144 results about "Equilibrium control" patented technology

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.

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 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 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 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 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 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 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 provides a multi-source cooperative operation and dynamic adjustment method for a power distribution network, and relates to the technical field of power system operation and control, and the method comprises the steps: building a multi-level physical characteristic model based on the collected network topology parameters of the power distribution network and the physical operation parameters of all distributed energy devices; on the basis of the multi-level physical characteristic model, a master-slave collaborative optimization control architecture is utilized to obtain collaborative balance control conditions; based on the master-slave collaborative optimization control architecture, the collaborative balance control condition and the initialized energy management interaction signal, distributed iterative calculation is carried out to obtain an energy management interaction signal and a power control strategy; and based on the real-time operation state data and the power control strategy of the power distribution network at the current moment, performing rolling optimization calculation in a limited time domain by using a model prediction control method to obtain a real-time control instruction for driving each distributed energy device to act. According to the invention, the problem that multi-body operation and dynamic optimization in the power distribution network are difficult to coordinate in the prior art is solved.

The present application relates to a kind of narrow body vehicle balance control method based on control moment gyro, belong to narrow body vehicle active roll control system field.The dynamics equation of control moment gyro is established, the active roll dynamics model of narrow body vehicle is calculated to obtain the roll angle error and roll angular velocity error of vehicle, then the active roll controller is designed using sliding mode control method to control the roll angle error and roll angular velocity error, and the rotational angular velocity of control moment gyro frame is obtained;Finally, the control moment gyro on narrow body vehicle is adjusted in real time, and vehicle balance is realized.The vehicle roll scheme in the present application uses control moment gyro device, with high control precision, fast response speed, and independent of suspension system, can realize greater balance torque.By controlling the frame angular velocity of control moment gyro, the dynamic balance of narrow body vehicle when steering can be realized, to assist the safe steering of driver.

The invention relates to the field of automatic balance weight forklifts, in particular to an automatic balance weight forklift control method and system based on multi-source data, and the method comprises the steps that the multi-source data of a sensor are obtained; compensating the weighing value of the left pallet fork and the weighing value of the right pallet fork according to the real-time attitude angle of the forklift, and generating an equivalent left weighing value and an equivalent right weighing value under the horizontal reference system; calculating a static gravity center offset component and a dynamic inertia offset component; performing addition or weighted summation on the static gravity center offset component and the dynamic inertia offset component to obtain a dynamic gravity center offset; inputting the real-time center-of-gravity offset into a balance controller, and judging whether the absolute value of the center-of-gravity offset reaches or exceeds a preset stable safety threshold value or not by the balance controller; and if so, triggering a balance control strategy. Through hierarchical feature construction and physical constraint fusion of multi-source data, high-precision and low-delay dynamic gravity center estimation is realized, so that the effect of dynamically adjusting a forklift control strategy is achieved.

The invention discloses an intelligent landing leg automatic balance control system and control method, and belongs to the technical field of landing leg control. The method is used for solving or improving the technical problems that the anti-shake capability is insufficient under the dynamic load and the sensor error affects the balance precision in the existing scheme. Through the technical advantage of independent operation of each module, the high-precision data of the sensing module, the intelligent strategy of the decision control module, the precise action of the execution module, the risk prevention and control of the security module, and the deep cooperation of the data-strategy-action closed loop, control-protection double tracks and scene adaptation optimization among the modules, the safety of the system is improved. The full-process efficient linkage of data acquisition, dynamic control and safety guarantee is realized, and the dynamic load adaptive capacity, the balance control precision and the system reliability are effectively improved.

The present invention discloses a control method and control system for cooling balance in a pipe network, which adopts a method to meet the needs of the first unfavorable cooling user. First, the normal return water temperature range value of the user is preset; then, the return water temperature value and valve opening of each user are monitored; then, the first unfavorable cooling user is obtained, and when the user is monitored to have a maximum valve opening and a return water temperature value not within the preset normal return water temperature range value, it is determined to be the first unfavorable cooling user; the working frequency of the cooling water pump can be adjusted, and the cooling water pump can adjust the water supply again, or only the valve opening can be adjusted to adjust the water supply amount for different users; finally, it is ensured that the return water temperature value of each user is within the preset normal return water temperature value, and the pipe network enters a cooling balance state; this solves the problem in the prior art that a centralized cooling system generally uses a balancing valve for cooling balance control, resulting in poor cooling balance control effect caused by control disorder.

The invention relates to the technical field of hoisting equipment control, in particular to a double-beam crane control device for a lifting gas engine unit of a power plant, which comprises the following modules: a load stabilizing module for monitoring the tension difference and the swing amplitude of a hoisting cable in real time and starting an automatic adjusting function when the tension difference and the swing amplitude exceed a set threshold value; the path planning module is used for generating a hoisting path according to the weight and the size of the gas engine unit and adjusting the path when an obstacle or working condition change is detected; the dynamic balance module is used for monitoring the vertical offset and the vibration condition of the gas engine unit, and the alarm prompting module is used for sending out an acousto-optic warning signal when an abnormal condition occurs in the hoisting process; according to the method, intelligent feedback control, self-adaptive path planning and high-precision positioning technologies are introduced, so that the defects in the aspects of load stability, dynamic balance control and complex working condition adaptability in the prior art are overcome, and the safety and high efficiency of the gas engine unit in the hoisting process are ensured.

The invention discloses a building comprehensive management control method and device and a medium, and belongs to the technical field of building automation control, and the method comprises the steps: building a dual-medium coupling model between an air medium and a building structure medium, and carrying out the parameterization; establishing a heat flux balance equation based on a parameterization result; building operation data and environment data are collected and processed; the air medium enthalpy difference change rate and the building structure body temperature change rate are calculated and substituted into the heat flux balance equation, the real-time heat flux difference is obtained, and a coupling state vector is generated; and inputting the coupling state vector into a dynamic balance optimization control equation to execute iterative solution, obtaining a control variable, and generating a control signal to adjust a building operation state. According to the method, an energy transfer rule is accurately described through double-medium coupling modeling, a heat flux balance equation is established to realize dynamic balance control, control variables are divided into air side and building structure body side adjustment components to realize multi-system collaborative optimization, and the control precision and the energy-saving effect are improved.

The invention discloses a Nash equilibrium control method for a data-driven unmanned system under incomplete information. The method comprises the following steps: constructing a distributed dynamic state feedback controller for an unmanned system, and converting a Nash equilibrium solving problem into an output adjustment problem; in the off-line stage, a continuously excited control input sequence is applied to the unmanned system, a corresponding state sequence, a state derivative sequence, a measurement noise sequence and an external signal sequence are collected, and unmanned system data matrixes are constructed respectively; based on the unmanned system data matrix, a Nash equilibrium search problem is converted into a semi-definite programming problem and solved, and a dynamic feedback control gain matrix is obtained; and in the online stage, the controller of each agent dynamically adjusts a decision based on a control signal generated by the dynamic feedback control gain matrix, so that the unmanned system is converged to a Nash equilibrium point. According to the method, an offline and online scheme of data driving and no precise modeling is adopted, robust anti-interference and distributed equilibrium convergence are achieved, and the method is suitable for a complex unmanned collaborative scene.

The present invention discloses a humanoid robot dynamic jumping and balance control method, electronic equipment, and medium. The method comprises the following steps: planning the trajectory of the center of mass and the sole of the foot of the humanoid robot during jumping; modeling the humanoid robot as a single rigid body, taking the position, angular offset, linear velocity, and angular velocity of the robot's center of mass as state variables, and taking the ground contact force and the ground contact torque as control quantities, constructing a model predictive control problem, and converting the problem into a standard QP problem for solution to obtain the optimal ground reaction force and torque; constructing a whole-body motion control model, utilizing the desired end state and the optimal ground reaction force to obtain the joint position, velocity, and feedforward joint torque; controlling the humanoid robot to perform jumping motion according to the joint position, velocity, and joint torque; the joint torque being the sum of the feedforward torque and the feedback torque, and the feedback torque being calculated by proportional differential control; and adopting a stride strategy to achieve landing stability of the robot after the humanoid robot lands.

The present disclosure relates to the technical field of intelligent robots, and specifically provides a robot, a control method and device thereof, and a storage medium. A robot control method includes obtaining first attitude information of a robot and determining second attitude information of a standing surface according to the first attitude information, determining a target dynamic equation according to a dynamic equation of the robot and a dynamic equation of the standing surface, establishing a control optimization task of the robot based on the target dynamic equation, obtaining target torques of each joint of the robot based on the first attitude information, the second attitude information and the control optimization task, and controlling movements of each joint of the robot according to the target torques. In the present disclosure, through dynamic analysis and optimization control of the attitude of the robot and the attitude of the standing surface, the balance problem of the robot on a dynamic standing surface is solved, the balance control of the robot on the dynamic standing surface is realized, the application scenario of the robot is expanded, and the control stability of the robot is improved.

The invention relates to an electricity-hydrogen-chemical-storage-heat multi-energy coupling system intelligent regulation and control simulation verification platform and method based on a distributed architecture, and the platform comprises an energy management and control platform which employs a cross-time-scale layered regulation and control architecture and comprises an optimization scheduling layer and a cooperative control layer; the optimization scheduling layer generates a multi-time scale scheduling instruction from a second level to a day level based on a multi-target dynamic optimization function; the cooperative control layer receives an instruction of the optimization scheduling layer, and executes real-time electricity-hydrogen-storage-heat cooperative frequency and voltage regulation control through a power balance controller, a heat supply network balance controller and a hydrogen transmission balance controller; the distributed simulation system is used for truly simulating dynamic behaviors of the physical system; and the timing system is used for providing a global clock synchronization signal for the energy management and control platform and the distributed simulation system. According to the method, a high-precision, high-real-time and high-reliability simulation verification means is provided for coal-based chemical green low-carbon transformation, the engineering risk can be remarkably reduced, and the flexibility and economical efficiency of the system are improved.

The invention discloses a flexible interconnection device energy balance control method, system and equipment based on multi-port power interaction, and a medium, and belongs to the technical field of flexible interconnection device energy balance control, and the method comprises the steps: collecting multi-port flexible data; obtaining a system state estimation value; adjusting the droop control coefficient of each port by adopting a self-adaptive adjustment mechanism; calculating reference power and reference voltage of each port according to the droop control coefficient and the system state estimation value; calculating the energy balance control quantity of each port based on a Lyapunov energy function; calculating a multi-port coordination control quantity; generating a total control quantity of each port; the fault is judged by comparing the residual signal with a fault detection threshold value; and outputting the power regulation quantity and the voltage regulation quantity of each port according to the total control quantity. According to the multi-port coordination control algorithm, the power coupling effect between the ports is effectively processed through the coordination coefficient between the ports and the double-layer control structure, and the system oscillation is reduced.

The invention discloses an intelligent low-temperature liquid evaporator control optimization method. The method comprises the steps of low-temperature liquid evaporator multi-valve control unit modeling, self-adaptive evaporator loss function design, multi-valve control unit centralized execution evaluation architecture design, priority experience playback training and evaporator control optimization. The invention belongs to the field of intelligent control, and particularly relates to an intelligent low-temperature liquid evaporator control optimization method, which comprises the following steps of: respectively constructing a precision control reward item, an energy consumption penalty item and a safety penalty item, and balancing control precision and system collaboration; based on self-adaptive evaporator loss function design, action logic contradictions are avoided through conflict punishment, and then control optimization stability is improved; the action conflict degree is incorporated into experience priority calculation, and a conflict scene is learned preferentially; importance weight and collaborative penalty design are added to evaluate network loss, so that the action conflict probability is remarkably reduced; and the distribution offset is corrected through importance sampling, so that the control optimization reliability is improved.

This invention discloses a force balance control method for a six-dimensional active cellular micro-force sensor. The micro-force sensor includes a probe, a moving platform, a base, and six measurement branches connecting the moving platform and the base. Each measurement branch consists of a flexible beam, a sensing layer, and a driving layer. The method includes: when the probe at the end of the micro-force sensor is subjected to an external measuring force, the flexible beam deforms accordingly; the real-time pose of the moving platform is measured by the sensing layer of each measurement branch; the difference between the real-time pose and the desired zero pose is used to obtain an error signal, which is then fed into a robust sliding mode predictive controller to generate a corresponding control law; the control law then passes through a damping compensator and a decoupler to obtain a control input voltage signal, which is applied to the driving layer. Under the voltage, the driving layer undergoes bending deformation, causing the moving platform pose to return to the desired equilibrium position. This invention effectively solves the problem of complex lumped interference and achieves the goal of fast response, strong robustness, and high stability force balance control.

The invention relates to the technical field of shield tunneling machine control, in particular to a self-balancing control system and method for a slurry shield, and the method comprises the following steps: in the tunneling process of a shield tunneling machine, obtaining the pressure of a working bin and the liquid level of an air cushion bin in real time; entering the pressure control mode according to the received instruction for selecting the pressure control mode; entering the liquid level control mode according to the received instruction for selecting the liquid level control mode; in the pressure control mode, the pressure of the working bin is maintained near the pressure target value of the muddy water bin; and in the liquid level control mode, the deviation, obtained in real time, of the air cushion bin liquid level and the air cushion bin liquid level target value is judged, and according to the deviation obtained through judgment, the rotating speed of the sludge discharging pump is adjusted so that the liquid level of the air cushion bin can tend to the air cushion bin liquid level target value. According to the invention, cooperative control of pressure and liquid level is realized, so that the slurry shield keeps stable pressure and moderate liquid level in the tunneling process, and the automation characteristic improves the control precision, the response speed and the safety of the system.

The invention discloses a vehicle self-balancing control method and device, equipment, a vehicle, a program product and a storage medium, the vehicle comprises two wheels arranged front and back, and the method comprises the steps that the driving state of the vehicle in a self-balancing mode is detected, and first state data is obtained; the first state data comprises vehicle head steering state data, vehicle body inclination state data and vehicle speed related data; determining first control data of the vehicle according to the first state data, wherein the first control data comprises vehicle head steering control data and vehicle speed related control data of the vehicle; the vehicle head steering of the vehicle is adjusted according to the vehicle head steering control data, and the vehicle speed related state of the vehicle is adjusted according to the vehicle speed related control data, so that the vehicle approaches or achieves a control target; wherein the control target comprises a preset vehicle body inclination state, and the vehicle is in a driving self-balancing state under the preset vehicle body inclination state.