611 results about "Feedback controller" patented technology

The invention provides a dynamic path planning method and system in an intelligent traffic system, and relates to the technical field of intelligent traffic. Constructing a dynamic road network traffic capacity model based on a space-time diagram convolutional network; generating a multi-branch trajectory prediction result with a confidence score, adaptively starting an encryption parameter synchronization mechanism in combination with vehicle density, and generating a candidate path set through multi-agent collaborative game optimization; performing multi-dimensional deviation degree evaluation based on actual driving data and planning expectation; synchronously generating a multi-mode cooperative guidance signal; the system comprises a multi-source data fusion unit, a space-time modeling engine, a hierarchical decision-making system, a path verification and execution module, a closed-loop feedback controller, an event response system and a multi-mode man-machine interface. According to the method, the global resource utilization efficiency is improved through cooperation of data-driven modeling and hierarchical game decision, and the real-time performance, the safety and the system adaptability of path planning are improved through a closed-loop feedback and event response mechanism.

The present invention relates to the technical field of circuit control, and relates to a direct-current high-voltage generator regulation and control method and system based on intelligent feedback. A fuzzy control logic operation is performed on an output current flux value and an input voltage fluctuation factor of a load experimental object, so as to obtain the disturbance amplitude of a voltage fluctuation state for a current flux change trend; if a step-up transformer can execute a PID control technology by adjusting a transformation ratio, PID real-time adjustment parameters are calculated, and a crossover mutation operation of individuals is performed on the basis of a fitness function, so as to generate a first boost regulation and control scheme; and if the step-up transformer cannot execute the PID control technology by adjusting the transformation ratio, a calibrated state feedback controller is constructed on the basis of a state variable of the current step-up transformer and an adjustment signal output amplitude, so as to generate a second boost regulation and control scheme. The present invention achieves intelligent feedback regulation and control by independently analyzing components of direct-current high-voltage generators, improving the stability and accuracy of outputting high-voltage direct current.

The invention provides a control method of tension adjusting equipment on a composite copper foil continuous production line, which comprises the following steps: acquiring a tension set value and a tension actual value of adjacent stations on the composite copper foil continuous production line, and calculating a difference value between the tension set value and the tension actual value to obtain tension deviation data; in the process of adjusting the tension between the adjacent stations, judging whether the copper foil snakes or not, and if yes, feeding back snaking offset data of the copper foil to a feed-forward compensation function and a feedback controller so as to cooperatively adjust the control of the tension; on the basis of tension balance between adjacent stations, operation parameters of all stations of the composite copper foil continuous production line are collected in real time, and a production line operation mathematical description function is established; and optimizing control parameters of production line operation in combination with a preset rule in the preset knowledge base.

The present invention relates to adaptive multi-state encoding and processing in virtualized computing environments. The system includes a virtualized state selection module that dynamically transitions between binary, ternary, quaternary, and higher-order encoding states based on workload, bandwidth, security posture, and compliance requirements. A virtual encoding engine utilizes hardware-accelerated components, such as vFPGAs, vGPUs, and cTPUs, to enhance encoding throughput. A compliance-driven feedback controller continuously monitors encoding efficiency, threat levels, and adherence to mandates such as GDPR, HIPAA, and FIPS 140-3. Additional features include AI-based anomaly detection, federated model refinement, distributed ledger-backed audit trails, and quantum-resistant encoding techniques. By integrating intelligent encoding decisions with scalable compliance enforcement, the system enables high-performance, secure, and regulation-ready data processing across distributed cloud and edge environments, delivering measurable improvements in system responsiveness, data integrity, and operational trust.

The invention provides an automatic energy-saving control method and device for a ring cooling fan based on load feedback, relates to the field of ring cooling fans, and solves the technical problem of delay of regulation and control in an energy-saving working state. The method comprises the steps that working condition data are input into a preset powder box model, and a feed-forward air volume instruction is obtained through calculation; and inputting the working condition data into a state observer to obtain an optimal estimated temperature value. And the deviation between the optimal estimated temperature value and a preset temperature set value is calculated, and a feedback air volume compensation instruction is obtained through calculation of a feedback controller according to the deviation. And fusing the feed-forward air volume instruction and the feedback air volume compensation instruction to obtain a final air volume control instruction, and issuing the final air volume control instruction to a fan frequency converter for execution. And continuously monitoring the numerical value and the change trend of the feedback air volume compensation instruction, taking the feedback air volume compensation instruction as a prediction error signal of the powder box model, and adaptively adjusting key thermal parameters in the powder box model. The method is used in the control process of the ring cooling fan.

The invention discloses a multi-agent spatio-temporal dynamic system intrusion tolerance and fault tolerance cooperative security consistency control method. The method comprises the following steps: constructing mathematical models of a leader and a follower of a multi-agent spatio-temporal dynamic system based on a partial differential equation; constructing a mathematical model of actuator faults and spoofing attacks; defining a consistency condition to obtain an error system; constructing a proper Lyapunov functional, and obtaining a system stability criterion by using a Lyapunov stability theory; and the error of the multi-agent space-time dynamic system tends to zero by using the state feedback controller, so that the system realizes safety consistency control. The invention comprehensively considers that a multi-agent space-time dynamic system is easy to have actuator faults in a complex environment and is easy to suffer from network attacks in network communication, introduces an intrusion tolerance and fault tolerance cooperative security consistency control method, improves the robustness of the system, and improves the reliability of the system. And the multi-agent space-time dynamic system can achieve a safety consistency control target.

The invention relates to the technical field of trajectory tracking control of piezoelectric motion tables, and discloses a trajectory tracking control method and device for a piezoelectric console, and the method comprises the steps: constructing an initial dynamic model of a piezoelectric motion table based on an asymmetric Bouc-Wen hysteresis model, and obtaining a to-be-identified parameter set; based on the root-mean-square error between the actual output displacement of the piezoelectric motion platform at the plurality of sampling time points and the predicted output displacement of the initial dynamical model, constructing a self-adaptation function of the parameter set to be identified; identifying and acquiring a target model parameter set by using a multi-modal Bayesian gradient optimization algorithm and taking the value convergence of the self-adaption function as an optimization target to obtain a target dynamic model; based on the target dynamic model, constructing a hysteresis state observer, and obtaining feed-forward compensation voltage; constructing a self-adaptive fuzzy PID feedback controller, and obtaining a feedback control voltage; and summing the feedforward compensation voltage and the feedback control voltage to generate a driving voltage so as to drive the piezoelectric motion table to perform trajectory tracking.

The invention belongs to the technical field of unmanned system control, and particularly relates to a data-driven unknown nonlinear system output adjusting method and device. The method specifically comprises the following steps: constructing an inner membrane system: constructing a k-order auxiliary matrix of an evolution matrix according to an external reference signal, and calculating an inner membrane matrix pair based on the auxiliary matrix to form the inner membrane system; a nonlinear system, a sensor and an inner membrane system are connected in sequence, control input is directly applied to the nonlinear system, the difference between the output of the sensor and a trajectory expected to be tracked is used as the input of the inner membrane system, and the state of the nonlinear system and the state of the inner membrane system are collected. Calculating the nonlinear state of the nonlinear system, the derivative of the state and the derivative of the state of the inner membrane system; constructing a filtering matrix by using the evolution matrix of the external reference signal; solving a positive semidefinite programming problem by using the collected data and the filtering matrix to obtain a construction control gain matrix; and constructing a feedback controller by using the control gain matrix to realize system output control.

The invention relates to the technical field of power system control, solves the problems of network attack, limited bandwidth and transmission delay of a power system in a signal transmission process and conservative DET parameter selection and controller design, and particularly relates to a power system dynamic event triggered load frequency control method under Dos attack and random delay. Comprising obtaining a continuous time system parameter matrix; setting an event triggering threshold function; state parameters facing Dos attack and random time delay conditions are set; constructing a state feedback controller; and collaborative design optimization is carried out by applying a GA optimization algorithm. Compared with a traditional control method, the method has the advantages that on the premise of ensuring the stability of the system, by optimizing event triggering conditions, the communication requirement and bandwidth occupation are remarkably reduced, the utilization efficiency of communication resources is improved, network congestion and delay possibly caused by frequent communication are reduced, and the service life of the system is prolonged. And the operation efficiency of the whole power system is improved.

The invention relates to the field of thermal power generation, and discloses a thermal power boiler combustion optimization method based on multi-parameter feedback control, which comprises the following steps: acquiring key parameters such as oxygen concentration, temperature, pulverized coal concentration, air flow, pulverized coal flow and boiler load in boiler operation; establishing a distributed parameter model for describing dynamic changes of oxygen concentration, temperature and pulverized coal concentration in the hearth along with time and space; key characteristic variables representing the combustion state are extracted through multi-scale analysis; dynamically optimizing multiple parameters of different areas in the hearth based on a distributed feedback controller; a global optimization objective function is constructed, and the ratio of the air flow to the pulverized coal flow is dynamically adjusted; and the optimized control instruction is sent to a boiler system, and combustion parameters are adjusted in real time through an execution mechanism. According to the method, through distributed modeling, multi-scale analysis and feedback control, the combustion efficiency is remarkably improved, pollutant emission is effectively reduced, and the method can adapt to coal quality fluctuation and load change.

The invention provides a multivariable decoupling control method and system for an air inlet system of a high-altitude simulation cabin, and the method comprises the steps: firstly building a precombustion chamber cavity thermodynamic differential equation, and building a state equation in combination with a regulating valve first-order inertia model and an engine model; constructing a decoupling matrix by using a differential flatness theory, and converting a pressure and temperature coupling system into an independent control channel; monitoring a system state in real time by using an extended state observer, uniformly estimating internal and external disturbances as total disturbances, and generating a compensation signal; the model prediction controller performs rolling optimization on future time domain control quantity according to deviation between a set value and an actual value, generates an initial instruction in combination with the compensation signal, and converts the initial instruction into an independent valve control signal through a decoupling matrix; the high / low-temperature airflow mass flow is controlled through the opening degree of the adjusting valve, the engine model outputs actual parameters to form closed-loop feedback, and the controller updates the control quantity in each cycle. The multi-variable strong coupling, the dynamic disturbance and the model uncertainty are effectively overcome, the control precision and the parameter robustness are both achieved, and the complex working condition requirements are met.

The invention belongs to the technical field of cluster unmanned system cooperative control, and particularly relates to a heterogeneous unmanned system data driving cooperative output adjusting method and device. The method specifically comprises the following steps: S100, setting that the heterogeneous unmanned system is composed of a plurality of unmanned monomers and follows an external system; introducing an inner membrane system, and establishing an expansion system of each unmanned monomer according to the kinetic model of the unmanned monomer; s200, open-loop track data of an expansion system of each unmanned single body is obtained through an offline experiment, and a data matrix is obtained; s300, based on the data matrix, calculating a distributed data driving control gain matrix; and S400, based on an inner membrane system state and the control gain matrix, obtaining a distributed dynamic state feedback controller, and realizing output adjustment of the unknown model heterogeneous unmanned system.

The invention belongs to the technical field of networked multi-axis motion control, and discloses a multi-axis cooperative control method, system and device based on digital-analog linkage, and the method comprises the steps: outputting a tracking error prediction value corresponding to a reference trajectory through an offline single-axis tracking error prediction model, and compensating the tracking error prediction value to the reference trajectory to obtain a new reference trajectory; the feedback controller generates a control signal according to the new single-axis reference trajectory and the actual trajectory, and the disturbance observer estimates external disturbance in real time based on the control signal and the actual trajectory and outputs a disturbance estimation result; according to the reference trajectory and the actual trajectory, estimating a contour error by using a Newton iteration method, inputting the contour error into a generalized cross coupling controller, and calculating to obtain a contour error compensation amount for each single axis; and combining the single-axis control signal, the disturbance estimation result and the contour error compensation amount to serve as control input of the mechanism model, and obtaining an actual track output by the mechanism model. According to the invention, high-precision contour tracking control of networked multi-axis equipment is realized.

Systems and methods for controlling a variable-pitch propeller of an aircraft are provided. A method for controlling the variable-pitch propeller includes using a feedback controller, operating the variable-pitch propeller at a current operating condition including a current rotational speed, determining a speed error between the current rotational speed of the variable-pitch propeller and a set point rotational speed for the variable-pitch propeller, determining a gain for the feedback controller based on a power coefficient and an advance ratio of the variable-pitch propeller. Using the feedback controller, a propeller pitch command is determined based on the speed error and using the gain. The pitch of the variable-pitch propeller is adjusted according to the propeller pitch command to reduce the speed error.

The invention provides an LED lamp adaptive speed regulation heat dissipation method and system based on real-time junction temperature monitoring. The method comprises the following steps: S100, acquiring a PWM signal or an analog signal of an LED driving command signal in real time; s200, on the basis of the change of the driving instruction signal, feedforward prediction is carried out by using a dynamic thermal inertia mapping model, and a feedforward fan control quantity is generated; s300, LED junction temperature is monitored in real time through a forward voltage method, and feedback fan control quantity is generated through a feedback controller according to the deviation between the real-time junction temperature and the target junction temperature; and S400, synthesizing the feedforward control quantity and the feedback control quantity to generate a fan PWM control signal, outputting the fan PWM control signal to a fan driving circuit, and adjusting the rotating speed of the cooling fan. According to the method, driving signals and junction temperature information are processed in parallel, and feedforward and feedback control is combined, so that self-adaptive accurate regulation and control are realized, thermal load change is quickly responded, system lag is effectively inhibited, and LED heat dissipation performance is optimized.

The invention relates to the technical field of unmanned aerial vehicle flight control, and provides an unmanned aerial vehicle trajectory tracking control method and system based on self-adaptive dynamic programming, and the method comprises the steps: obtaining a position subsystem control input through a control law of a position subsystem based on a position loop expected value, an external interference estimated value and a position tracking error, and carrying out the control of the position subsystem; a position coordinate vector and a first-order derivative thereof are calculated by adopting a position subsystem so as to update a position tracking error, and an external interference estimated value is updated through an interference observer; based on an Euler angle vector reference signal, feedforward control input is obtained through calculation, attitude subsystem control input is obtained through calculation in combination with optimal feedback control input, an Euler angle vector and a first derivative of the Euler angle vector are calculated through an attitude subsystem, an optimal feedback controller is designed for a nominal error system by adopting a self-adaptive dynamic programming method, and the optimal feedback controller is used for controlling the nominal error system. And updating the optimal feedback control input. And the unmanned aerial vehicle system is ensured to have the optimal tracking performance while having relatively high robustness in finite time.

The invention discloses a miniature proportional valve control method based on active-disturbance-rejection control, and relates to the technical field of miniature proportional valve control, and the method comprises the steps that a target flow set value is received and is used as a control signal to be sent to a control unit, and the control unit comprises a tracking differentiator, an expansion state observer and a nonlinear feedback controller; the tracking differentiator processes the target flow set value to obtain a differential input signal; the expansion state observer receives the differential input signal and the actual flow feedback signal, and estimates the total disturbance of the system in real time to obtain a disturbance estimation value; the non-linear feedback controller combines the differential input signal and the disturbance estimation value to generate a compensation current signal; the compensation current signal is used as a control parameter of the micro proportional valve, and the position of the valve element is accurately adjusted. An active disturbance rejection control algorithm is adopted, the control performance and disturbance rejection are improved, accurate flow control of the micro proportional valve is achieved, and the micro proportional valve is more suitable for industrial application with high requirements.

The invention provides a pressure test control method and system for a universal pressure testing machine, and relates to the technical field of material testing machines, and the method comprises the steps: obtaining hydraulic cylinder parameters and servo valve parameters, building a pressure control mathematical model, calculating a transfer function, initializing a feedback controller, determining the number of hidden layer nodes, and setting an activation function and a network weight. A self-adaptive feedback controller is obtained; generating a closed-loop control system, constructing an objective function based on an integral absolute error and adjustment time, determining a Pareto optimal solution set in combination with a multi-objective genetic algorithm, selecting a neural network training sample, generating a training sample set, performing offline pre-training, and updating a network weight to obtain a pre-trained neural network; and the feedback controller is embedded into a pressure control system, outputs feedback controller parameters, sets an anti-saturation strategy of the feedback controller, judges whether the feedback controller is saturated or not, limits the amplitude of an integral item according to the relation between an error signal and a saturation direction, determines whether to stop integration or not, and generates a press control strategy under the current working condition.

The present application relates to a kind of vehicle steering body posture and control method of handling stability, comprising the following steps: the signal input required for control is collected, vehicle total anti-lateral moment is calculated by body posture feedforward-feedback controller, front and rear axle anti-roll moment distribution ratio is calculated by handling stability feedforward-feedback controller, total anti-roll moment and its front and rear axle distribution ratio are calculated, revised by control comprehensive module, finally output each suspension angle vertical force control instruction of vehicle.The present application has the following advantages:1) vehicle body posture control and handling stability control are comprehensively considered, and both are simultaneously optimized;2) vehicle body posture control and handling stability control both use feedback-feedforward, avoid the problem of pure feedforward control or feedback control, so that the overall performance of vehicle is more "natural";3) steering input and road input are decoupled, and four high sensors are saved.

The utility model relates to a laser automatic frequency locking system based on similarity identification spectrum, comprising a laser, a spectrum module, a digital PID feedback controller and an automatic frequency locking operation system, the automatic frequency locking operation system is used for determining a locking point of a received spectrum signal based on a similarity identification algorithm, and determining a corresponding automatic frequency locking parameter based on the locking point, and performing PID locking control on the laser by the digital PID feedback controller based on the automatic frequency locking parameter of the locking point. The scheme has the advantages of small environmental influence interference, more stable working state, wide application range and high working efficiency.

The invention discloses a high-speed train operation control method based on an adaptive neural network. The method comprises the steps that a longitudinal dynamic model of a high-speed train is established, the speed and acceleration states of the train are observed in real time through a high-order sliding mode observer, the unknown system dynamic state is recognized in combination with the neural network, and the dynamic approximation precision is improved. And by utilizing a self-adaptive output feedback controller and combining the observed train state and the approached unknown dynamic state, the accurate tracking control of the train displacement and speed is realized. According to the controller, the accumulation of parameter estimation errors is inhibited by introducing a leakage item, and the adaptability of a train to uncertainty is enhanced. The control method provided by the invention can effectively improve the running stability and trajectory tracking precision of the train, and ensures the safe and reliable running of the train under unknown dynamic interference.

The invention discloses a motorcade distributed cooperative control method under dual attacks of sensors and actuators, and relates to the technical field of motorcade safe operation control. The problems that a traditional motorcade cooperative security control method is poor in environmental adaptability, insufficient in attack compensation capability and insufficient in robustness are solved. The thought of hierarchical control is adopted, and the designed hierarchical control comprises a basic cooperative controller of each vehicle, a first cooperative feedback controller of each vehicle, an advanced cooperative controller of each vehicle and a second cooperative feedback controller; the stability of the system under the sensor attack is ensured through a first cooperative feedback controller, an advanced cooperative controller is designed to counteract the influence of the attack on a control loop, and an actuator attack forms negative value compensation through a second cooperative feedback controller and is fed back to a feedforward compensation module of a vehicle. The system disturbance caused by the attack of the actuator can be resolved in real time, and the robustness of control is ensured. The method is mainly applied to the cooperative control of the motorcade.

The invention provides a suspension optimal control method and system based on feedforward and feedback, and the method comprises the steps: constructing a suspension system dynamic model, and constructing a suspension control force model according to the suspension system dynamic model; a state observer is constructed, then the current suspension state of the vehicle is estimated by using the state observer, then a feedback controller is constructed, and the suspension state is imported into the feedback controller to obtain feedback control force; constructing a feed-forward controller, then obtaining road surface unevenness information, and importing the road surface unevenness information into the feed-forward controller to obtain feed-forward control force; and importing the feedforward control force and the feedback control force into a suspension control force model to obtain the optimal control force of the system. According to the vehicle suspension control method and device, the problems that in the prior art, the vehicle suspension is controlled according to the running state of the vehicle affected by vibration, if sudden large-amplitude vibration influence occurs, operation among parts of the suspension exceeds the normal range, and the vehicle cannot run stably are solved.

The invention relates to the technical field of data center machine room energy conservation, and discloses a machine room cold channel closed management method and device and terminal device.The method comprises the following steps that the state of a cold channel is obtained by deploying environment monitoring nodes, a heat-flow coupling model and a stability function are constructed, a feedback controller is designed to generate an air door and refrigeration control instruction, and a heat-flow coupling model is established; linkage adjustment of the air velocity and the temperature is achieved, closed-loop control is constructed, and efficient and energy-saving management of a cold channel is achieved; the device comprises an environment monitoring module, a state modeling module, a stability evaluation module, a state feedback control module and an execution linkage module. Through state fusion updating, a component control structure, a stability function driving strategy and a linkage execution mechanism, fine adjustment and efficient cooperative control of the temperature and airflow of the cold channel are achieved, the adjustment stability and response efficiency are improved, energy consumption is remarkably reduced, and the problems that an existing system is poor in control precision, poor in linkage performance and the like are solved.

The invention relates to the technical field of audio processing, and discloses an audio output control method, device and equipment and a storage medium, and the method comprises the steps: detecting an input voltage signal and collecting an audio input signal through an MCU control unit, obtaining a voltage parameter matrix and an audio parameter matrix, and combining the voltage parameter matrix and the audio parameter matrix to form a mixed feature matrix; inputting the mixed feature matrix into a deep neural network for feature extraction to obtain an audio feature space; constructing a cross attention model, calculating an association weight value among the audio parameters, and generating an audio curve switching control sequence; switching a control sequence based on an audio curve, dynamically adjusting the voltage of the power amplifier through a feedback controller, and collecting working state data of the power amplifier; and performing nonlinear distortion compensation and noise suppression processing on the working state data of the power amplifier to generate an audio output quality parameter, thereby effectively solving the problem of unstable audio output under different power supply conditions, and realizing intelligentization and precision of audio output control.

The invention discloses a denitration ammonia injection control system and method.The system comprises a feed-forward controller, an ammonia injection control unit and a control unit, and the feed-forward controller is used for calculating the theoretical ammonia injection amount according to the NOx concentration of an inlet and the flue gas flow speed; the inlet NOx abrupt change pre-judgment controller is used for predicting the change trend of the inlet NOx concentration through a machine learning model based on the historical operation data of the equipment and outputting a preset ammonia injection amount; the feedback controller is used for performing closed-loop correction according to the deviation between the measured value and the set value of the NOx concentration of the exhaust port and outputting the compensated ammonia spraying amount; the exhaust port NOx abrupt change pre-judgment controller is used for monitoring the change rate of the exhaust port NOx concentration, triggering an emergency ammonia spraying mode when the abrupt change working condition is recognized, and outputting the emergency ammonia spraying amount; the jitter elimination controller is used for carrying out filtering and step length limitation on the total output of the controller so as to generate a stable final ammonia spraying total amount control instruction; and the execution unit is used for receiving and executing the final total ammonia spraying amount control instruction. The system can accurately control the total amount of sprayed ammonia.

The invention relates to an electrically-driven deep sea winch active wave compensation control method based on ship motion prediction. The method comprises the steps of data collection, optimization and training of a motion prediction model, ship motion prediction, prediction controller signal generation, feedback controller signal generation, control signal synthesis and control execution. According to the control method, the active wave compensation capability of the winch system under the complex sea condition is improved by adopting the motion prediction control method based on the LSTM model and PSO optimization. According to the method, a more accurate control basis is provided by predicting the future motion state of the laying lifting point in a high-precision manner, and hyper-parameters of the LSTM are adjusted through a PSO optimization algorithm, so that the prediction model keeps the optimal performance under different sea conditions. According to the system, predictive control is combined with feedback control, rapid response and accurate control in complex sea condition changes are ensured, the response lag and oscillation problems are effectively reduced, and the rapidity and reliability of active wave compensation of a winch system in deep sea operation are improved.

The invention discloses a hydroelectric generating set power active control method, system and device based on frequency prediction and a medium, and belongs to the technical field of power control, and the method comprises the steps: collecting basic operation data of a hydroelectric generating set adjusting system in real time, and carrying out the preprocessing of the basic operation data; time sequence characteristics of the power grid frequency data are extracted, and a neural network is adopted to generate a power grid frequency prediction sequence in a future time window; the power grid frequency prediction sequence is converted into a dynamic power feed-forward compensation amount, feed-forward compensation amount optimization calculation is carried out, the feed-forward compensation amount is superposed to the output end of a feedback controller, and a composite power instruction input value hydroelectric generating set is formed; and updating a neural network input sequence in each control period by adopting a rolling time domain prediction strategy, dynamically correcting a future prediction result, and realizing controlled quantity updating based on actual frequency deviation. According to the method, the compensation weight is dynamically updated by using the online adaptive algorithm, the prediction error and the system performance target are considered, and the compensation amount distribution is optimized.

The invention discloses a heavy-load train operation control method which comprises the following steps: carrying out stress analysis on each carriage in a target heavy-load train, and calculating the control force of each carriage according to the control force acting on each carriage, the coupler force between each carriage and the adjacent carriage and the basic resistance borne by each carriage; constructing a multi-mass-point longitudinal dynamic model of the target heavy-load train; parameters of the basic resistance model have uncertainty; based on the multi-particle longitudinal dynamic model, solving a non-parallel distribution compensation fuzzy control law and an additional control law to obtain an optimal guaranteed-performance composite nonlinear feedback controller, and establishing a speed tracking closed-loop control system based on the optimal guaranteed-performance composite nonlinear feedback controller; and a speed tracking closed-loop control system is adopted to adjust the control force acting on each carriage based on the current speed of each carriage and the relative displacement between each carriage and the adjacent carriage, so that the target heavy-load train runs according to the expected speed. The running efficiency and the running safety of the heavy haul train can be improved.

The invention discloses a traction-type AGV robust adaptive path tracking method considering trailer drift suppression, and belongs to the field of intelligent transportation AGV path tracking control. First, a path tracking control system of a towed AGV is modeled, where an articulation angle and an articulation angular velocity are introduced into a control system state to suppress drifting behavior of a trailer. Then, a robust adaptive path tracking control method combining feedforward control and feedback control is developed to improve tracking performance and robustness. In feed-forward control, a feed-forward controller capable of minimizing a tracking error in advance is designed. In feedback control, an H-infinity robust feedback controller based on observation is designed to weaken the influence of random disturbance. Wherein the preview distance model and the fuzzy algorithm are introduced into the feedback controller so as to improve the tracking precision and the adaptive capability of the path tracking control system. According to the invention, the tracking precision, robustness and stability of the traction-type AGV in a path tracking scene can be effectively improved.