253 results about "Yaw control" patented technology

The invention relates to a multi-machine cooperative yaw control method and device considering a dynamic wind direction and a medium. The multi-machine cooperative yaw control method comprises the steps that S1, the dynamic relation between the wind direction and a wake flow area is established based on a Gaussian-curl hybrid model; s2, constructing a single-machine yaw optimization model based on model predictive control, optimizing single-machine yaw by taking maximum generating capacity of a wind power plant and reduction of fatigue load as optimization objectives, and obtaining a single-machine optimal yaw angle through rolling optimization and feedback correction; and S3, a serial optimization method is adopted to carry out multi-round iterative optimization on one fan by one fan, and an optimal multi-fan cooperative yaw control result is obtained. Compared with the prior art, the method has the advantages that higher total generating capacity and more balanced fatigue load can be realized, so that the whole wind power plant reaches the optimal state of power and load in a large range.

The invention discloses a heavy commercial vehicle yaw control system with delay compensation and slip suppression. A state sensing unit collects signals and sends data to a yaw control unit and a braking force control unit. The yaw control unit acquires a desired yaw moment and a braking moment. A yaw velocity tracking module calculates a desired yaw velocity. And the wheel slip suppression module obtains a brake torque for avoiding slip through control. The braking force control unit addresses braking force distribution under yaw moment control and wheel slip suppression, and compensates for the delay of the pneumatic brake system. And the braking force cooperative distribution module calculates the expected braking chamber pressure of each wheel according to the required yawing moment and the braking moment. The braking force delay compensation module calculates and predicts the pressure of a braking chamber through a prediction model, and obtains control input of a braking actuator through a PID controller so as to compensate delay. According to the system, the driving safety of the heavy commercial vehicle under the complex road condition is improved through cooperative control.

The invention relates to an empennage structure of a flapping-wing robot, which comprises a yawing mechanism, a pitching mechanism and a connecting mechanism, the yawing mechanism comprises a yawing steering engine, a yawing steering engine rocker arm, a yawing rocker arm and a yawing control surface; the pitching mechanism comprises a pitching steering engine, a pitching steering engine rocker arm and a pitching surface; the connecting mechanism comprises a pitching steering engine fixing plate, an empennage surface plate and a fuselage. The pitching motion function of the empennage is achieved through the knuckle bearing and the connecting rod structure, the yawing motion function of the empennage is achieved through the flexible material, the steering engine rocker arm and the yawing rocker arm, the yawing structure and the pitching structure are combined through the empennage plane plate, and the whole empennage mechanism is formed. The yawing motion cannot be affected during pitching motion, decoupling of the pitching motion and the yawing motion is achieved, meanwhile, the yawing control steering engine and the pitching control steering engine are both installed on the fuselage, empennage structural parts are reduced, the loading capacity during empennage motion is reduced, and the beneficial effects of being compact in structure and high in adjusting capacity are achieved.

The invention discloses a yaw wind error compensation method and system based on wind measurement data, and relates to the technical field of wind power generation equipment control, and the method comprises the steps: setting a wind measurement point position, and collecting an original wind field data set; calculating an incoming flow and a cabin wind direction angle according to the original wind field data set; performing deviation calculation to obtain a yaw wind error angle; triggering a dual-channel compensation module, accumulating errors, constructing an error queue, and performing batch compensation to obtain a compensation result; yawing control parameters are called, the cabin attitude is analyzed according to the compensation result, the yawing control parameters are updated, and self-adaptive compensation of yawing to the wind error is achieved. The technical problems that in the operation process of the wind driven generator, due to wake flow, terrain, turbulent flow and other environmental factors and equipment loss, a traditional yaw system cannot accurately detect the wind direction and compensate the wind alignment error, the power generation efficiency is low, and the potential safety hazard of equipment is large are solved, and the purposes of accurately improving the wind alignment precision of a wind wheel and improving the power generation efficiency are achieved. The power generation efficiency is obviously improved; and the equipment operation safety is enhanced.

The invention provides a wind turbine generator yaw control method and system based on turbulence intensity and an operation mode. The method comprises the steps that the turbulence intensity of the position where a to-be-controlled wind turbine generator is located and the operation mode of the wind turbine generator are obtained; determining whether to start a yaw system based on the turbulence intensity; when the turbulence intensity is larger than the turbulence intensity threshold value, the yaw system is closed, and when the turbulence intensity is smaller than or equal to the turbulence intensity threshold value, if the operation mode of the wind generating set is a fan starting mode or a grid-connected operation mode, a first yaw control strategy is selected to conduct yaw control over the wind generating set, if the operation mode of the wind generating set is the standby mode, selecting a second yaw control strategy to perform yaw control on the wind generating set; wherein the operation modes of the wind generating set comprise a wind waiting mode, a fan starting mode and a grid-connected operation mode. According to the technical scheme provided by the invention, the yaw system structure can be effectively protected in an area with high turbulence intensity and fast wind direction change.

The invention discloses a yaw control method and a related device, and relates to the field of wind power generation, and the yaw control method comprises the following steps: obtaining an original wind speed time sequence data set, an original wind direction time sequence data set and design parameters of a wind turbine generator, and calculating a yaw rate of the wind turbine generator based on the original wind speed time sequence data set and the original wind direction time sequence data set; obtaining a wind speed probability density function, a wind direction deviation probability density function and yaw control input data, determining initial yaw control parameters based on the wind speed probability density function, the wind direction deviation probability density function and the design parameters, and performing analogue simulation according to the yaw control input data and the initial yaw control parameters to obtain yaw control parameters. And determining a target yaw control parameter based on the simulation result and a preset multi-target constraint condition. According to the method, the difference of wind regimes of different wind power plants and the difference of wind turbine generators are considered, the two kinds of environmental condition data of the wind speed and the wind direction of the wind power plants are combined, the design parameters of the wind turbine generators are combined, and the target yaw control parameters are more adaptive to the wind turbine generators and the actual wind regimes.

The invention provides an unmanned aerial vehicle flight control method and system based on a multi-constraint optimization nonlinear prediction model, and the method is characterized in that the method comprises the steps: obtaining multi-mode unmanned aerial vehicle state data and multi-mode flight environment monitoring data which are collected in real time through a multi-mode sensor; acquiring control input including pitching, rolling and thrust motion for controlling the unmanned aerial vehicle; taking the multi-modal unmanned aerial vehicle state data, the multi-modal flight environment monitoring data and the control input as the input of a pre-trained nonlinear prediction model, outputting a yaw control quantity for adjusting the control input, and generating a control instruction for controlling the flight of the unmanned aerial vehicle by using the yaw control quantity and the control input; wherein the nonlinear prediction model takes multiple constraints including a dynamic model constraint, a reference control input constraint and a state constraint as a training target in a training process. According to the invention, high-precision stable control of the unmanned aerial vehicle can be realized.

The invention relates to the technical field of aircrafts, and discloses a distributed asynchronous tilt-rotor aircraft and a control method, and the method comprises the steps: receiving an instruction from the ground to obtain a ground instruction, and obtaining position information, speed information and the health state of the aircraft; deciding an adopted flight mode; in the multi-rotor mode, the optimized cross inclination angle is adopted to enhance the yaw control performance of the aircraft; giving an optimized control quantity in a fixed wing mode; in the transition flight mode, corresponding control strategies are obtained based on different asynchronous tilting strategies for control; adjusting the attitude of the aircraft according to the control instruction; according to the method, different flight modes can be controlled by adopting corresponding control distribution algorithms, the problems of complex control and low reliability of the tilt-rotor aircraft in the transition process can be effectively solved, the full-attack-angle and full-speed-domain flight capability of the tilt-rotor aircraft in the transition process is realized, and the flight efficiency of the tilt-rotor aircraft is improved. And the stall state of the aircraft in the transition process is avoided.

The invention provides a wind power plant yaw control method, system and device based on hierarchical optimization and a medium, and relates to the technical field of wind power plants, and the method comprises the steps: collecting real-time data of a wind power plant; the real-time data comprises wind speed, wind direction and wind turbine state information; preprocessing the real-time data to obtain initial wind power plant data; performing reference calculation and layered optimization on the initial wind power plant data in combination with a wake flow model to obtain an optimal yaw angle; the wake flow model is used for simulating the mutual influence effect between the wind turbines; the hierarchical optimization comprises a coarse search stage and a fine search stage; and according to the optimal yaw angle, the wind turbine is controlled to execute yaw. By adopting layered optimization, the calculation efficiency and adaptability of yaw control are improved, so that the overall power generation efficiency of the wind power plant is improved.

A coordinated control method and apparatus for the lateral stability of an electric vehicle and a storage medium. The method comprises: acquiring the current yaw velocity, the current sideslip angle, the current longitudinal velocity and a steering angle input by a driver; on the basis of the current yaw velocity, the current sideslip angle, the current longitudinal velocity and the steering angle, using a preset hybrid control rule to determine an additional yaw moment and an additional front wheel steering angle; sending the additional yaw moment to a DYC system, so that the DYC system allocates the additional yaw moment on the basis of a preset allocation rule, so as to obtain respective longitudinal braking forces of four hubs; and sending the additional front wheel steering angle to an AFWS system, so that the AFWS system allocates the additional front wheel steering angle on the basis of a preset steering control rule, so as to obtain respective steering angles of the four hubs. The present application avoids a lack of driving comfort and stability during single-system yaw control, ultimately remarkably improving the lateral control stability of vehicles.

The present application provides a cleaning device for a yaw brake disc of a wind turbine, which relates to the technical field of wind power equipment, and includes a mounting frame, one end of which is connected to a cleaning mechanism, and the other end of which is connected to a base of the wind turbine. The cleaning mechanism includes a rotating cylinder, and the outer wall of the rotating cylinder is connected to the mounting frame. A connecting pipe is provided at the lower end of the rotating cylinder, and a cleaner is provided at one end of the connecting pipe away from the rotating cylinder, and the cleaner contacts the upper surface of the yaw brake disc. The cleaning mechanism of the present application can automatically clean the yaw control disc, and does not require staff to climb to clean the yaw brake disc, thereby protecting the safety of the staff and saving labor costs.

The present invention relates to a yaw control method, system and electronic equipment for a wind turbine. The method first installs a laser radar on the wind turbine for a period of time to obtain sufficient historical measurement data, and then develops a data-driven machine learning method to obtain a laser radar wind direction estimation model. The laser radar can then be removed or migrated to other wind turbines, and the laser radar wind direction estimation model is used to replace the role of the laser radar in calibrating yaw deviation to improve the accuracy of inflow wind measurement in the wind turbine control process and significantly reduce costs.

The invention relates to a stability control method and system based on dynamic target yaw, and the method comprises the steps: obtaining a first output result based on a vehicle dynamics model, an input steering wheel rotation angle and a pedal signal; based on the operation parameters of the vehicle, the current driving intention of the vehicle is obtained, and the driving intention comprises forward driving and backward driving; calling a corresponding target yaw velocity formula based on the driving intention; obtaining a target yaw velocity based on the first output result and a target yaw velocity formula; on the basis of the target yaw velocity, the obtained side slip angle and the actual yaw velocity, additional yaw moment needing to be applied is obtained; and controlling the yaw stability of the vehicle based on the additional yaw moment. According to the method and the device, the problem of relatively poor yaw control stability caused by poor yaw stability control robustness due to improper single calculation of the target yaw in related technologies can be solved.

The invention relates to the technical field of new energy, and discloses an optimization method for an intelligent yaw system of a wind generating set, and the method comprises the steps: building the intelligent yaw system, enabling the system to be internally provided with seven modules, and enabling a multi-sensor data collection module to collect wind direction, wind speed and yaw angle data in real time, the data fusion module performs Kalman filtering fusion processing to obtain a high-confidence state estimation value, the intelligent decision output module generates an optimal yaw control instruction by adopting a multi-mode control strategy and a parameter self-adaptive mechanism based on fused data, an execution mechanism is driven to realize accurate wind alignment, and the system integrated hardware-in-the-loop test module is used for realizing accurate wind alignment. Omnibearing verification can be carried out before deployment, after actual operation, operation indexes are continuously monitored through the performance evaluation module, control parameters and fusion algorithm parameters are adjusted online through the optimization module on the basis of methods such as machine learning, closed-loop optimization is formed, finally, yaw precision, response speed and system stability are remarkably improved, and maintenance cost is reduced.

The present invention discloses a yaw control method and system based on meteorological data, including: acquiring first environmental data around a first object; predicting first characteristic data in the first environmental data according to the first environmental data; generating a first control target according to the first characteristic data; and using the first control target to generate a control instruction to control the first object. By combining meteorological data prediction and the dynamic response characteristics of the wind turbine, accurate yaw control instructions can be generated in real time, significantly improving the wind turbine's ability to capture the dominant wind direction and improving power generation efficiency. At the same time, the optimized control strategy effectively reduces the mechanical load and energy consumption of the yaw system and extends the service life of the equipment. Under extreme weather conditions, the present invention has higher stability and safety, avoids equipment wear caused by overly fast or over-frequency adjustments, and further improves the reliability and economic benefits of the wind power generation system.

The invention relates to a fan yaw control method, device, system and equipment, a medium and a product. The method comprises the steps that sensor data corresponding to a target time interval are acquired, and the sensor data comprise radar sensing data collected by a laser radar, stress sensing data collected by a stress-strain sensor and fan sensing data collected by other sensors; the other sensors comprise a wind speed sensor, a wind direction sensor, an ultrasonic sensor and an inertial measurement unit; according to the sensor data and a preset wind power prediction model, obtaining corresponding wind power prediction data of the fan at the target moment; and controlling the fan to yaw according to the wind power prediction data. By adopting the method, the control precision can be improved.

The invention discloses a large-scale wind power cluster-oriented coupling yaw control wind power plant parameterization mesoscale numerical simulation method, system and device. Firstly, basic data of wind turbines of a target wind power cluster are obtained; performing numerical modeling on each wind turbine by using the basic data; then, in numerical modeling, a yaw control command is added, the influence of yaw of the front row of wind turbines on the rear row of wind turbines is calculated through a yaw wake flow model, and therefore mesoscale numerical simulation under yaw control of the wind power plant is achieved. And finally, coupling the wind power plant parameterized model considering yaw control to a numerical weather forecast model, and carrying out numerical simulation research on a large-scale wind power cluster. Compared with a traditional wind power plant mesoscale numerical modeling method, yaw control parameterization is coupled, and flowing and operation characteristics and the like of a large wind power cluster under operation control can be simulated.

An aircraft having a plurality of independent yaw control mechanisms includes an airframe having a central fuselage sized to hold at least one operator or payload and a wing extending from the fuselage. The aircraft includes a distributed thrust array coupled to the airframe, the thrust array having at least a first, second, and third pair of propulsion assemblies. Each propulsion assembly includes a rotor and is operable for at least single-axis thrust vectoring. The aircraft further includes a flight control system operable to independently control and combine each yaw mechanism of the propulsion assemblies. The yaw mechanisms for inducing a yaw moment include: canting at least one pair of propulsion assemblies away from the fuselage, selectively tilting at least one pair of propulsion assemblies forwards and backwards, varying an aerodynamic control surface of at least one propulsion assembly, and varying a rotational speed of at least one propulsion assembly.

The invention discloses a wind power plant multi-target yaw control method considering power load comprehensive benefits, and belongs to the technical field of wind power generation. The whole wind power plant wake flow modeling considering the yaw state is carried out by analyzing the wake flow model, the inflow data of each fan in the wind power plant is determined, and the total power and the average life of the wind power plant are rapidly and accurately predicted by combining the fan power, the thrust coefficient curve and the S-N curve of the transition section pipe node. Single fan power optimization and fan fatigue life optimization with power constraint are integrated, a two-stage multi-target control optimization system is established, and positioning of an optimal yaw combination of each stage is accelerated by establishing a Bayesian machine learning network and utilizing efficient and accurate power and life prediction data. According to the method, the optimal yaw strategy considering the power load comprehensive benefit can be accurately and efficiently provided according to the real-time wind speed data, and the load is reduced to the maximum extent and the service life of the fan is prolonged while the power generation requirement of the wind power plant is met.

The embodiment of the invention provides a yaw angle rapid optimization method and system for active yaw control, and the method comprises the steps: setting an initial yaw matrix formed by all fan yaw angles as a zero matrix, calculating the corresponding power of each fan traversing a preset fan yaw angle candidate set, and calculating the corresponding power of the fan yaw angle candidate set; selecting a first fan yaw angle corresponding to the maximum power of each fan to form a first yaw matrix of all fans; for each fan, after different offsets are added on the basis of the first fan yaw angle, the corresponding power is calculated, the offset value is in a preset offset angle candidate set, and a second fan yaw angle corresponding to the maximum power of each fan is selected to form a second yaw matrix of all the fans; and for each fan, different correction disturbance values are added on the basis of the second fan yaw angle, the power of the wind field is calculated, and a third fan yaw angle corresponding to the maximum power of each fan is selected to form a third yaw matrix of all the fans.

The invention provides an active yaw control method for a single-point mooring floating type draught fan platform, and belongs to the technical field of offshore wind power. A wind direction angle is obtained in real time through a wind direction sensor, and the deviation between the wind direction angle and the azimuth angle of a platform main shaft is judged; the system calculates the average wind direction in a set time window so as to suppress the influence of high-frequency wind direction disturbance. The controller dynamically calls a model predictive control (MPC) algorithm according to wind direction deviation, outputs a target rotation angle of the flow guide rudder, drives the flow guide rudder to adjust the direction of the flow guide rudder, generates a yaw moment acting on the platform, and guides the platform to rotate around a single-point mooring rotor to realize active wind facing; the guide rudder assembly and the hydraulic driving system are arranged between the vertical columns with the heaving plates in cooperation with the platform, accurate and rapid attitude control can be achieved, and the wind facing capacity and the structural stability of the draught fan are remarkably improved. According to the wind turbine platform, the wind facing posture can be adjusted in real time according to the change of the wind direction, so that the wind energy utilization efficiency is improved, and the power generation requirement under the deep and far sea complex environment is met.

The embodiment of the invention provides an offshore wind field simulation and wind turbine generator control system and method and a wind turbine generator, and the system comprises a data preprocessing module which is used for carrying out format conversion, projection transformation and quality control on multi-source heterogeneous meteorological data; the data fusion module is used for performing intelligent fusion on the preprocessed multi-source heterogeneous meteorological data to generate three-dimensional fusion field data; the mode adjusting module is used for dynamically optimizing a data fusion strategy based on the sea condition change; the resolution conversion module is used for performing temporal-spatial resolution conversion on the three-dimensional fusion field data to generate refined three-dimensional wind field data; and the zone control module is used for performing zone division on the wind field based on the refined three-dimensional wind field data, generating differential yaw control strategies of the corresponding zones according to related data and zone characteristics of each zone, and driving a unit to execute the yaw control strategies. The wind field simulation precision and the adaptability to complex sea conditions are improved, and wind energy capture and equipment loads are balanced through a differential yaw strategy.

The invention discloses an emergency yaw control method, device and equipment for the out-of-control rotating speed of a wind turbine generator and a medium. The emergency yaw control method comprises the steps that real-time operation data of the wind turbine generator are obtained; determining a predicted operation state of the wind turbine generator according to the operation data of the wind turbine generator; if the emergency yaw is triggered, acquiring real-time environment data, and determining a target yaw angle according to the real-time environment data; according to the current yaw angle and the brake temperature data, the yaw speed is dynamically adjusted, and an emergency yaw system of the wind turbine generator set is controlled to output a control signal at the dynamically adjusted yaw speed till the target yaw angle is reached. The invention belongs to the field of wind turbine generators. The yaw speed can be adjusted in real time, the energy consumption of a hydraulic system is reduced, and the overall energy utilization efficiency is improved.

The invention belongs to the technical field of unmanned aerial vehicles, and discloses a tandem rigid rotor heavy-load unmanned aerial vehicle and a control method thereof. The tandem rigid rotor heavy-load unmanned aerial vehicle comprises a vehicle body, horizontal attitude control small propellers are installed at the two ends of the front portion and the two ends of the rear portion of the vehicle body respectively and used for roll control and pitching fine adjustment, a front main rotor is installed on the front side of the top of the vehicle body, and a rear main rotor is installed on the rear side of the top of the vehicle body. The front main rotor and the rear main rotor are used for generating lift force and adjusting pitching moment, and a plurality of vertical yaw control small paddles are installed at the bottom of the aircraft body and used for generating yaw control moment; driving systems are mounted on the small horizontal attitude control propellers, the front main rotor, the rear main rotor and the small vertical yaw control propellers, a controller system is further mounted at the top of the aircraft body and used for constructing a closed-loop feedback control framework, and the controller system is connected with the driving systems; according to the invention, the heavy load requirement can be met, and the cost benefit and the good flight control performance are realized.

The invention relates to the technical field of wind power generation, particularly provides a multi-target yaw wake flow optimization method for a wind power plant, electronic equipment and a storage medium, and aims to solve the technical problem that the service life of a wind turbine generator is remarkably shortened possibly due to the fact that an existing yaw control strategy considers the whole power generation capacity but does not consider fatigue damage of the generator. In order to achieve the purpose, the wind power plant multi-target yaw wake flow optimization method comprises the steps that unit information, inflow condition information and a fatigue damage agent model of a target wind power plant are acquired; establishing an initial population based on the unit information; starting from the initial population, performing target iteration by using a genetic algorithm to maximize a first optimization target and minimize a second optimization target; when the first optimization target and the second optimization target converge, obtaining a Pareto frontier of multi-target optimization; and obtaining the optimal yaw angle combination of the target wind power plant based on the Pareto front. The fatigue damage of the unit is effectively inhibited while the total generating capacity is improved by bringing the fatigue damage of the unit into a control optimization target.

The invention provides an explicit model prediction control system and method, and the method comprises the steps: obtaining a current yaw angle and a yaw angular velocity of a three-degree-of-freedom helicopter, and generating an error vector of the three-degree-of-freedom helicopter; determining the current yaw motion state of the three-degree-of-freedom helicopter, and determining a control state vector for explicit model prediction control according to the error vector and the yaw motion state; the state space region of the three-degree-of-freedom helicopter is calculated off line based on explicit model predictive control in advance, and a target state space partition corresponding to a state vector is identified and controlled based on the state space region; and retrieving a control law associated with the identified state space partition, and controlling the yaw motion of the three-degree-of-freedom helicopter by using a yaw control signal generated by the retrieved control law. According to the technical scheme provided by the invention, the control signal can be updated in time when the three-degree-of-freedom helicopter is subjected to yaw control.

The invention discloses a yaw variable pitch control method, device and system based on wind regime prediction. The method comprises the steps that an original sensor data stream related to wind regime prediction is pulled from a message queue; pre-processing the original sensor data stream to obtain pre-processed first data; performing data windowing on the preprocessed first data; calculating a fuzzy entropy corresponding to the first data after windowing; selecting a corresponding reference model based on the fuzzy entropy to determine a predicted wind direction and a predicted wind speed; formulating a yaw control strategy according to the predicted wind direction, and formulating a variable pitch control strategy according to the predicted wind speed; and performing yaw control according to the yaw control strategy, and performing variable pitch control according to the variable pitch control strategy. According to the method, the wind direction and the wind speed are determined through wind regime prediction, the yaw control action is assisted, the control hysteresis is reduced, the system response speed is increased, and the accuracy of yaw and variable pitch control is improved.

The invention belongs to the technical field of floating equipment, and particularly relates to a tethered airship with a propelling device and a conveying system for the tethered airship. A connecting part is arranged on the outer surface of a boat body, a propelling device comprises a horizontal propelling part and a vertical propelling part, the horizontal propelling part is arranged on the peripheral surface of the boat body and used for moving the boat body in the horizontal direction, and the vertical propelling part is arranged on the peripheral surface of the boat body and used for moving the boat body in the vertical direction. The horizontal direction is perpendicular to the vertical direction, and the mooring rope is detachably connected with the connecting part. According to the tethered airship with the propelling device in the technical scheme, the horizontal propelling part is used for providing propelling force in the horizontal direction to achieve the functions of headwind adjustment, yaw control and the like of the airship body, and the vertical propelling part is used for providing pulling force in the vertical direction to achieve height adjustment and pitching control of the airship body. The propulsion device improves the propulsion efficiency of the boat body, and further enhances the wind measurement resistance and attitude stability of the boat body.

The invention discloses a yaw control method based on data driving and multi-objective optimization, and the method comprises the steps: dividing a wind speed interval: according to the wind resource characteristics, yaw behavior, wind direction distribution characteristics, wind speed frequency distribution, turbulence intensity in different wind speed intervals, and the influence of a yaw deviation angle on output power in different wind speed intervals of a mountain wind power plant, determining the wind speed interval of the mountain wind power plant; the wind speed range below the rated wind speed is divided into a low-speed stable interval of 3-6 m / s, a medium-speed optimization interval of 6-8 m / s and a high-speed balance interval of 8-11 m / s. A data driving and multi-objective optimization algorithm is adopted, so that the yaw system can flexibly adjust yaw control parameters in real time according to dynamic changes of the wind speed, the wind direction and the turbulence intensity. No matter whether the wind direction changes suddenly or the turbulence intensity fluctuates, the yaw system can make a response rapidly, and it is ensured that the wind turbine generator is in the best windward state all the time.

The present invention relates to the technical field of aircraft performance analysis, and specifically discloses a structural angle design and performance analysis method and system for an inclined thrust quadrotor. First, the angular parameters of the two degrees of freedom of the inclined thrust quadrotor are set, and the three-axis thrust equation in the body coordinate system is constructed. Then, the components of the x-axis and y-axis in the three-axis thrust equation are set to zero, and the self-stabilization boundary of the quadrotor is calculated to obtain the self-stabilization domain. Next, the lift coefficient and yaw moment coefficient are calculated according to the three-axis thrust equation. After discretizing the angular parameters within the self-stabilization domain, the lift coefficient values and yaw moment coefficient values at each discrete point are calculated. Finally, the desired lift efficiency and desired yaw control efficiency are set, and the values of the angular parameters that satisfy the desired efficiency are solved respectively. The present invention explores the coupling relationship and sensitivity between flight performance and two structural angles from both quantitative and qualitative levels, providing a guiding direction for the structural optimization of aircraft.