59results about How to "Realize self-tuning" patented technology

The invention discloses a method for automatically adjusting speed loop control parameters of an alternating-current servo system based on inertia identification, which comprises the following steps: firstly, a current loop and a servo motor are used as generalized objects, and estimated values of the servo motor and the rotary inertia loaded on the servo motor are obtained by the inertia identification based on a disturbance torque observer; and then a pole collocation method is adopted to adjust proportion parameters and integral parameters of a speed loop proportion integration differentiation (PID) controller automatically. In method for automatically adjusting the speed loop control parameters of the alternating-current servo system based on inertia identification provided by the invention, by combining the inertia identification algorithm based on the disturbance torque observer with the characteristics of an alternating-current servo system, auto-adjustment of the speed loop PID parameters for the alternating-current servo system can be realized under different rotary inertias. Engineers do not need to set and adjust the controller parameters manually according to the experience and the system can automatically carry out the auto-adjustment of the speed loop parameters. Compared with the prior art, the method for automatically adjusting the speed loop control parametersof the alternating-current servo system based on inertia identification is simple in design principle, and has the advantages of good adaptability under the condition that the inertia change of the external load equipment is obvious, and the like.

The invention discloses an implementing mechanism of a vehicle electronic parking brake system. The invention comprises a transmission device and a brake clipping caliper assembly. After the output of the direct current motor in the transmission device is performed with speed reduction and torque increase via a synchronization belt transmission device and a involute few tooth difference planetary transmission device, the rotation motion is transferred into a straight line motion through a sliding helical transmission mechanism, and a braking disc is braked through the method that a piston and a braking block assembly are pushed by a screw sleeve. The circumferential freedom degree of the piston is limited by the braking block assembly, and the circumferential and the racial freedom degrees of the screw sleeve are respectively limited by a piston non-round hole and a blocking ring. The screw sleeve and a screw rod adopt self locking thread matching, to guarantee the parking braking to be secure and reliable. Compared with the implementing mechanism of the traditional vehicle rear wheel parking braking system, the invention has the advantages that the driving cab space is saved, the labor intensity of the driver is reduced, the parting braking is more secure and reliable, and the invention is convenient for adopting intelligent control and integrating other functions.

The invention discloses a PDFF-based AC servo driver control parameter self-tuning method. Firstly, current and speed signals required for identifying an AC servo system model are acquired; secondly, according to the acquired signals, a speed loop controlled object model of a permanent magnet synchronous motor AC servo driving system is identified and parameters of the model are identified; and finally, according to the parameters and performance indexes of the model, searching optimization tuning is performed on control parameters of a servo driver so that the optimal control parameter is acquired. According to the self-tuning method, a PDFF controller is utilized to substitute a conventional PI controller on a speed loop of the servo driver and the parameters of the controller are automatically tuned. The model of the controlled object is identified by the self-tuning method by utilizing a recursion least square method. Then according to the feasible performance indexes, searching optimization is performed on the parameters of the controller by utilizing a mode searching algorithm, and the optimal control parameter is obtained so that the servo driving system can be great in anti-disturbance capability, control precision and robustness.

The invention provides a quadrotor aircraft and a control method thereof. The quadrotor aircraft includes a body and an aircraft control module, and a navigation and inertial measurement module, a power module, a communication module and a motor drive module separately connected with the aircraft control module. The main controller module performs synthesis calculation of real-time flight attitude information and control information of the communication module fed back by the navigation and inertia measurement module to output motor control signals to control the motor drive module. The quadrotor aircraft of the invention can automatically adapt to changes of the external environment to modulate flight parameters to reach a predetermined control effect. In the control method, the flight controller module adopts a nerve-based fuzzy self-tuning PID control scheme to calculate a practical output variable to improve robustness of flight of the aircraft.

The invention discloses a fast self-learning improved ADRC control method for a non-linear system, which comprises the following steps: S1, creating an active disturbance rejection controller (ADRC) which includes a tracking differentiator (TD) part, an extended state observer (ESO) part, a non-linear state error feedback (NLSEF) part and a disturbance compensation part, wherein S1 includes S11, establishing a tracking differentiator (TD) control model, S12, establishing an extended state observer (ESO) control model, S13, establishing a non-linear state error feedback (NLSEF) control model, and S14, establishing a disturbance compensation control model; S2, creating a self-learning active disturbance rejection controller (SADRC): applying a self-learning method to the non-linear state error feedback (NLSEF) control model to establish a self-learning non-linear active disturbance rejection control system model; and S3, creating a fast self-learning active disturbance rejection controller (FSADRC): designing a learning rate oriented adaptive mechanism by using an additional momentum term method and establishing a fast self-learning model based on dynamic adaptive learning rate.

The invention relates to a wind power variable-pitch multi-variable fuzzy neural network PID control method. The control method includes the following steps that a fuzzy parameter setting module is used for presetting the weight of a PID neural network module; the error between a rotating speed reference value and the actual rotating speed output of a wind driven generator is calculated through a PID calculation module to obtain a reference output quantity of torque of the wind driven generator; the error between the power output value and the power reference value of the wind driven generator and the error change rate are set through the fuzzy parameter setting module to obtain a presetting parameter of the weight of the PID neural network module; through a negative gradient algorithm with a momentum factor, the weight of the PID neural network module is trained, and the reference value output of torque and the reference value output of the pitch angle of the wind driven generator are adjusted. The output power of the wind driven generator can be stabilized nearby a rated valve, and safety of a fan is ensured.

The invention provides a multi-target electric energy quality comprehensive control and optimization device which comprises a control part and a main circuit part, wherein the control part comprises a detection functional module, a multi-target electric energy quality control and optimization controller and a man-machine interface, the main circuit part comprises a passive LC main circuit and an active VSI main circuit, the detection functional module is used for detecting and analyzing electric energy quality indexes of a load, a power grid and the multi-target electric energy quality comprehensive control and optimization device, and the multi-target electric energy quality control and optimization controller controls the device to conduct evaluation and analysis on the priorities of electric energy quality control targets and an optimal control strategy at the current moment within the range of security capacity in a unified and coordinated mode and sends out a control command to control the main circuits to conduct electric energy quality control and optimization in a unified and coordinated mode. The device is high in capacity and easy to expand, and capable of solving the electric energy quality problems such as voltage deviation, voltage fluctuation and flickering, three-phase imbalance, harmonic waves and low power factors to a certain extent.

The present invention relates to a control method of a parameter self-tuning motor controller, and is a motor control system method of realizing the high-performance control of three closed loops (a current loop, a speed loop and a position loop). The control method of the parameter self-tuning motor controller of the present invention is based on the DSP design, has the strong digital operation and motor control capability, and can be widely used in the industry fields, such as the intelligent wheelchair control, the unmanned mower, the industrial automation, the National defence aviation, etc. Meanwhile, a DSP-based mobile motion controller parameter tuning method is developed, so that a motion controller speed and position controller PID parameter self-tuning practical technology is realized.

The invention provides a quad-rotor unmanned aerial vehicle and a control method thereof. The quad-rotor unmanned aerial vehicle comprises a body and a main controller module and further comprises a navigation module, a sensor module, a communication module and a motor control module which are respectively connected with the main controller module, wherein the main controller module is used for comprehensively calculating the real-time flight attitude information fed back by the sensor module and the navigation module and the control information of the communication module and then outputting a motor control signal to control the motor control module. The quad-rotor unmanned aerial vehicle is advantaged in that automatic adaptation to change of the external environment can be realized to modulate flight parameters to realize the pre-determined control effect. According to the control method, the main controller module employs a control scheme combining a back-propagation artificial neural network with inertia term (BPNNI) neural network and based on weight adjustment with proportional integral derivative (PID) control to calculate an actual output control variable.

The invention discloses a method for optimizing PID control four-rotor aircraft flight through a crowd search algorithm. A four-rotor aircraft is controlled through a control method for optimizing thePID control parameter based on the crowd search algorithm, so that the anti-interference capability of the aircraft is enhanced, the robustness of the aircraft is improved, and the flight attitude ofthe aircraft can be self-adjusted in real time when the aircraft is subjected to external interference.

The present invention adopts single-order plus dead-time model; said upper computer controlling output panel control board key to make systems operation on ' identifying stage ', at this point, the relay identifying link switched into closed loop system; under action of relay link, after beginning systems operation, at short notice establishing limit loop; according to real-time measurement to relay output each parameter and biasing relay feed-back identifying formulae to calculate out system identifying three parameters: K, Theta and Pi, and storing in RAM. According to identified model parameter, system calculates each parameter of novel internal mold controller, computational result stored in RAM memory unit, the obtained model and internal mold controller parameter loading in each link in real production process. The present invention realizes the self calibration of digit internal mold controller, reducing hardware cost and raising systematical mobility, reliability and accuracy.

The invention discloses a PSO-PID algorithm based intelligent control method of an automatic gas control valve. The automatic gas control valve is taken as a research object, characteristics of a PID control system is taken into full consideration, and a transfer function model of a controlled object is established; meanwhile, an artificial intelligence technology is introduced, PID parameter optimal solutions are searched by an improved particle swarm algorithm with converging factors, and gas flow is automatically controlled. The PSO-PID algorithm based intelligent control method has the advantages that the shortcomings about manual parameter adjustment on a traditional PID gas control valve are overcome, and self-adjusting of PID parameters is realized; the intelligent control method is short in consumed time, high in precision and adaptive capability, good in applicability and the like, and has a promising application prospect and high business value.

The invention relates to a gas turbine fuel pressure control method and a gas turbine fuel pressure control system. The method comprises the following steps: S1. comparing a pressure reference value with a pressure measured value to obtain a pressure error, and carrying out differential operation on the pressure error to obtain a change rate of the error; S2. carrying out blurring operation on the error and the change rate of the error to obtain a PID parameter variation; S3. correcting an original PID parameter value according to the PID parameter variation to obtain a corrected PID parameter value; S4. carrying out PID operation according to the corrected PID parameter value to obtain target valve opening; and S5. regulating the opening degree of a speed ratio valve according to the target valve opening and actual valve opening. By combining blurring control with PID, the adaptability and the robustness of pressure control are improved, the parameter self-tuning is achieved, and when control parameters in a gas turbine are changed, the pressure of the gas turbine still can be regulated accurately, so that a good control effect can be obtained.

The invention discloses a material transfer device reinforcement learning control method based on state and disturbance estimation. The method comprises the steps that firstly, a control model of a material transfer device electro-hydraulic servo system is established; then, a novel nonlinear extended state observer is adopted to estimate the unknown state and equivalent disturbance of the hydraulic servo system, and the theoretical estimation error of the nonlinear extended state observer is zero; on the basis of the state and equivalent disturbance estimation, a sliding mode controller is designed to realize rapid and high-precision control of the hydraulic servo system; finally, a reinforcement learning method is adopted, online self-adaptive learning is conducted on sliding mode controller parameters through system self-adaptive learning, and the control performance of the hydraulic servo system is improved. According to the invention, other states and disturbance information can be obtained according to the position information of the hydraulic servo system; the sliding mode controller parameter self-tuning method can realize control of sliding mode controller parameter self-tuning through a reinforcement learning method, a large number of manual experiments for tuning are not needed, the workload is reduced and the control precision is improved.

The invention discloses an incubation room temperature control method based on cat group optimization and immune fuzzy PID, the temperature of an incubation room serves as a controlled object, a temperature physical model of the incubation room is established through a transfer function, a control rule table, a fuzzy theory domain, a fuzzy language value and a subordinating degree function of a fuzzy ID controller algorithm are designed to realize setting of an integral coefficient and a differential coefficient; a fuzzy reasoning is used for approximating the inhibition amount of cells in animmune algorithm, an immune control rule is determined, an immune control rule, a fuzzy theory domain, a fuzzy language value and a subordinating degree function of an immune P controller algorithm are designed to realize setting of a proportion coefficient; a cat group optimization algorithm is used for intelligent optimization of values of a quantification factor a scale factor of the immune P controller algorithm to determine optimal values of the quantization factor and the scale factor; the temperature of the incubation room can be accurately controlled, the incubation room temperature control method has good dynamic and static performance, is small in overshoot, and fast in adjusting time, and the self-setting of PID parameters is realized quickly and efficiently.

The invention discloses an intelligent potted plant housekeeper control system. The characteristics lie in that the housekeeper control system is composed of a potted plant housekeeper control system parameter adjustment platform and an intelligent controller-PID cascade soil moisture intelligent control system. The intelligent potted plant housekeeper control system effectively solves defects of existing potted plant cultivation, the fast response, the control accuracy and the robustness of the coil moisture of a potted plant growing environment are improved through designing closed-loop control of the intelligent controller-PID cascade soil moisture intelligent control system in the intelligent potted plant housekeeper control system, and the soil moisture is enabled to reach a system set value quickly to meet the demands of potted plants for water in each growth stage.

The invention provides a direction adjustment control system for a horizontal drilling machine. The direction adjustment control system comprises a positioning measurement system, a fuzzy controller,a PID (Proportion Integration Differentiation) controller and direction adjustment oil cylinders which are arranged on the drilling machine. The invention also provides a direction adjustment controlmethod for the horizontal drilling machine. The actual posture of the drilling machine is compared with the expected posture to obtain the real-time vertical deviation distance L and the deviation angle theta; deviation parameters and the rate of change thereof are input into the fuzzy controller; parameters KP, KID and KD in the PID controller are obtained by selecting appropriate fuzzy control rules and calculating; the PID controller sends out an action signal to the direction adjustment oil cylinders according to the PID parameters; and the direction adjustment of the drilling machine in the vertical or horizontal direction is realized through the cooperation of the action strokes between the different direction adjustment oil cylinders to ensure that the drilling machine advances according to the predetermined route. According to the direction adjustment control system and method, the fuzzy controller is introduced, and different direction adjustment strategies are adopted according to the magnitude of the deviation, so that the fast and high precise direction adjustment of the drilling machine is realized.

The invention relates to a non-axisymmetric rotary tungsten electrode GTAW and pulse laser composite welding method, and belongs to the technical field of GTAW welding. A based welding system comprises a pulse laser system, a welding gun system and a wire feeding device. The method comprises the following steps: providing pulse laser by the pulse laser system, arranging a laser unit between the wire feeding device and a welding gun, periodically providing pulse laser to irradiate a welding wire by matching with rotation of a non-axisymmetric tungsten electrode. The problems such as uneven smelting for non-axisymmetric rotary electric-arc welding wires are solved, thermal input of welding is reduced, quality of welding seams is improved, and deposition efficiency is remarkably improved.

The invention discloses an ECAS system self-adaptive control method for automobile rollover prevention. The ECAS system self-adaptive control method for automobile rollover prevention comprises the steps of firstly, collecting offline data, and erecting and training an improved door control circulation neural network for predicating an automobile rollover time; secondly, collecting automobile running state data according to a certain sampling period and carrying out filtering processing on the automobile running state data; thirdly, using the pre-trained improved door control circulation neural network to perform automobile rollover time predication according to a certain updating period so as to update a proportion coefficient of a self-adaptive PD controller; fourthly, calculating an automobile transverse load transfer ratio according to a certain control period and obtaining a deviation between the automobile transverse load transfer ratio and a set value, and inputting the deviation into the self-adaptive PD controller to perform control output; and fifthly, enabling an automobile ECAS system electromagnetic valve to adjust the height of an airbag according to the output of theself-adaptive PD controller. According to the ECAS system self-adaptive control method for automobile rollover prevention, models and parameters can be self-adjusted to achieve a better anti-rollovereffect; and meanwhile, the ECAS system self-adaptive control method for automobile rollover prevention is suitable for multiple automobile models so as to reduce workloads of test engineers; and therefore, the efficiency of loading the ECAS system on the automobile is enhanced.

The invention relates to a permanent magnet direct drive wind turbine generator system control method based on neural network direct torque control, and belongs to the technical field of electrical engineering. According to the method, a neural network direct torque control strategy is adopted, a stator flux linkage neural network is trained offline to approach a relation curve of a stator flux linkage reference value and the electromagnetic torque, variable stator flux linkage reference value control is achieved, and a stator current d-axis component ids of a permanent magnet direct drive type wind driven generator is controlled to be zero; and a stator voltage calculation formula of the permanent magnet direct drive type wind driven generator is discretized, reference values u * s alpha and u * s beta of alpha-axis and beta-axis components of the stator voltage are obtained through calculation, the reference values are modulated through an SVPWM module to generate driving signals to drive a power switch tube of a machine side converter, and the permanent magnet direct drive type wind driven generator is controlled to work. Generator stator side current harmonic distortion and machine side converter energy consumption can be reduced, and it is ensured that the performance of the whole wind turbine generator system is optimal.

The invention discloses a self-adjustable servo type service drum brake with parking function. A parking brake device is additionally arranged on a self-adjustable servo type drum brake assembly, according to the parking brake device, a parking pull arm is hinged to a through hole formed in the upper part of a rear tendon of a rear brake shoe assembly through a pull arm pin, and is fixed and limited through a retainer ring at a hinge joint of the through hole; and grooves are formed in the middle of the parking pull arm and the middle of a front tendon of a front shoe assembly, the two ends ofa parking push plate are correspondingly arranged at the middle of the parking pull arm and the groove in the middle of the front tendon of the front shoe assembly, one end of a parking inhaul cableis connected to the lower end of a brake pull arm, and the other end of the parking inhaul cable penetrates through a brake bottom plate assembly to be connected to a hand brake end of a vehicle chassis. According to the self-adjustable servo type service drum brake with the parking function, a vehicle with a servo type drum brake can realize manual parking, the cost for independently developing aparking device is saved, and the reliability is high.

The invention relates to an adaptive multi-mean two-step clustering method, and the method comprises the steps: carrying out the preliminary clustering of input data through employing a multi-mean clustering algorithm based on a chaotic quantum particle swarm in the first step, and carrying out the further clustering on the basis of a clustering result in the first step through employing an adaptive hierarchical clustering algorithm in the second step, and obtaining a final clustering result; the method can be used for cluster distribution data clustering, can also be used for non-cluster data clustering, and has the advantages of being high in operation speed, low in complexity, wide in application range and small in influence of abnormal values. The method can be used as a basic technology for data processing, and can be used for data processing work in the fields of system modeling, pattern recognition, machine learning, data mining and the like.

The invention relates to a control system and a control method for a rotating hub test, which are used for executing a test working condition driving task. The system comprise an information acquisition unit, a human-computer interaction unit, a control unit and an execution unit, and are characterized in that the information acquisition unit is used for acquiring and outputting vehicle information; the human-computer interaction unit receives user input, generates test condition selection and vehicle parameter setting according to the user input and outputs the test condition selection and the vehicle parameter setting; the control unit receives the vehicle information, the test condition selection and the vehicle parameter setting, generates a target pedal position according to the vehicle parameters and the vehicle information based on the test condition, and outputs the target pedal position; the execution unit is used for receiving the output target pedal position and driving thepedal to the target pedal position. The method provided by the invention can be used for carrying out various working condition tests on various vehicle types.

The invention discloses an intelligent lathe control method. The method comprises the following steps: 1, in a processing process, current of a main motor and a deviation value returned by a grating ruler are detected in real time, a change deltaaf for a feed rate af serves as a system adjustment amount, and closed-loop feedback learning control during the processing process is realized; and 2, during a workpiece processing process, the vibration condition of a lathe workpiece serves as an input value, a particle swarm optimization algorithm is adopted to set servo driver parameters, and the system can operate more stably. Self setting of parameters of a numerical control driving device can be realized, the numerical control system can timely acquire workpiece configuration error information, and adjustment on parameters of a subsequent process are facilitated.

The invention discloses a PLC based expert rule PID constant-pressure water supply system and method. The system consists of water pumps, frequency converters, a PLC and the like, wherein pressure sensors are mainly used for detecting pressure of water outlets of the water pumps, and then transmitting data to the PLC to perform feedback control with a set water pressure value. After computing processing is performed in the PLC, a CPU emits a control signal to regulate rotation speed of motors of the water pumps and to control number of the water pumps, so that pressure of the water outlets of the water pumps is stabilized near given pressure. According to the control system and method disclosed by the invention, conventional PID is improved, and an expert rule base is added into the conventional PID, so that the conventional PID can be self-tuned in a self-adaptive mode online. The PLC based expert rule PID constant-pressure water supply system quickly tracks a water pressure parameter set value, and controls water amount by changing frequency of an asynchronous motor of a water pump, so that water supply pressure is controlled, and automatic control of the water supply system is realized. The system can realize PID parameter self-adaption, improves stability of the water supply system, can perform parameter online self-tuning, and facilities improving quickness of the water supply system.

The invention provides a diode chain-type packaging furnace, and the furnace comprises a furnace body, an atmosphere control system, a temperature control system, and a transmission system. The furnace body is provided with a direct opening, and the furnace body comprises an inlet platform, an inlet transition segment, an inlet thermal preservation, a heating segment, an outlet thermal preservation segment, a cooling segment, an outlet transition segment, and an outlet platform. The inlet transition segment and the outlet transition segment are respectively provided with a transition packagingsteel sleeve, and the atmosphere control system comprises an atmosphere generation device, a temperature control device, a gas circuit control device and an exhaust gas channel. The temperature control system comprises a temperature control instrument, a K-thermocouple, and a temperature alarm system. The transmission system comprises a mesh belt conveying device and a variable frequency speed regulating device disposed on the temperature control instrument, and the mesh belt conveying device is disposed at the direct opening of the furnace body. According to the scheme of the invention, thenumber of leaking points of the whole furnace is reduced, and the oxygen content meets the technological requirements in the whole course. The furnace is good in temperature control effect, is stablein continuous transmission, is convenient to operate, and enables the quality of a product to be better.