model are preset in the vehicle-mounted calculation unit; the double-closed-loop trajectory tracking control strategy comprises an outer-loop pose planning layer and an inner-loop balance control layer. According to the invention, a double-closed-loop control structure is adopted, so that the trajectory tracking precision and stability of the unmanned motorcycle can be effectively improved.

The invention discloses a surface-mounted permanent magnet synchronous motor sensorless high-performance sliding-mode control method, and the method comprises the steps: designing an improved self-adaptive terminal sliding-mode switching function for the problem of high-frequency buffeting of a sliding-mode observer caused by the fixed gain design of the switching function; and dynamically adjusting the gain of the switching function according to the sum of the stator current error and the integral thereof under the two-phase static coordinate system so as to suppress high-frequency buffeting and improve the estimation precision. In order to further improve the performance of the position sensorless control system, a reaching law in a sliding mode controller is optimized, a novel composite gain self-adaptive sliding mode reaching law is designed, the reaching law combines a self-adaptive gain term, a nonlinear exponential term and a linear term, the system state is accelerated to approach when being far away from a sliding mode surface, buffeting is reduced when the system state approaches, and the control precision of the position sensorless control system is improved. Therefore, the dynamic response speed and buffeting suppression capability of the control system are balanced.

The invention relates to the technical field of robot control, and provides a robot body self-balancing control method applied to a quadruped robot, the robot body self-balancing control method comprises the following steps: S1, detecting a slope angle and attitude offset data of the quadruped robot in real time, the attitude offset data comprising roll angle offset and pitch angle offset; s2, transmitting the slope angle and attitude offset data to a main control system; s3, the main control system executes partition compensation control according to the attitude offset data: when roll angle offset exists, a left and right leg height compensation instruction is generated, and the robot is controlled to stretch out and draw back a left leg and a right leg; when the pitch angle deviation exists, a front and rear leg height compensation instruction is generated, and the robot is controlled to stretch out and draw back a front side leg and a rear side leg; and S4, performing partition compensation control through iteration to enable the fuselage to return to the horizontal position again and maintain the balance state.

The invention discloses a double-foot wheel-legged robot pose control method and device based on hierarchical cooperative control, a medium and a product, and relates to the field of robot control, and the method comprises the steps that a hierarchical cooperative control framework is constructed; the layered cooperative control framework comprises a balance controller and a whole body attitude controller; the balance controller determines a reference wheel joint driving torque based on a simplified inverted pendulum dynamic model according to the pose information of the upper mass center of the biped wheel-leg robot; the whole-body attitude controller performs optimization control on all joints of the biped wheel-leg robot by adopting an incremental model prediction control algorithm combined with a reference wheel joint driving moment based on a whole-body dynamic model; state information of the biped wheel-legged robot is obtained; according to the state information, a driving torque instruction of each joint is obtained based on a hierarchical cooperative control framework; and driving the double-foot wheel-leg robot to move according to the driving torque instruction of each joint. The precision, robustness and real-time performance of robot motion control can be improved.

The invention relates to the field of wind power generation, in particular to a performance degradation prediction method based on an independent variable pitch system of a wind turbine, which comprises the following steps of: 1, establishing a performance degradation model by using a Wiener process by taking a pitch angle control error as a core degradation characterization quantity, and analyzing a degradation rule of key components of the variable pitch system in real time; 2, defining a state vector containing a control error and a change speed thereof, introducing deterministic drift and random fluctuation brought by degradation, and constructing a state-space equation; 3, designing a target function, and dynamically adjusting a weight coefficient according to a degradation state; and 4, implementing model prediction control, adjusting a control strategy in real time according to typical working conditions, balancing the control precision and prolonging the service life of parts. By comprehensively analyzing the complex relationship between the external load and the degradation of the variable pitch system, a more accurate performance degradation model is established by using the Wiener process, and the influence of the external load on the degradation law of key components is fully considered.

The invention provides a compensation balance system and method of an electrodynamic transducer, and aims to solve the following problems in the prior art: a traditional electrodynamic sound source transducer needs to realize large-volume displacement in a low-frequency application scene, but the flexibility of an elastic suspension support of the traditional electrodynamic sound source transducer is insufficient to bear hydrostatic pressure; meanwhile, traditional passive and active compensation modes have challenges in the aspects of delay and stability. In order to solve the problems, the compensation balance system and method of the electrodynamic transducer mainly comprise an underwater acoustic transducer, a low-pressure middle cabin and a high-pressure gas cylinder, and a system self-checking function, a transducer piston position balance control function and a transducer fuzzy self-adaptive control function are integrated. The defects in the prior art are effectively overcome, and balance between the inner cavity of the transducer and the external hydrostatic pressure can be rapidly achieved. In addition, the control process is further simplified by determining the target control quantity, and the overall performance of the system is improved.

The invention discloses an air cushion belt dynamic balance control system and a management and control method, and belongs to the field of air cushion belt conveyors. Original signals of a sensor are obtained, a Fluent noise filtering algorithm is used for eliminating airflow interference, synchronous tension and air pressure data are aligned through timestamps, a reliability model is used for filling temperature field missing values, and standardized data streams are formed; based on the standardized data flow, analyzing an air pressure gradient by means of a fluid mechanics equation, extracting abnormal vibration modal characteristics of the carrier roller, calculating a fluctuation coefficient in combination with tension simulation, and obtaining a multi-dimensional parameter set containing dynamic distribution of a pressure field and a belt deviation angle; inputting the multi-dimensional parameter set into the digital twin, updating the fatigue damage parameters of the belt through Fluent simulation driving, rendering the visualization result of the flow field of the air chamber in real time, and outputting a simulation result containing the dynamic cloud picture of the pressure field of the air chamber and the fatigue damage distribution of the belt; and calculating the pressure balance degree of the air chamber according to a simulation result.

The invention discloses an automatic shipment balance control method, which belongs to the technical field of automatic shipment control, and comprises the following steps: scanning a cabin of a berthing empty ship, establishing a cabin three-dimensional model, constructing a wharf coordinate system and a ship coordinate system, and obtaining ship type data; planning a shipping strategy according to the ship type data, setting shipping turns and blanking point coordinates and target material height of each turn, and determining safe operation parameters of the chute tube; according to the coordinates of the blanking point of the current turn and the safe operation parameters of the chute tube, the outlet of the chute tube is controlled to be aligned with the coordinates of the blanking point of the current turn based on the wharf coordinate system by adjusting the motion parameters of the ship loader, and blanking is conducted when it is monitored that the material height of the current turn reaches the target material height; controlling the outlet of the chute tube to transfer to the blanking point coordinate of the next round; refreshing the cabin three-dimensional model in the loading process, obtaining the posture of the ship body, and updating the coordinates of the blanking point; and stopping the shipping operation until the shipping volume reaches the standard. The method can improve the automatic shipment balance control precision.

The invention discloses a six-shaft simple electric control speed change clutch sheet type electric driving system which comprises a power input mechanism, a speed change assembly and a two-shaft power output mechanism, and a power input shaft, a speed reduction shaft assembly, a reverse gear shaft mechanism and the two-shaft power output mechanism of the speed change assembly are arranged on the periphery of a main shaft in the circumferential direction. And the structure is simple and reliable, the expansibility is excellent, and various functional modules such as human-controlled reversing, inertial reversing and active upshift and downshift according to real-time power can be flexibly expanded according to actual requirements. The motor can always and efficiently keep working in the current high-efficiency area according to the change of the driving intention, a multi-parameter control strategy with the consciousness and intention of people as priority is achieved, and harmony and unification of people, vehicles, roads and running resistance / running loads are achieved. The important scientific and engineering technology common key problem of traction / driving force-running resistance / load efficient and accurate balance control is solved.

The embodiments disclose a financial transaction platform comprising a Stability Verification Engine coupled to a Transaction Input and configured to calculate stability functions using a Lyapunov Stability Engine to evaluate whether a proposed transaction converges toward equilibrium within a Stability Valley defined by threshold values in a Stability Function Database, a Deterministic Consensus Protocol coupled to the Stability Verification Engine and configured to process validated transactions through pre-commit verification, mathematical proof generation, and finality attestation to ensure irreversible acceptance, a Cascade Prevention System coupled to the Deterministic Consensus Protocol and configured to apply progressive intervention levels including enhanced verification, fee adjustment, transaction size limits, processing delays, and emergency stabilization when abnormal conditions are detected, and a Transaction Output coupled to the Cascade Prevention System and configured to forward transactions confirmed as stable and finalized to downstream predictive management and interface node systems.

The invention discloses an electric heat comprehensive energy balance control method and system based on a master-slave game, and belongs to the technical field of comprehensive energy management, and the method comprises the steps: taking the benefit maximization of a comprehensive energy operator as a first objective function, constructing an upper layer model, and generating an optimal energy selling price, and decision variables comprise an electricity selling price and a heat selling price; building a lower-layer model by taking user income maximization as a second objective function, and determining an optimal output plan and a load adjustment plan in the lower-layer model through an optimal energy pricing given by the upper-layer model; and taking a comprehensive energy operator corresponding to the upper-layer model as a leader, taking a load aggregator corresponding to the lower-layer model as a follower, and achieving Stackelberg equilibrium through a master-slave game, so that electric heating comprehensive energy is subjected to equilibrium control. According to the method, better global economic performance can be obtained, and the balance between the electricity price and the customer satisfaction is considered at the same time.

The invention relates to a balance control algorithm for gravity center trajectory planning and real-time tracking of a humanoid robot, in particular to the technical field of robot control, and realizes dynamic balance control through a closed-loop process of state sensing, online gravity center trajectory re-planning, hierarchical control law calculation and joint torque output and execution. A layered dynamic modeling and control framework is constructed, a variable-height inverted pendulum model is combined with model prediction control, and a gravity center and zero moment point track feasible in dynamics is generated online; virtual restoring force is generated through a gravity center impedance controller, a task priority inverse dynamics solver is used, multi-task execution is coordinated on the premise that balance tasks are guaranteed to be absolutely preferential through a null-space projection technology, theoretical torque is converted into current instructions to drive joints to move, and through efficient collaboration and real-time updating of dynamic models of all levels, the balance tasks are optimized. According to the invention, deep collaboration of various technical features is realized, and the problems of poor adaptability, slow response and poor balance capability of a traditional method in a dynamic environment are effectively solved.

The invention relates to the technical field of robot attitude balance control, and provides a robot attitude balance control method and system. Before the feet of the robot make contact with the supporting face or at the initial stage of contact, preset micro-force excitation is actively applied to the supporting face for detection, and mechanical response information and foot displacement information between the feet and the supporting face are collected in real time; based on the information, the system can estimate the local physical characteristics of the supporting surface in real time, and dynamically control and adjust the balance control strategy of the robot according to the estimated local physical characteristics. Through active detection and foresight adjustment, the characteristic change of the supporting surface can be identified and adapted before or at the initial stage of instability, so that the control conflict and vicious circle possibly brought by passive compensation are avoided.

The invention provides a biped robot standing balance control method based on MPC, and relates to the technical field of robots. The method comprises the following steps: S1, acquiring an external reference signal in a future T time interval; s2, acquiring a current robot state through state estimation; s3, constructing a robot centroid dynamics prediction model based on a single rigid body model, setting a grounding sliding constraint and a sole overturning constraint, and converting a problem into a QP problem for solving; s4, solving an optimal input sequence according to an external reference signal and a robot state; s5, retaining the first-step supporting force and the moment of force of the optimal sequence, and abandoning the predicted values of the remaining steps; s6, calculating a force jacobian matrix of the robot; and S7, the supporting force and the torque are mapped to the joints and issued to all motors. The ground reaction force during standing is directly calculated through the MPC, the supporting force and torque distribution of the two feet are optimized, the precision and stability of balance control are improved, frequent state switching is avoided, foot sole overturning is effectively prevented, and the safety and reliability of the system are enhanced.

The invention discloses a balance control method and system for amplitude and flow of a regulating valve for a chemical plant. The invention relates to the technical field of regulating valves. Calculating an error E between the target value O and the feedback value F: E = O-F; then, each PID controller i calculates an initial electric signal ei (t); each PID controller activates a bidirectional Seq-Bi-GRU recurrent neural network, executes a regression task based on the data set D of historical errors and the error E as input, and outputs an error threshold T1 for each PID controller, which is used for judging whether to activate the integral action of the PID controller or not; by introducing the bidirectional Seq-Bi-GRU recurrent neural network, the error threshold T1 and the saturation threshold T2 can be dynamically calculated based on the historical error data set and the current error. According to the dynamic adjusting mechanism, the integral action of the PID controller can be flexibly activated or closed according to the actual situation, and the integral saturation phenomenon of the multi-branch flow conveying system is effectively avoided.

The invention discloses a self-balancing control method applied to a heteroaxial two-wheeled vehicle, the vehicle carries a scissor-type double CMG module, the module comprises two CMG units, and the method comprises hardware decoupling: using the scissor-type double CMG to counteract course disturbance torque generated when the CMG works on a physical level; role separation: redefining a CMG system and a steering system; feedforward coordination: during turning, not depending on the CMG always generating a restoring moment to maintain a 0-degree inclination angle, calculating a steady-state inclination angle (phi lean) required at the speed and the steering angle through a dynamic model feedforward; and track planning: by coordinating track planning, it is ensured that the inclination action of the CMG and the steering action of the steering are perfectly synchronized in time, and balance is dynamically maintained. The problem of CMG saturation is solved, high-precision decoupling control is achieved, turning is smooth and safe, full-speed-domain coverage is achieved, and efficiency and energy saving are achieved.

The invention relates to a multi-objective optimization control method for an intelligent networked electric vehicle based on data driving and an application thereof. The method comprises the following steps: extracting a vehicle model for a single intelligent networked electric vehicle and obtaining a state representation of the vehicle model in a vehicle queue; constructing a data-driven prediction model based on a subspace identification method and historical data, and constructing a linear input and output mapping relation; constructing a multi-objective optimization function, and executing optimization control based on a multi-objective optimization result; the method is applied to a controller of an intelligent network-connected electric vehicle in a vehicle queue, the controller collects acceleration and braking operation data to track torque and outputs control quantity for executing optimization control, and queue control is achieved. According to the method, the problem of control performance degradation caused by modeling errors or system complexity is effectively solved; a multi-objective optimization problem is introduced, so that the practicability and robustness of the system under a complex working condition are enhanced; the control performance is balanced while the prediction precision is kept, and the operation safety, the energy saving performance and the cooperation efficiency of the intelligent network connection electric vehicle queue are effectively improved.

The invention relates to an electromagnetic bearing rotor system unbalance control method based on a DDPG algorithm, and the method comprises the following steps: building a rotor dynamics equation according to rotor dynamics, and carrying out the decoupling control; constructing a compensation current, extracting an unbalance coefficient in the compensation current, and constructing a self-adaptive identification equation; constructing a DDPG intelligent agent, fusing position errors, system response and control output, and designing a multi-target reward function through a normalized weighted optimization strategy; and a DDPG intelligent agent is used to optimize an unbalance coefficient identification parameter, and a compensation current is dynamically adjusted in combination with the rotating speed of the rotor, so that unbalance force disturbance is counteracted. According to the invention, identification is carried out by combining the deep reinforcement learning algorithm DDPG according to the unbalance coefficient reflected to the two ends of the rotor by the unbalance force borne by the rotor, the identification and unbalance compensation efficiency of the unbalance coefficient is improved, and rapid, stable and efficient compensation of a rotor system is realized.