3193 results about "Control objective" patented technology

The invention provides an intelligent regulation and control method for a three-stage constructed wetland recirculating aquaculture system, and belongs to the technical field of machine learning. The method comprises the following steps: firstly, continuously collecting water quality data and operation control data of each control unit, and constructing a multi-source heterogeneous data set under a unified time scale; then, constructing a pollution evolution trend prediction model, and capturing a dynamic evolution trend of water quality along with time and control behavior changes; then, under the guidance of a prediction result, analyzing the similarity of historical states and the sensitivity of regulation and control response, automatically identifying key control parameters which influence the water quality change of the system at present, and reasoning the dynamic adjustable boundary of the key control parameters; and finally, constructing a reinforcement learning strategy network fusing state prediction, a parameter boundary and a control target, realizing multi-target tradeoff among pollutant removal efficiency, a water quality standard-reaching rate and operation energy consumption, and outputting an efficient and steady control strategy through continuous interactive training. According to the invention, efficient, accurate and robust operation of the wetland system can be realized.

Disclosed in the present invention is an unmanned aerial vehicle formation cooperative obstacle avoidance method based on distributed model predictive control. The method comprises the following steps: establishing an unmanned aerial vehicle motion model to predict a control state of a single unmanned aerial vehicle; on the basis of the unmanned aerial vehicle motion model and control objectives of reaching a target state and maintaining formation, establishing a cost function; setting a constraint, updating the control state in a prediction time domain under the condition that the cost function is minimum, and obtaining the control state of each unmanned aerial vehicle in a subsequent period of time; and each unmanned aerial vehicle flying in the subsequent period of time on the basis of the control state, so as to realize cooperative obstacle avoidance. The unmanned aerial vehicle formation cooperative obstacle avoidance method based on distributed model predictive control disclosed in the present invention has the advantages of high stability, low operation amount, low delay and the like.

The invention discloses a quadruped robot control method and device.The method comprises the steps that quadruped robot joint angle information is obtained, and the quadruped robot joint angle information comprises hip joint adduction and abduction angles, hip joint flexion and extension angles and knee joint bending angles; calculating a rotation error vector according to the joint angle information of the quadruped robot; according to the rotation error vector, a model prediction control objective function is constructed, and the optimization objective of the model prediction control objective function is that the error between a prediction model and an expected state is minimum; according to the model prediction control objective function, quadratic programming solving processing is carried out, and a foot end force prediction value is obtained; generating a joint torque command by using a virtual force model control method; and robot control is conducted according to the foot end force predicted value and the joint torque command. The quadruped robot control method realizes quadruped robot control, improves environmental fitness and anti-rollover capability, and reduces calculation complexity and response delay. The method can be widely applied to the technical field of robot control.

The invention discloses a shield tunneling intelligent control method and system based on a ground-tunnel-machine-information-human adaptation level, and relates to the crossing field of underground engineering intelligent construction and information technology. Setting a first-level index and a second-level index; dividing the shield construction state into three levels of intelligent adaptation levels by combining the total score of the construction state with a dynamic threshold value; setting four targets of attitude intelligent control, settlement intelligent control, tunneling efficiency optimization and construction abnormity diagnosis; a machine learning prediction model is constructed, and the construction state parameters corresponding to the targets are predicted in real time; according to the shield intelligent adaptation level, the man-machine cooperation modes are divided into three classes of A level, B level and C level; and comparing actual data with a prediction result of the machine learning model, and dynamically correcting the control target parameters. Through real-time sensing of geological, mechanical and environmental multi-dimensional construction states and in combination with a dynamic weight distribution strategy, precise evaluation of the shield construction state is achieved, and meanwhile self-adaptive switching of the man-machine control right is achieved.

The invention relates to the technical field of sewage treatment, in particular to a coupling control system and method for deep denitrification of sewage, and the system comprises a real-time water quality monitoring module, a microorganism twinborn modeling module, a real-time prediction module, an intelligent decision module, an execution mechanism module and a prediction regulation and control module. Compared with the prior art that a passive feedback control strategy based on an effluent quality index is generally adopted, the hysteresis quality is high, and violent fluctuation of an inflow load cannot be coped with; according to the method, a digital twinborn body capable of reflecting the functional state of a microbial community in real time is constructed, and a control target is improved from a traditional process parameter set point to direct optimization of microbial ecological functions; according to the invention, the method achieves the fundamental crossing from the control of technological parameters to the regulation and control of microbial ecology, can carry out intervention from the root of the reaction process, enables the system to have the active health management capability, and remarkably improves the stability of the treatment efficiency and the intelligent level of coping with complex working conditions.

The invention discloses a coordinated control method and system for comprehensive energy multi-agent coordinated group control and autonomous decision making. The method comprises the following steps: establishing a relaxation strategy of an agent corresponding to a distributed power supply; the main coordinator iteratively solves to determine a global coordination signal according to the global operation data of the integrated energy system and the operation data of each agent by taking the lowest total cost, the highest system energy efficiency, the minimum carbon emission and the minimum global penalty coefficient meeting the global relaxation constraint as a relaxation global optimization target; the minimum operation cost of each intelligent agent, the minimum response deviation to a global coordination signal and the minimum deviation between an actual state and a reference state are taken as control targets; establishing an electricity price autonomous decision-making model of each agent and a response power boundary autonomous decision-making model for a global coordination signal; and based on the control target of each agent, the electricity price autonomous decision-making model and the response power boundary autonomous decision-making model, predicting to obtain a control target value of each agent, and realizing balance between a global optimization target and local autonomy.

The invention relates to the technical field of unmanned aerial vehicles, and discloses an unmanned aerial vehicle simulation method, device and equipment, a medium and a product, and the method comprises the steps: simulating and generating at least one target unmanned aerial vehicle based on target unmanned aerial vehicle parameters; environment parameter information is received, and a task scene is simulated and generated according to the environment parameter information; controlling the target unmanned aerial vehicle to execute the target task in the task scene according to the target algorithm; the algorithm is selected after a corresponding triggering operation is received in the algorithm selection interface; the algorithm interface comprises an algorithm selection control of at least one algorithm type. According to the invention, the simulation effect of the unmanned aerial vehicle is more comprehensive and reliable.

The invention belongs to the field of active steering of electric vehicles, and relates to an active four-wheel steering path tracking control method based on Nash game, which comprises the following steps: S1, establishing a two-degree-of-freedom transverse dynamic model of a vehicle; s2, designing a tire cornering stiffness correction coefficient by adopting a magic formula to correct the cornering stiffness in the prediction model in real time; s3, the Nash game is introduced into four-wheel steering control, the control target of front wheel steering is tracking precision, and the control target of rear wheel steering is transverse stability; and solving the optimal control quantity of each gamer through a distributed model prediction architecture.

The invention relates to a multi-cell control method for hydrogen production alkaline electrolytic cells based on nonlinear model predictive control, which belongs to the technical field of hydrogen production and comprises the following steps of: performing data acquisition on key positions of a hydrogen production alkaline electrolytic cell system in real time; based on the dynamically determined priority of each electrolytic cell, dynamic load distribution of each electrolytic cell is carried out, and a multi-dimensional cooperative regulation strategy is implemented to obtain a hydrogen yield target value of each electrolytic cell; constructing a nonlinear model comprising an electrolytic reaction model, a heat transfer model and an inter-tank coupling model, and performing parameter identification and verification; and designing a nonlinear model predictive control algorithm, performing discretization processing on the nonlinear model, introducing Kalman filtering to process the uncertainty of the model, taking a corresponding hydrogen yield target value reached by each electrolytic cell on the premise of meeting the constraint as a final control target, constructing an optimized target function, and performing solving to obtain an optimal control scheme. Compared with the prior art, the control precision and the system stability can be effectively improved.

The invention relates to a four-axis unmanned aerial vehicle PID parameter setting method based on a whale optimization algorithm, and belongs to the technical field of unmanned aerial vehicle control. The method aims at solving the problems that in the traditional PID parameter setting process, experience is relied on, time is consumed, and optimal parameters are difficult to obtain. According to the method, the whale optimization algorithm is introduced, and the characteristics of high global search capability and high convergence speed are utilized, so that the parameters of the four-axis unmanned aerial vehicle PID controller are automatically optimized. The method comprises the steps that firstly, a kinetic model of the four-axis unmanned aerial vehicle is established, a control target of a PID controller is determined, PID parameters serve as optimization variables, and a fitness function is defined to evaluate control performance; then, performing global search in a parameter space by using a whale optimization algorithm, and gradually optimizing PID parameters by simulating a whale predation behavior; the optimized PID parameters are applied to a flight control system of the four-axis unmanned aerial vehicle, and stable attitude, height and position control is achieved. The method has the advantages that PID parameters are automatically set through the whale optimization algorithm, the low efficiency and subjectivity of a traditional trial and error method are avoided, and the parameter setting efficiency and precision are remarkably improved; meanwhile, for an unmanned aerial vehicle control system with high nonlinearity and complexity, the WOA can adjust parameters based on actual feedback under the condition that accurate modeling of the system is not needed, and dependence on system modeling is reduced.

The invention provides a vehicle driving control method and device for a backlight scene, equipment and a medium. The method comprises the steps that multi-source information of a target vehicle is acquired in real time; performing fusion calculation on the multi-source information to obtain a current backlight risk index of the target vehicle; determining a driving assistance strategy or an automatic emergency braking strategy based on the backlight risk index; and controlling the target vehicle according to the driving assistance strategy or the automatic emergency braking strategy. According to the vehicle driving control scheme for the backlight scene, the backlight risk index is generated by fusing the multi-source information, the backlight scene is accurately judged, the corresponding driving assistance or automatic emergency braking strategy is formulated, the driving safety and reliability of the vehicle in the complex backlight environment are improved, and the driving safety of the vehicle in the complex backlight environment is improved. The problems that in the prior art, due to dependence on a single sensor in a backlight scene, the target recognition precision is low, a dynamic adaptation mechanism is lacked, and a braking strategy is difficult to pre-judge and adjust in advance are solved.

The invention provides an unmanned aerial vehicle consistency control method based on a Stackelberg-Nash game, and relates to the technical field of multi-agent consistency and game optimization control. The method comprises the following steps: establishing a motion attitude nonlinear dynamic model of each unmanned aerial vehicle in a multi-unmanned aerial vehicle system, and defining a communication network topological relation; constructing a consistency error and a performance index function; the method comprises the following steps: establishing a layered Stackelberg-Nash game mechanism with a plurality of participants; utilizing a Bellman optimality principle to construct a coupling HJB equation to solve an optimization control strategy of the leader and the follower; and constructing a single evaluation network to estimate the optimization control strategy of the leader and the follower in each execution so as to realize an optimization control target. A favorable tool is provided for analyzing a series of control problems of master-slave consistency of multiple unmanned aerial vehicles in the control field, and the reliability of a control system can be enhanced to a certain extent.

The invention discloses an automatic driving vehicle path planning method and system combined with high-precision perception, and relates to the technical field of automatic driving vehicles, and the method comprises the steps: obtaining the multi-mode real-time data of the surrounding environment of a target vehicle through a sensor module; performing fusion processing to generate a high-precision environment perception map; generating a global path and an initial local path by combining the current position and the target position of the target vehicle; dynamically optimizing the initial local path based on model predictive control to obtain a final local path; and controlling the target vehicle according to the global path and the final local path. The technical problem that in the prior art, due to the fact that environment sensing precision is insufficient, path planning is not flexible enough and dynamic obstacle effective prediction is lacked, automatic driving safety and path planning real-time performance are poor is solved, and the technical effects of improving automatic driving safety and enhancing path planning real-time performance and adaptability are achieved.

The invention discloses a phase modifier unit state monitoring and load control method and system for reactive power compensation of a power grid, belongs to the technical field of automatic control of power systems, and mainly solves the problem that service life loss is aggravated or a control target is single due to the fact that the health state of equipment is not fully considered when an existing phase modifier unit responds to reactive power requirements of the power grid. The method comprises the following steps of: calculating reactive vacancy and extracting vibration frequency band energy characteristics by acquiring voltage and frequency of a power grid as well as vibration, temperature and exciting current signals of a unit in real time, and constructing a health state index HSI in combination with self-adaptive wavelet basis selection; taking minimum equipment life loss and optimal power grid voltage stability as multiple objectives, dynamically generating a load control instruction by adopting a particle swarm algorithm, realizing weight adaptive adjustment based on HSI, and introducing an online life loss model as a constraint condition; finally, reactive power output is adjusted through an excitation system, and cooperative control of power grid stability and equipment life extension is achieved.

The invention discloses a zero common-mode voltage control method and system for two parallel converters based on single vector predictive control, and the method comprises the steps: building a prediction model and an evaluation function with parallel current, three-phase circulating current and common-mode voltage as control targets, and achieving the comprehensive control of output current and three-phase circulating current while guaranteeing the zero common-mode voltage; on the basis of the mapping relation between zero common-mode voltage and switch state combinations, 20 switch combinations with the common-mode voltage being 0 are selected, and an alternative switch combination library is formed; and a common-mode voltage penalty term considering a commutation process and a system parameter error is introduced into the evaluation function, and according to current polarity determination, alternative vectors generating common-mode voltage are rejected online, so that accurate control of zero common-mode voltage is realized. The invention provides an efficient and reliable common-mode voltage suppression scheme, and the common-mode voltage of the two parallel converters is successfully eliminated.

The invention discloses a light passenger car chassis steering stability self-adaptive control method, which comprises the following steps of: collecting multi-dimensional working condition parameters in real time, and covering 12 types of key parameters such as a steering wheel rotating angle and a wheel speed; after preprocessing and abnormity diagnosis, double models are adopted to estimate the dynamic state of the vehicle in parallel; dynamically setting a control target, and realizing personalized control in combination with driver style recognition; the control quantity is optimized through multi-mode strategy dynamic switching and steering and braking system cooperative control; and actuator dynamic compensation, scenarized self-learning and multi-stage fault handling mechanisms are introduced. According to the method, the complex working condition adaptability is improved, the response speed is controlled, the subsystem cooperation efficiency is improved, the system robustness and the long-term use performance are enhanced, and the driving safety of the light bus is effectively guaranteed.

The invention discloses a small crawler wheel wing combined type deformable land-air amphibious reconnaissance robot and a control method thereof. The robot adopts a crawler wheel wing integrated miniaturization design and comprises a control cabin, a left crawler wheel wing system and a right crawler wheel wing system, the crawler wheel wing systems are connected with the control cabin through steering engines, and a flight mode and a ground mode can be stably switched under the driving of the steering engines. In the flight mode, a flight motor of the crawler wheel wing system drives propellers to rotate at a high speed, lift force is provided, and air flight and attitude stability are achieved. In the ground mode, the crawler wheel wing system is adjusted to the ground contact position, the propellers stop working, the ground motor drives the crawler and the driving wheels through the gear set to provide advancing power, the driven wheels assist in supporting, and the stability and obstacle crossing ability in the complex terrain are enhanced. A multi-mode control method based on model predictive control is adopted for the robot, and the multi-mode control method is achieved by establishing control models of a flight mode and a ground mode, constructing a unified state-space equation and a predictive equation, designing a cost function, dynamically switching the control models and coordinating constraint conditions and control targets. And the trajectory tracking precision and the system stability of the robot in the flight mode and the ground mode are ensured.

The invention discloses a defrosting control device, a defrosting control method and a temperature regulation and control system. The defrosting control device comprises an acquisition module, an edge calculation module, a defrosting module and a control module, the defrosting module comprises a plurality of defrosting units arranged on the heat exchange unit; the acquisition module is used for acquiring air pressure difference of the heat exchange unit and temperature field distribution information of a set surface of the heat exchange unit; the edge calculation module is used for determining a critical defrosting threshold value and frost layer thickness distribution information of a set surface according to the wind pressure difference and the temperature field distribution information; the control module is used for determining a target defrosting area according to the frost layer thickness distribution information and the critical defrosting threshold value and controlling the defrosting unit corresponding to the target defrosting area to conduct defrosting. The invention provides a defrosting control device, a defrosting control method and a temperature regulation and control system, which can reduce the defrosting energy consumption, ensure the continuous work of the temperature regulation and control system where a heat exchange unit is located during defrosting, prolong the service life of the temperature regulation and control system and increase the application scene of the temperature regulation and control system.

The invention relates to the technical field of power electronic control, and discloses a voltage and current stabilization and surge suppression cooperative control method for power equipment, and the method comprises the following steps: dynamically segmenting an output current frequency band, and remodeling the output impedance characteristics of a system; predicting and controlling a hierarchical optimization control target based on a multi-time scale model; dynamically switching an energy feedback path; identifying aging parameters of the device on line and adaptively adjusting a control strategy; global stability verification and fault-tolerant protection: verifying the stability of the control system based on the Lyapunov stability theory, and triggering a protection mechanism when the magnetic flux is saturated or the aging of the device exceeds the limit. By means of dynamic impedance frequency domain segmentation, the impedance characteristic of the system is divided into a low-frequency voltage stabilization area and a high-frequency surge suppression area according to frequency bands, the contradiction that in a traditional method, it is difficult to consider steady-state precision and transient surge suppression at the same time due to the single impedance characteristic is solved, and collaborative optimization of voltage stabilization control and surge energy blocking is achieved.

The invention discloses a tray forking method and system, a storage medium and a program product, and relates to the field of general control or adjustment systems.The method comprises the steps that tray area images are collected, and tray position coordinates and cargo distribution data are obtained; carrying out gravity center calculation to obtain a cargo plane gravity center predicted value, calculating a stress compensation coefficient of a scissor fork module, and determining an initial stress value; determining motion track parameters of the robot, and generating a motion control instruction for controlling a pallet fork of the robot to move to a preset position; an initial lifting instruction is generated and used for controlling a scissor fork module of the robot to conduct lifting motion; acquiring real-time stress data of the scissor fork module, determining a horizontal attitude deviation value of the tray, and generating a lifting compensation instruction for adjusting the real-time stress data so that the target tray is adjusted to a horizontal state; and generating a truck body forward moving instruction and a module homing instruction, and controlling the target tray to be placed on the truck body. According to the invention, the tray forking and moving stability of the robot can be improved.

The invention provides a control system, method and equipment based on intelligent treatment of flotation gas. The system comprises a monitoring unit, an evaluation unit, an operation unit, an identification unit and a control unit, the evaluation unit is connected with the monitoring unit and the operation unit. The control unit is connected with the operation unit and the recognition unit. The monitoring unit is used for monitoring flotation gas information of the target area; the evaluation unit is used for evaluating the flotation gas information by adopting a preset artificial intelligence (AI) algorithm to obtain an evaluation result corresponding to the flotation gas information; the operation unit is used for determining operation information related to the exhaust fan in the target area based on the evaluation result; the recognition unit is used for collecting picture information corresponding to abnormal working conditions in the target area and determining a recognition result corresponding to the picture information by adopting a preset AI image analysis algorithm; and the control unit is used for controlling technological parameters corresponding to the flotation gas in the target area based on the operation information and the recognition result.

A combination vehicle includes a tractor including a steered wheel and a trailer towed by the tractor. A control device for the combination vehicle includes a control unit. The control unit is configured to, when a reverse operation of the combination vehicle is performed, assist a reverse operation of the trailer by causing a controlled variable to follow a target value of reverse control that is set through a specific operation by an operator. The control unit is configured to execute a process of limiting the target value and a process of limiting a time rate of change in the target value from a viewpoint of suppressing occurrence of a jackknife phenomenon.

The invention discloses a method and a system for adjusting the internal environment of a mobile laboratory cabin, particularly relates to the technical field of environment control, and aims to solve the problem that the existing environment adjusting method adopts a fixed control target and cannot adapt to differentiated environment requirements in a multi-task scene of a mobile laboratory. The method comprises the following steps: acquiring a current task identifier of a mobile laboratory, identifying a corresponding experiment task execution stage, and dynamically generating an inter-parameter collaborative constraint relation matrix based on a fuzzy inference rule base; a regulation and control demand vector is generated by collecting a multi-dimensional environmental parameter measurement value and combining a pre-stored environmental parameter expected value; calculating a regulation and control conflict risk entropy value based on the matrix and the vector, and performing risk judgment; when the risk tolerance is exceeded, a roundabout regulation and control strategy is generated as an optimization guide parameter; finally, an environment control instruction is generated in a coordinated mode according to the optimized guiding parameters and sent to an executing mechanism; the dynamic adaptation of the environmental parameter regulation and control strategy and the experiment task is realized, and the precision and reliability of multi-parameter cooperative control are improved.

The present application relates to the technical field of robot control. Provided are a robot obstacle avoidance control method and a related device. In the present application, an RMP mapping tree is constructed on the basis of individual actual spatial positions of all obstacles currently present in an operating environment where a target robot is located, such that a root node task of the RMP mapping tree corresponds to a robot joint space, and corresponding leaf node tasks comprise a position motion task and a pose motion task of a robot tail end executing an expected operation, and comprise obstacle avoidance motion tasks of a plurality of robot key parts of the robot tail end respectively performing obstacle avoidance on the obstacles; and then, geometric dynamical systems involving speed information are respectively constructed for various motion tasks, and an expected joint acceleration is solved on the basis of an RMP push-forward operation and an RMP pull-back operation, so as to control the target robot to move, thereby enabling the robot to achieve expected operation execution effects while avoiding dynamic obstacles with high agility and real-time performance.

The invention relates to the technical field of vehicle torque control, and provides a vehicle torque control method and device, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring a road slope corresponding to a road on which a target vehicle runs currently and a real-time slip rate of the current target vehicle; determining an actual road adhesion coefficient of each wheel in the target vehicle based on the road gradient; based on the actual road adhesion coefficient, determining an optimal slip rate corresponding to each wheel in the target vehicle; and under the condition that the target duration is larger than the first preset duration, the torque compensation mode is started to control the output torque of the target vehicle, and the target duration is the duration when the real-time slip rate is not smaller than a first preset slip rate threshold value. Through the method provided by the invention, the running stability of the target vehicle under the complex road condition is improved.

The invention belongs to the technical field of vacuum coating, and particularly relates to a vacuum coating machine electron gun control method and system.The control method comprises the steps that in the coating process, key real-time parameters reflecting the working state of an electron gun and the evaporation process are continuously collected and fused, and the current coating state is evaluated in real time based on the key real-time parameters; and in combination with preset coating process requirements, an electron beam control target instruction set of a next control period is dynamically generated through a built-in decision mechanism and is sent to a power controller, a focusing coil controller and a scanning coil controller of the electron gun, and the electron gun is driven to adjust the power output, the focusing state and the scanning motion of the electron gun in real time. Through accurate and stable control of the evaporation rate, material characteristic changes are effectively coped with through a strong closed loop of power and the evaporation rate; the dynamically planned scanning path can actively compensate the non-uniformity of the thermal field of the crucible, and beam spot energy distribution is optimized in combination with focusing adjustment, so that the uniformity of the thermal field is remarkably improved.

The invention discloses a cooperative control method for a heavy haul railway long and large combination train based on a coupler force closed loop in order to solve the problem that operation safety is threatened due to unstability and breakage of a coupler caused by overlarge longitudinal impact force in the traction braking process of the long and large marshalling train. According to the method, coupler force is introduced into a control system of a locomotive to form a unit train coupler force closed-loop control system in a marshalling train, and traditional locomotive control is changed into train control. According to the method, the purpose of minimizing coupler force of slave control locomotives and front locomotives in a group is achieved, a distributed cooperative control strategy is adopted for unit trains in the group, the purpose of equivalently decomposing the long and large heavy-load combined train into unit trains running independently is achieved with the fact that stress of front coupler of each slave control locomotive is almost zero. And automatic driving operation of the unit trains in the marshalling is realized. By recognizing the stress change trend of the couplers and adopting a coupler force closed-loop active control mode, the overlarge impact force of the train couplers is relieved, and the running safety of the whole heavy-load train is guaranteed.

The invention provides a satellite orbital transfer control method and device, electronic equipment and a storage medium, and relates to the technical field of satellite control. The satellite orbital transfer control method comprises the following steps: constructing a three-dimensional centralized monitoring area corresponding to a target satellite based on acquired first operation information of the target satellite; based on the three-dimensional centralized monitoring area, generating a monitoring instruction, and based on the monitoring instruction, controlling a monitoring terminal corresponding to the target satellite to perform centralized monitoring on the three-dimensional centralized monitoring area; when it is monitored that the target terminal exists in the three-dimensional centralized monitoring area, second operation information corresponding to the target terminal in a unit time period is obtained, and a control mode corresponding to the target satellite is determined based on the first operation information and the second operation information; and based on the control mode, controlling the target satellite to perform orbital transfer operation. According to the invention, the orbital transfer capability of the target satellite can be improved and the collision probability can be reduced.

The invention discloses a hydroelectric generating set speed regulation control method considering excitation coordination. The method comprises the steps that 1, system state information is collected and preprocessed; step 2, on-line identification of excitation speed regulation coupling characteristics; 3, decomposing a multi-time-scale control target; step 4, designing a self-adaptive multivariable controller; 5, working condition self-adaptive parameter optimization; step 6, intelligently inhibiting the water attack effect; 7, multi-machine cooperative reactive power optimization control is carried out; 8, optimizing and executing a control strategy in real time; the technical problems that excitation speed regulation dynamic coupling, multi-time scale response mismatch, multi-machine cooperative control and the like in a hydroelectric generating set control system cannot be comprehensively solved in the prior art are solved, and the regulation response speed and the system operation safety are improved while the frequency and voltage stability is ensured.

The invention belongs to the technical field of crude oil electric heating furnaces, and relates to a crude oil electric heating furnace control system and a crude oil electric heating furnace. Temperature feature vectors of multiple independent heating sections are collected, a dynamic weight matrix used for representing the thermal inertia unbalance degree is generated, and temperature control compensation gains are generated through real-time analysis in combination with crude oil viscosity-temperature data; performing adaptive adjustment by combining corresponding element values of the dynamic weight matrix to output a segmented power regulation instruction, preferentially calling redundant power of the main and auxiliary coils for cooperative heating, starting adjacent segment compensation heating when the main and auxiliary power is insufficient, and setting heat balance constraint and deviation monitoring termination conditions at the same time; local over-coking is avoided while the power resource utilization rate of the crude oil electric heating furnace is remarkably improved, the viscosity is rapidly converged to a steady-state range through closed-loop feedback of viscosity data after heating and iterative optimization of a regulation instruction, and the stability of long-term operation of the system and the achievement speed of a control target are remarkably improved.