163 results about "Design control" patented technology

The invention provides a heat storage heat pump system control method based on a physical information neural network, and belongs to the technical field of heat storage pump system intelligent control. Aiming at the problems that in the prior art, an algorithm is difficult to adapt to dynamic energy consumption requirements, engineering application of a model is difficult due to building space heterogeneity, high-order RC model prediction credibility is weak, engineering feasibility is poor and the like, a solution combining a physical information sequence to sequence neural network technology and a finite-state machine control strategy is provided. On the model level, a 2R2C resistance-capacitance RC model of building temperature change is established, and then a PI-Seq2seq prediction model is proposed based on the physical model. On the control flow optimization level, on the basis of an industrial and commercial time-of-use electricity price policy, an FSM control model is designed, a system state set is defined, parameters and a transfer function are input, and a control rule is constructed in combination with the working period of a building heat pump and the characteristics of a heat storage tank. And finally, energy consumption cost optimization and indoor temperature stabilization under the peak-valley electricity price are realized.

The invention discloses an air robot control method and system oriented to a complex environment, establishes a kinetic model of an air robot according to the control requirement of the air robot for executing contact operation in the complex environment, and provides a hierarchical control framework. The framework includes an outer torque estimator, an impedance-based force / trajectory tracking module, and a position controller and an attitude controller. Firstly, a generalized torque estimator is introduced, and effective estimation of external disturbance is achieved under the condition that no additional sensor is needed; secondly, the contact force tracking performance is improved while the track precision is maintained by using an impedance control module; and finally, a position controller and an attitude controller ensure rapid convergence of the position and the attitude. Theoretical analysis shows that the designed control law can ensure the stability and convergence of the system when uncertainty and external contact force exist, and an effective control method is provided for autonomous operation of the aerial robot in a complex task environment.

The invention relates to a four-rotor unmanned aerial vehicle pose control method based on a global sliding mode. The invention relates to the technical field of unmanned aerial vehicle control, and the method comprises the steps: carrying out the modeling of a dynamic model of a quad-rotor unmanned aerial vehicle, and obtaining the nonlinear state space description of the quad-rotor unmanned aerial vehicle; secondly, respectively designing global sliding mode control laws for the position subsystem and the attitude subsystem according to the nonlinear model; according to the output of a position subsystem controller, the expected acceleration is mapped into expected lift force and attitude angle by designing control distribution; and finally, constructing a nonlinear programming problem corresponding to a nonlinear model prediction controller by taking a previously designed global sliding mode control law as a contraction constraint, and solving the problem to obtain a control quantity. According to the method, the quadrotor unmanned aerial vehicle can effectively perform trajectory tracking under the conditions of output constraint and convergence guarantee, and the control precision, the response speed and the safety in the flight process are improved.

The invention discloses an aircraft active side lever force feedback control method based on feedback linearization. The method is suitable for pitch axial force feedback control and roll axial force feedback control of an aircraft active side lever. The method comprises the following steps: establishing a kinetic equation of a mechanical transmission system and a pitch axis motor or a roll axis motor, and establishing a state-space equation of an active side lever system according to the equation; designing a linear expansion observer, and estimating the thrust applied to the active side lever by the driver based on the linear expansion observer; and designing a feedback linearization control method, deducing a control law according to a state-space equation of the active side lever system, and introducing the estimated thrust applied to the active side lever by the driver into the control law to realize real-time compensation of external interference. Under the condition that the thrust of the driver cannot be measured, the thrust of the driver is obtained through the linear expansion observer, the thrust of the driver is compensated by designing the control law, and therefore the dynamic performance and the steady-state performance of the servo system are improved.

The invention provides a heavy duty gas turbine control system which comprises a signal conditioning module and a plurality of parameter control modules, and a rotating speed control module, a load control module, a temperature limit control module and an acceleration control module in the parameter control modules are all used for achieving closed-loop control according to the deviation between a set value and a corresponding observation value; the starting control module is used for acquiring a starting fuel quantity instruction through a designed control strategy; the IGV and VGVs control module obtains an IGV and VGVs angle instruction according to the turbine inlet temperature set value, the turbine outlet temperature set value and the deviation maximum value of the corresponding observation value; the fuel quantity control module obtains a total fuel quantity instruction based on a full working condition range fuel quantity control strategy; the fuel gas distribution control module is used for obtaining an opening degree instruction of each fuel valve according to the total fuel quantity instruction; the adaptability, the reliability and the usability of the control system in application scenes such as autonomous design and technical improvement are improved.

The invention discloses a self-adaptive finite time fuzzy safety control method for a flexible joint mechanical arm, which comprises the following steps that a flexible joint mechanical arm state space model influenced by spoofing attack is established, and a control signal comprises an unknown time-varying parameter and an unknown bounded attack function; introducing a Nussbaum function meeting a preset limit integral property; designing a control method based on a finite time stability principle, and ensuring that a system state converges to a bounded residual set within finite time; a fuzzy logic system is adopted to approach an unknown nonlinear function in the mechanical arm model; defining an error variable through coordinate transformation, and constructing a parameter which exponentially decays along with time; constructing a Lyapunov function containing the exponential decay parameter, and designing a virtual control function, a controller and a parameter adaptive law based on the function; and the Nussbaum function is constructed to be used for processing the unknown time-varying parameters. According to the invention, the influence of spoofing attacks on state signals can be reduced.

The invention discloses a multi-stage control method for a lower limb exoskeleton, is applied to the field of exoskeleton robots, and aims to solve the problem that the design control precision is reduced due to the uncertainty of a model in the prior art. According to the controller designed by the invention, in a high-level control layer, a human body training mode is determined by a motion intention of an operator so as to generate a reference gait track; in the middle control layer, a variable admittance controller is designed, and three training modes of human exoskeleton cooperative movement, namely a passive mode, an active mode and a passive-to-active mode, are planned. In a low-level control loop, a method with a radial basis function neural network estimation function and a fixed-time convergence controller with input dead zone compensation are provided so as to ensure that an exoskeleton joint position tracks an expected trajectory output by an admittance loop. In order to avoid the Zeno phenomenon of the designed controller, an event trigger mechanism is used to determine the execution time of sampling and transmitting signals. Finally, the effectiveness of the proposed control strategy is verified through simulation and experimental results.

The invention provides a self-adaptive fixed time tracking control method based on event triggering, which is used for solving the technical problem that a virtual control law is easy to generate singularity in the traditional backstepping method design. The method comprises the following steps: establishing a mathematical model of a non-strict feedback nonlinear system with input time delay, and introducing an auxiliary system to counteract delay influence; an error dynamic system is obtained through coordinate transformation; according to system fixed time convergence, designing a piecewise function, introducing a backstepping method to design a controller and an adaptive law, using an RBFNN to approach an unknown function therein, designing a virtual control signal corresponding to each error signal, and obtaining an actual controller and an adaptive law; according to the actual self-adaptive controller, event triggering conditions are designed, when the event triggering moment is reached, the event triggering conditions containing input are triggered, and information transmission and response are carried out. An event triggering mechanism is designed, the number of times of control instruction transmission is reduced, communication resources are saved, and rapid convergence and safe operation of the system state are achieved.

The invention discloses an engineering system fault-tolerant tracking control method based on data driving, and belongs to the technical field of engineering control methods. Comprising the following steps: S1, establishing an engineering system equivalence model under a fault, and defining a performance index function and a corresponding value function so as to convert an optimal control problem into a zero-sum game problem; s2, aiming at the problem that the state of the engineering system is unmeasurable, reconstructing the state by utilizing historical input and output data so as to design and solve an optimal control strategy; and S3, introducing and defining a Q function, designing a controller gain and a disturbance gain # imgabs0 #, and optimizing the # imgabs1 # in combination with a designed model-free non-strategy Q-learning output feedback algorithm to obtain an optimal controller. Through an injection molding industrial process and a depth control simulation experiment of an autonomous underwater vehicle (AUV), convergence of the algorithm and an excellent tracking control effect of a designed controller are verified.

The invention relates to the technical field of nuclear power plant system design, in particular to a nuclear power system design drawing generation method and device, electronic equipment and a storage medium. According to the nuclear power system design drawing generation method provided by the embodiment of the invention, design control demand data of a target nuclear power control system is acquired; performing control key point analysis based on the design control demand data to obtain target control key point data; performing schematic diagram construction on the target nuclear power control system according to the target control key point data to obtain a target system schematic diagram; in response to a condition that the target system schematic diagram meets a system principle verification condition, performing application diagram construction on the target nuclear power control system according to the target system schematic diagram and the target control key point data to obtain a target system application diagram; and in response to the condition that the target system schematic diagram meets the system application verification condition, determining the target system application diagram as a target system design diagram of the target nuclear power control system. Therefore, the efficiency of generating the design drawing of the control system of the nuclear power plant can be improved.

The present invention discloses a control method and system for modular design of a power distribution unit of an intelligent power distribution cabinet, belonging to the technical field of design control; an environment perception functional area, an intelligent control functional area and a power regulation functional area are set for the power distribution unit of the intelligent power distribution cabinet; the environment perception functional area acquires temperature data and humidity data; the intelligent control functional area controls the operation of components in the intelligent power distribution cabinet and adjusts the optimal temperature and humidity range; calculates the power generated by the components during operation; calculates the comprehensive current data and comprehensive voltage data of the components; based on the comprehensive current data and comprehensive voltage data, calculates the comprehensive power and operation influence degree of the components; preset thresholds, analyzes and outputs early warnings to the intelligent control functional area. The present invention optimizes the energy utilization efficiency, improves the safety and reliability of the system through dynamic regulation and intelligent early warning, and at the same time has good scalability and adaptability, and can meet the requirements of modern intelligent power systems.

The invention provides a sewage treatment process adaptive neural network control method with time-varying asymmetric constraints, is used for a sewage treatment process with unknown parameters, and belongs to the technical field of urban sewage treatment process intelligent control. A controller is designed by adopting a self-adaptive control method, and the concentration of dissolved oxygen and the concentration of nitrate nitrogen in the sewage treatment process are accurately controlled. Firstly, due to the fact that the fuzzy neural network has excellent robustness, unknown dynamics appearing in a sewage treatment plant can be effectively approached. Secondly, control input is designed by constructing a time-varying asymmetric obstacle type Lyapunov function, and a fault-tolerant control method is designed in consideration of an actuator fault condition. And finally, performing a simulation experiment by using the reference simulation model 1, and verifying the effectiveness of the proposed method by a simulation result.

A spacecraft attitude preset performance control method based on an improved preset finite time function comprises the following steps: step 1, determining a control object and a control target according to a motion law of a spacecraft: designing a control law so that the control object and the control target are controlled under the influence of saturation factors of an execution mechanism; a spacecraft system attitude quaternion error vector part qev and an angular velocity error We of a spacecraft body coordinate system track an expected signal; 2, constructing a class sliding mode variable S, a self-adaptive boundary preset finite time function and auxiliary variables e and v; 3, designing a control law to enable the variable S to move in an envelope formed by a preset finite time function # imgabs0 #; and 4, checking and improving the performance of the preset finite time controller. According to the method, the problem of singularity easily occurring when an existing preset finite time control method faces internal and external interference and the problem that the angular velocity is too large in the large-angle maneuvering process are solved, meanwhile, the actual physical limitation of an executing mechanism is considered, and it can be guaranteed that higher reliability is obtained.

The invention relates to a mechanical arm actuator fault tolerance control method based on sliding mode control and a neural network, and belongs to the field of industrial robots. The method comprises the steps that modeling is conducted on the fault condition of a mechanical arm actuator, and a fault model is established; defining a joint angle tracking error, designing a sliding mode controller, and establishing a sliding mode surface of the sliding mode controller as linear sliding; designing a mechanical arm dynamic form according to the linear sliding surface and the fault model; estimating a total dynamic item by adopting an RBFNN neural network to obtain an estimated value of a system dynamic item, and taking the estimated value as an output quantity of the RBFNN neural network; designing a control law; calculating and generating a corresponding control input quantity according to a control law by adaptively updating a fault matrix of the weight matrix; and the mechanical arm actuator controls the mechanical arm according to the control input quantity so as to achieve fault compensation. According to the method, high-precision trajectory tracking is achieved under the condition that dynamics and actuator faults are unknown, and an accurate fault model or a fault detection system is not needed.

The invention discloses a long flexible blade reduced scale model design method suitable for a large fan wind tunnel experiment. The method comprises the following steps: selecting a reasonable similarity criterion, selecting a section airfoil of a model blade, optimizing the distribution of chord length and torsion angle in the length direction of the blade, and optimizing a model rotor variable pitch control strategy; the design objectives that the thrust coefficient of the reduced-scale model rotor in the experimental wind speed range is equal to that of the original-size fan rotor in the corresponding original-size wind speed range, and the first-order inherent frequency in the flapping and shimmy directions of the blades of the reduced-scale model is equal to that of the original-size blades are achieved, and the long flexible blade reduced-scale model is provided for a large-scale fan wind tunnel experiment. According to the method, the first-order inherent frequency of the flapping and shimmy directions of the model blade and the blade of the original size is equal, the thrust coefficients are equal under multiple working conditions, the wind tunnel experiment similarity criterion is met, different airfoil choices are appointed for different design control sections, and the method has high optimization solution efficiency.

The invention discloses a fault compensation and H-infinity fault-tolerant tracking control method for an autonomous underwater vehicle, and belongs to the technical field of engineering control methods. Comprising the following steps: S1, aiming at actuator faults, sensor faults and external disturbance problems in vertical plane motion of an autonomous underwater vehicle, introducing a depth variable and establishing a high-order all-drive fault model; s2, designing an intermediate estimator based on a high-order all-drive model, and realizing estimation of a system state and a fault; and S3, designing a controller based on the high-order all-drive model, solving a game Riccati equation by using a Minmax method, obtaining an optimal control strategy, and realizing fault compensation and external disturbance suppression. The effectiveness of the method and the excellent tracking control effect of the designed controller are verified through a depth control simulation experiment of the autonomous underwater vehicle.

The invention provides a design and application method of a sliding-mode deadbeat reaching law, and relates to the technical field of electrical engineering, and the method comprises the steps: designing a sliding-mode deadbeat reaching law SMDRL, designing a control strategy through a deadbeat control principle, defining a state change law on a sliding-mode surface through a sign function, and achieving the design of the sliding-mode deadbeat reaching law SMDRL. It is ensured that the system state converges to the sliding mode surface at the fastest speed in a control period; an improved sliding mode deadbeat reaching law ISMDRL is designed, a traditional sign function is replaced with a hyperbolic tangent function, and parameters of the hyperbolic tangent function are adjusted according to the system state; the SMDRL and the ISMDRL are applied to a speed driving system of a permanent magnet synchronous motor (PMSM), and the speed driving system comprises a PMSM mathematical model, a sliding mode speed controller with a speed disturbance observer and model prediction current control. The SMDRL is introduced from the traditional sliding mode reaching law for the first time through theoretical derivation, the convergence time of the SMDRL is the shortest, and the SMDRL is applied to a permanent magnet synchronous motor speed driving system.

The invention provides a plasma virtual control surface and control mechanism control distribution method for reentry flight of a high-speed aircraft. The method comprises the following steps: firstly, determining that the aircraft enters a reentry flight stage; secondly, the needed torque is calculated according to an attitude controller; then designing control distribution models of a plasma active flow control system, a pneumatic control surface control mechanism and an RCS backstepping control system based on a depth deterministic strategy gradient reinforcement learning algorithm; and the high-speed aircraft completes reentry flight based on the control distribution parameters obtained by the control distribution model. Auxiliary control is achieved through the plasma jet, and a new way is provided for accurate control over the aircraft. According to the method, control means can be reasonably distributed according to the early stage, the middle stage and the later stage of reentry flight, and relevant parameters of all control systems are determined. The reinforcement learning algorithm is used for processing the nonlinear characteristics of the input power and control output of the plasma exciter and the nonlinearity and uncertainty of aerodynamic characteristics in an attitude control model, the stability of a control system can be improved, and the method has a good application prospect.

This invention provides a low-computational-complexity, pre-set performance-tolerant control method for steer-by-wire systems. The control method includes: determining the control objective based on a pre-set performance control method; subsequently designing a new pre-set performance function and error transformation function; designing virtual control laws and control laws in the controller using a robust control method; establishing a dynamic model of the steer-by-wire system based on system dynamics; establishing a dead-zone model and a fault model based on the impact of dead zones and faults in the vehicle actuators on the control performance of the steer-by-wire system; simultaneously obtaining the input nonlinear model of the steer-by-wire system; subsequently establishing a state-space model of the steer-by-wire system; and finally, verifying the controller's control effect and optimizing its internal parameters using the state-space model. This invention considers fault and dead-zone issues, improving the robustness of the controller; and considers the limited computational resources of the vehicle, with a simple controller structure that improves the overall computational efficiency of the vehicle.

The invention discloses a carrier rocket test-launch process refined information management and control system based on a handheld terminal. The system comprises a decision-making area, a design management and control area and a test-launch execution area. From the perspective of converting files into data information transmission, a new process management and control design method and concept are adopted, carrier rocket launching site process information management and control design is carried out, a hierarchical management and control framework of different professional systems is established through a modularization method according to a launching site process operation mode, an information transmission management mode in refined management and control is constructed, and the management and control efficiency is improved. Unified management and template process scheme design in process management and control are realized, and the design scheme is implemented in a handheld terminal. Flow design work and result and state check and confirmation are completed among the stages through a handheld terminal, refined management and control of work flow information of a carrier rocket in a launching site are achieved, the test launch execution efficiency and reliability of a carrier rocket launching task are improved, and high-quality launch task completion is achieved.

The invention discloses a forklift path tracking control method based on MPC and ARC cooperation, and belongs to the technical field of industrial vehicle automatic control. Comprising the steps that an upper-layer MPC is designed based on a forklift kinematics model, and an expected steering angle and an expected speed instruction are obtained through solving; a lower-layer ARC is designed based on the pump control steering system dynamics model to track an expected steering angle, and a PID controller is designed to track an expected speed; a time delay compensation mechanism is integrated in the upper-layer MPC, and a high-frequency execution strategy is adopted. According to the method, interference of the steering system is accurately observed and compensated, parameter uncertainty is adaptively processed through parameters, nonlinear uncertainty is processed through robust items, a time delay compensation mechanism is integrated in MPC, all control rates are display expressions, online solution is not needed, and the method is suitable for large-scale popularization and application. The influence of steering resistance dramatic change, external interference, unmodeled dynamics and system time delay on the control precision is effectively reduced, and high-precision and low-time-delay path tracking performance is achieved.

This invention relates to an AUV close-range docking method based on sliding mode adaptive control under ocean current interference. The controller design eliminates decoupling of the AUV's motion and incorporates an integral term in the sliding mode adaptive controller design, employing Integral Sliding Mode Adaptive Control (ISMAC) to minimize chattering during the AUV's approach motion. Finally, in designing the control parameters, overshoot is minimized at the expense of settling time to ensure successful docking. Furthermore, the estimation of ocean current velocity gives the system a certain degree of anti-interference capability, demonstrating its robustness.

The application belongs to the technical field of cold cathode trigger tube, and discloses a cold cathode trigger tube circuit simulation SPICE design method, which comprises the following steps: main gap channel design; trigger gap channel design; control module design; cold cathode trigger tube characteristic parameter verification and problem analysis; cold cathode trigger tube SPICE model improvement based on gas discharge theory and characteristic parameter verification; improved cold cathode trigger tube application simulation and result analysis. The cold cathode trigger tube SPICE model provided by the application meets the functions of the modern cold cathode trigger tube, and is verified by simulation; and different parameters of the model can be modified to meet the requirements of different scenes.

The present invention provides a generalized improved active disturbance rejection control method based on model assistance and Smith predictor-like, belonging to the field of automatic control. The method includes the following steps: describing a class of actual industrial systems by using a high-order inertial system; designing a Smith predictor-like algorithm based on the input and output of the high-order inertial system; designing an extended state observer algorithm based on model assistance with the output of the obtained Smith predictor-like algorithm and the input of the high-order inertial system; designing a control law with the output of the obtained extended state observer algorithm and the system set value; obtaining a new input value of the high-order inertial system, and adjusting and controlling the output of the high-order inertial system according to this value. This method can make full use of the known model information, retain the characteristics of simple structure and easy parameter tuning of the active disturbance rejection control, enable the closed-loop system to better balance the tracking ability and anti-interference ability, and make the closed-loop system have strong robustness.

This invention discloses an adaptive robust brake-by-wire method and system, relating to the field of vehicle brake-by-wire technology. The method comprises the following steps: S1, establishing a multi-coupled dynamic mathematical model of the brake-by-wire system and determining the system state variables and control inputs; S2, online observation and approximation of the system's hydraulic coupling disturbances, mechanical friction disturbances, and external road surface disturbances; S3, designing a hierarchical adaptive robust control based on backstepping sliding mode control technology and combined with observations from a multi-disturbance observer; S4, adjusting the gain coefficient of the sliding mode control online; S5, verifying the asymptotic stability of the entire control system; and S6, converting the designed control law into an electrical signal and inputting it to the actuator of the brake-by-wire system. This invention achieves precise, rapid, and stable control of braking pressure under complex operating conditions, improving the robustness and adaptability of the brake-by-wire system.

The invention discloses a management optimization system based on Internet of Things, which comprises a design management module, an analysis control module and a storage feedback module, and is characterized in that the design management module is in network connection with the analysis control module, and the analysis control module is in network connection with the storage feedback module; the design management module is used for carrying out design control management on an Internet of Things model, the analysis control module is used for carrying out security optimization management analysis on the Internet of Things, and the storage feedback module is used for carrying out storage feedback processing on Internet of Things data information. The design management module comprises a model design module, a registration management module and an aggregation processing module, the model design module is in network connection with the registration management module, the registration management module is in network connection with the aggregation processing module, and the model design module is used for performing model design management of the Internet of Things. The system has the characteristics of high safety and intelligent analysis and processing.

The invention relates to a self-adaptive containment controller design method and a related device, and belongs to the technical field of artificial intelligence theoretical foundation.The self-adaptive containment controller design method comprises the steps that an initial driving system and an initial response system of a time-delay inertial memristive neural network with a reaction-diffusion term are constructed; the initial response system comprises a controller to be designed; according to a differential inclusion theory, processing orders of the initial driving system and the initial response system by adopting a variable transformation method to obtain a target driving system and a target response system, and calculating a synchronization error; and designing the controller to be designed based on the synchronization error to obtain a self-adaptive containment controller of the time-delay inertial memristor neural network with a reaction-diffusion term, and controlling the target driving system and the target response system to be synchronized by the self-adaptive containment controller. According to the invention, the driving system and the response system of the time-delay inertial memristor neural network with the reaction-diffusion term can be synchronized.

The invention discloses a buoy-unmanned aerial vehicle cooperative fault-tolerant docking control method based on event-triggered communication, and belongs to the field of unmanned aerial vehicle navigation, guidance and control. The method comprises the following steps: firstly, establishing a buoy-unmanned aerial vehicle affine nonlinear model considering the fault influence of an execution mechanism; then, a communication mechanism based on an event triggering strategy is designed, and in the collaborative docking process, aperiodic information interaction is carried out between the buoy and the unmanned aerial vehicle through the event triggering mechanism; then, based on a backstepping control theory, a controller is designed for the position, track, attitude and angular velocity loop of the buoy-unmanned aerial vehicle and the velocity loop of the unmanned aerial vehicle, and based on an observation-compensation idea, a lumped nonlinear item containing airflow disturbance and execution mechanism fault information is estimated and compensated; and finally, realizing cooperative fault-tolerant docking of the buoy and the unmanned aerial vehicle through the controller. According to the method, the accurate cooperative docking of the unmanned aerial vehicle and the buoy can still be realized under the conditions of limited communication resources, execution mechanism faults and complex airflow disturbance.

The invention provides an angular velocity measurement-free under-actuated spacecraft attitude hybrid finite time control method based on a layered sliding mode, and the method comprises the steps: employing a w-z parameter kinematic model suitable for an incomplete system, decoupling an under-actuated axis from the other two axes, and carrying out the deduction to obtain a south-north pole projection switching relation of w1 and w2, and a switching kinematic model; an improved self-adaptive second-order sliding mode observer is designed for the situation that the spacecraft has no angular velocity measurement, and anti-unwinding control of the spacecraft is achieved through hybrid control and a lagging strategy. The finite time stability of the designed control law is proved through the finite time convergence theorem and the Lyapunov theorem, and the effectiveness and superiority of the designed control law are verified through numerical simulation.

The invention discloses an active control system with a self-adaptive control strategy and a working method thereof. The active control system is characterized by comprising a vibration noise active control system and a control strategy incremental learning system, the control strategy incremental learning system comprises a noise source monitoring and evaluation module, a transmission path monitoring and evaluation module, a response surface control effect evaluation module, a control effect comprehensive evaluation module and a control strategy optimization design module; wherein the vibration noise active control system can realize a function of implementing control according to a certain strategy; the control strategy incremental learning system has the functions of matching and designing a control strategy according to the working condition information and feeding back the control strategy to the control system.