11 results about "Adaptive control theory" patented technology

The invention discloses a self-adaptive impedance matching method for a high-frequency signal transmission connector of a new energy vehicle, and relates to the technical field of signal processing, and the method comprises the steps: 1, obtaining the physical parameters of the high-frequency signal transmission connector of the new energy vehicle; calculating an electromagnetic field feature vector, and calculating a transmission line distribution vector of the high-frequency signal transmission connector; 2, calculating a propagation constant of a high-frequency signal transmission connector of the new energy vehicle; calculating the characteristic impedance of a high-frequency signal transmission connector of the new energy vehicle; 3, calculating a reflection coefficient; calculating an impedance error; step 4, calculating a compensation parameter vector, and generating a control signal by using an adaptive control theory according to the compensation parameter vector; and calculating the impedance matching degree according to the control signal. According to the invention, impedance change in a complex environment can be accurately dealt with, signal reflection and energy loss are significantly reduced, and transmission efficiency and signal integrity are improved.

The invention provides a vehicle control method and device, an electronic device, a vehicle and a storage medium, and relates to the field of automobile control, and the method comprises the steps: determining a rear wheel expected turning angle value of the vehicle according to the obtained current yaw velocity, lateral acceleration and longitudinal velocity of the vehicle; and controlling the rear wheel to rotate according to the rear wheel expected corner value. According to the vehicle control method provided by the invention, the control of the rear wheels is only determined by the yaw angle and the centroid sideslip angle of the vehicle in the current state. According to the method, the yaw angle and the side slip angle of the vehicle are taken as control quantities, the traditional self-adaptive LQR control theory is improved, and the rear wheel steering angle value with higher precision is calculated in real time, so that the accuracy and the reliability of vehicle steering control can be effectively improved, the stability and the safety of the vehicle are better, and the driving and riding requirements of the vehicle are well met.

The application discloses a city air traffic system control architecture switching method and device, relates to the technical field of system engineering and automatic control, and is based on an adaptive architecture switching control model constructed based on adaptive control theory and fuzzy logic control. Based on state variable values and performance index values of the system, the adaptive architecture switching control model is used to switch the type of the city air traffic control system architecture and the corresponding model structure in real time, so that the operation efficiency of the city air traffic system can be effectively improved, and the loss caused by the safety risk can be reduced. The application designs three types of city air traffic control system architectures for the city air traffic system, can meet the command and control requirements of different scenes, and provides a reference for the design of the city air traffic system control architecture.

The application discloses a real-time modeling and online optimization method and system for thermal characteristics of a steam turbine valve, key data reflecting changes in steam turbine flow is stably obtained from a SIS system or a DCS system; a flow characteristic fitting model between unit electric load, thermal load, main steam parameters and flow characteristics is established, and is optimized, a multi-parameter flow characteristic fitting model is output, standardized pretreatment data sets are input, and a theoretical flow characteristic curve is output; comparison is made with an actual flow characteristic curve, and a curve offset deviation value between the two is identified; the multi-parameter flow characteristic fitting model, the curve offset deviation value and a primary frequency modulation instruction of a power grid are fused, parameters of the flow characteristic curve are dynamically adjusted based on adaptive control theory and the multi-parameter flow characteristic fitting model, and an optimized valve position instruction parameter and a curve correction scheme are generated; and the application avoids the hysteresis problem of traditional offline correction.

The application relates to a fuzzy self-adaptive constant force polishing method, system and device, wherein the method comprises the following steps: based on a force sensor digital signal received in a workpiece polishing process, actual contact force in the polishing process is calculated in real time; based on the actual contact force, a damping coefficient of a mobility control model is adjusted through a fuzzy control theory; based on the actual contact force, the mobility control model is optimized through an adaptive control theory; and through the adjusted and optimized mobility control model, a target polishing track of a polishing tool is updated. Through the application, the problem of large tracking error of workpiece automatic polishing is solved, the best force control parameter dynamic rapid adjustment based on a fuzzy control algorithm is realized, and real environment position and stiffness compensation based on an adaptive control algorithm is realized, so that the effect of eliminating steady-state error and improving workpiece polishing precision is achieved.

The present invention provides an intelligent operation and maintenance method and system for air-conditioning systems based on Internet of Things technology, wherein the present invention utilizes intelligent sensors and edge computing nodes to process operating data, and generates a comprehensive operating information package in combination with environmental parameters. Next, simulation analysis is performed through a cloud-based digital twin model to generate performance predictions and fault point assessments, and the Bayesian network algorithm is used to evaluate the probability of failure and generate personalized operation and maintenance recommendations. Then, a genetic algorithm is used to optimize the operating parameters, and the settings are smoothly adjusted through adaptive control theory. When an anomaly is detected, multi-level thresholds and fuzzy logic are used to determine the severity of the fault, and an early warning mechanism is triggered immediately to push an emergency response plan. Finally, the maintenance process and user feedback are recorded, the digital twin model is updated, and a closed-loop operation and maintenance system is formed to ensure efficient and stable operation and improved service quality.

The application discloses a master-slave industrial robot system adaptive sliding mode trajectory tracking method. Firstly, a disturbed robot system is modeled; a master-slave control method of a double robot system is designed with the help of a distributed control idea, and on this basis, a segmented preset sliding surface, a master-slave industrial robot trajectory tracking sliding mode controller and an adaptive law of controller parameters are designed by using switching control, adaptive control theory and sliding mode control principle, so that the master industrial robot can compensate for the lumped disturbance and overcome the influence of the actuator fault within a limited time, the tracking error of the target trajectory converges to the preset boundary within a limited time, and the slave industrial robot can overcome the influence of the lumped disturbance and the actuator fault and realize the asymptotic tracking of the trajectory of the master industrial robot. The application solves the problem of how the master-slave industrial robot system can quickly realize consistent trajectory tracking under the influence of internal parameter perturbation, external disturbance, transmission mechanism gap and actuator fault.

The application discloses a kind of based on adaptive loop compensation dynamic wireless charging system's voltage stabilizing control method.The application is divided into two steps, first, according to the expected phase margin and crossing frequency, feedback controller meeting the frequency domain design parameter is designed;Second, according to the feedback controller designed above, using reference model adaptive control theory, the feedback controller parameters are adaptively iterated to obtain the feedback controller with better performance.The application introduces adaptive control algorithm, compared with the conventional lead-lag loop compensation feedback controller, not only can make electric vehicle when carrying out static wireless charging have satisfactory anti-interference performance, but also can suppress the wide-range voltage disturbance caused by electric vehicle movement in dynamic wireless charging process, more practical, wider application range.

The present invention provides a relative motion adaptive control method for the close-range detection mission of small spacecrafts, which is characterized by the following steps: Step 1, regarding the close-range detection object as the target spacecraft and the small spacecraft as the service spacecraft, and constructing a relative orbit dynamics model between the two; Step 2, designing a full-process nominal flight trajectory according to the requirements of the close-range detection mission, including parameters of some key hover points, transfer trajectories between hover points, and transfer times; Step 3, respectively representing the relative orbit dynamics model and the nominal flight trajectory in state space; Step 4, regarding the nominal flight trajectory as the reference model and the relative orbit dynamics model as the controlled object, and designing a relative motion adaptive controller by using the adaptive control theory SAC. The present invention still has good control effects under the influence factors such as the existence of modeling uncertainty terms, unknown disturbances, and limited control capabilities in the controlled object.

The application discloses a self-adaptive impedance matching method of a high-frequency signal transmission connector of a new energy vehicle, and relates to the technical field of signal processing.The method comprises the following steps: step 1: obtaining physical parameters of the high-frequency signal transmission connector of the new energy vehicle; calculating an electromagnetic field characteristic vector and a transmission line distribution vector of the high-frequency signal transmission connector; step 2: calculating a propagation constant of the high-frequency signal transmission connector of the new energy vehicle; and calculating a characteristic impedance of the high-frequency signal transmission connector of the new energy vehicle; step 3: calculating a reflection coefficient and an impedance error; step 4: calculating a compensation parameter vector, generating a control signal by using an adaptive control theory according to the compensation parameter vector, and calculating an impedance matching degree according to the control signal.The application can accurately cope with impedance changes in complex environments, significantly reduce signal reflection and energy loss, and improve transmission efficiency and signal integrity.

The invention discloses an LCL grid-connected inverter midpoint potential adaptive prediction control method, and the method comprises the steps: carrying out the discretization of a three-level NPC type LCL grid-connected inverter based on a forward Euler method, and building a prediction model; secondly, constructing a value function including grid-connected current tracking, filter capacitor voltage, inverter side current and a neutral-point potential balance term, wherein the neutral-point potential balance term is weighted by a variable weight coefficient; according to the method, a model-free adaptive control theory is innovatively introduced, a dynamic data model between midpoint potential deviation and a weight coefficient is established online by using a tight-format dynamic linearization method, and an adaptive updating law of the weight coefficient is designed through real-time estimation of a pseudo-partial derivative. According to the method, complex working conditions such as current step change can be effectively handled, neutral-point potential fluctuation can be strictly limited within 1V without manually setting parameters, cooperative control of grid-connected current high-precision tracking and neutral-point potential balance is realized, and the robustness and dynamic and steady-state performance of a system are remarkably improved.