30results about How to "Good dynamic and static characteristics" patented technology

The invention discloses a speed and current double closed-loop control system and method for a permanent magnet synchronous linear motor. The method comprises the steps of: designing a permanent magnet synchronous linear motor vector control system; designing a fuzzy adaptive sliding-mode speed controller; designing a nonlinear disturbance observation; designing a d-axis fuzzy PID controller; designing a q-axis fuzzy PID controller; obtaining a desired q-axis current reference value as an input of the q-axis fuzzy PID controller according to the designed nonlinear disturbance observer and thedesigned fuzzy adaptive sliding-mode speed controller; setting a d-axis reference current value as 0, and using the id obtained by subtracting park transform from 0 as the input of the d-axis fuzzy PID controller; after the processing by the d-axis fuzzy PID controller and the q-axis fuzzy PID controller, obtaining the ud, uq of the vector control system, and finally outputting the current operating driving voltage of the permanent magnet synchronous linear motor by the anti-park transformation and SVPWM modulation through the vector control and an inverter. The method enhances the robustnessof the system.

The invention discloses a fuzzy sliding mode and neural network based composite control system of a permanent synchronous motor. The control system comprises a rotation speed control outer ring and a current control inner ring, wherein a control unit in the rotation speed control outer ring adopts a composite control module; the composite control module comprises a fuzzy sliding mode control module and a neural network control module; and the fuzzy sliding mode control module and the neural network control module are combined together through two weighing factors lambda n and lambda f. The control system has the advantages of both the fuzzy sliding mode control module and the neural network control module, so that the strong robustness and high stability of the control system of the permanent synchronous motor are realized, the steady state precision is improved, and moreover, the rapidness in control and the strong load disturbance resistance are achieved.

The invention belongs to the field of controlling power converters of wind power generation systems and relates to a deadbeat power control method for a grid-side converter under network voltage unbalance. The deadbeat power control method comprises the steps that three-phase network voltage, a three-phase alternating side current and direct current side voltage of the grid-side converter are detected, a network voltage sampling value and an alternating side current sampling value under a two-phase rest frame through 3/2 coordinate transformation, and network voltage retardation is obtained by delaying one fourth of a power grid period of the network voltage sampling value; an active power reference value is calculated, and an alternating side current reference value is calculated and obtained; transformer alternating current side voltage controlled by the deadbeat power is calculated; in order to compensate for time delay in the calculation and control process, the transformer alternating current side voltage at the next moment is predicted and serves as control voltage; a switch signal controlling a power switch component is obtained and is used for controlling on-off sequence and on-off time of the power switch component. According to the deadbeat power control method for the grid-side converter under network voltage unbalance, the grid-side converter can be effectively controlled to have good dynamic and static characteristics under the condition of network voltage unbalance, and reliable grid connection operation of a wind generating set is ensured.

The invention discloses a hybrid electric vehicle belt-driven started generator (BSG) torque ripple compensating controller and a construction method of the hybrid electric vehicle BSG torque ripple compensating controller. The torque ripple compensating controller controls a composite controlled object. The torque ripple compensating controller comprises a PI adjuster, an extended inverter control module and a current compensating module. The composite controlled object comprises a hybrid electric vehicle BSG, a photoelectrical coded disk and a revolving speed and electrical degree calculation module. A neural network is adopted to build the current compensating module, the neural network is of a four-layer structure, and the neural network is trained by the adoption of the Powell algorithm. According to the hybrid electric vehicle BSG torque ripple compensating controller and the construction method of the hybrid electric vehicle BSG torque ripple compensating controller, the current compensating module is recognized through the neural network, the current harmonic wave of a BSG motor can be restrained effectively, and the torque ripple of the motor is reduced significantly, so that the hybrid electric vehicle BSG system has good dynamic and static characteristics and very strong robustness.

The invention discloses an electromagnetically-driven micro mirror H-infinity control method and an H-infinity control system, which are applied to an electromagnetically driven micro mirror platform composed of an NI PXI controller and LabVIEW software and other hardware equipment. The control method comprises the following steps: S1, selecting an optimization model; S2, selecting a weighting function; S3, regulating the parameters of the weighting function; S4, solving an H-infinity controller; S5, analyzing the performance of a closed-loop system; and S6, discretizing the H-infinity controller through a Z transformation method. The electromagnetically-driven micro mirror H-infinity control method is disclosed in view of the shortcomings of the existing electromagnetically driven micro mirror PID control method. On the basis of ensuring good dynamic and static characteristics of the micro mirror system, the method improves the un-modeled dynamic robust performance of the system, reduces the power consumption of the controller, and restrains the output noise. The method achieves a good control effect, and is more in line with the requirements of practical application.

The invention relates to a brushless DC motor simulation control method and a brushless DC motor simulation system. The brushless DC motor simulation control method comprises steps that S1, back electromotive force in a BLDCM body is acquired; S2, a PI controller is used to establish a speed control module; S3, a Hall signal generating module is established; S4, a reference current module and a current hysteresis control module are established; S5, an inversion circuit module is established. On basis of analysis of brushless DC motor mathematic model, by combining with conventional PI control and fuzzy control advantages, fuzzy PI control and current hysteresis control are used for a permanent magnet brushless DC motor double-closed loop control system used for an electric vehicle, and then simulation verification of a control strategy is carried out, and therefore the rotation speed response of the DC brushless motor is fast and overshoot-free, and strong inhibition performance related to load disturbance is provided, good dynamic, static characteristics are provided, and then the acceleration performance and the driving stability of the electric vehicle are improved.

The invention discloses a feedback linearization sliding-mode control method of a three-phase three-wire system shunt active power filter. According to the control system, an indirect current control method is adopted, and reference supply current is selected as a reference signal for current tracking control. The feedback linearization technology is used for controlling direct current-side voltage of the shunt active power filter. An integral position tracking sliding-mode control is used for tracking control of the reference signal. The problem that the computing method of a sinusoidal signal in traditional unit is inapplicable in case that the harmonic content of the power voltage is higher is solved. According to the feedback linearization control method, the control of the direct current-side voltage is realized, and the system has good dynamic and static characteristics and possesses good adaptability to variation in load. With the adoption of an integral position tracking sliding-mode controller, the harmonic content of the power current after being compensated can be effectively reduced, and the harmonic compensation effect of the active filter can be improved. The whole control system of the active filter is simple in structure and easy to realize, and has good theoretical and practical significance.

The invention discloses an arbitrary level real-time sector subdivision direct torque control method, which comprises the following steps that: S1: the total number x of sectors of the current motor control system is determined, and the sector correlation coefficient n is determined according to a formula; S2: according to the sector correlation coefficient n and the total number m of basic vectors, the m-layer sector layout is built; S3: the position of motor flux is judged, and the used vectors at the current position in the sector layout is locked at the position; S4, the instantaneous speed of a motor is detected for the synthesis of control vectors; S5: the lock-in positions of the control vectors are determined, so that a coordinate axis of a motor control system is built; S6: zero sectors are determined according to the instantaneous speed of the motor, and in accordance with the zero vectors, a real-time vector table is synthesized; and S7: appropriate vector values are selected from the vector table to be used for controlling the motor. In the method, according to the real-time situation, the optimal vector is synthesized to be used to reduce the torque ripple so as to achieve better static and dynamic characteristics.

The invention relates to a decoupling control method and system of a fuel cell air system. The method comprises the following steps of recognizing and calculating air parameters, and generating a gaincoefficient and a time coefficient of a decoupling control matrix, wherein the air parameters are an input variable and an output variable obtained through a test; generating an input and output parameter model in an air parameter control loop according to the autoregressive moving average model with the control quantity; substituting the gain coefficient and the time coefficient of the decoupling control matrix into the input and output parameter model in the air parameter control loop to generate a system transfer function relation matrix; and decoupling the system transfer function relationship matrix to generate a decoupling control matrix, and designing a decoupling controller according to the decoupling control matrix. The invention provides the method capable of relatively independently controlling parameters with strong coupling in the fuel cell air system, namely the decoupling control, so that the real-time online operation is realized, and the stable operation of the wholesystem is facilitated.

The invention discloses a sliding mode variable structure Buck circuit control method based on an extreme learning machine, and the method comprises the following steps: S10, carrying out the analysis of a Buck circuit topological structure, and building a system mathematical model through a state space averaging method; S20, defining a sliding mode surface of a controller, designing an extreme learning machine adaptive law, and designing the controller according to the system mathematical model in the S10; S30, verifying the existence of the sliding mode and the stability of the system by using the Lyapunov theorem according to the controller in the S20. Voltage and current signal changes of the circuit are monitored at the same time, and duty ratio signals output by a system are corrected in real time; the system can rapidly reach the sliding mode surface from any initial state, loads are switched when the circuit is in a steady state, the system can be stabilized to a steady-state output voltage value in a short time, the robustness of a controller is guaranteed, and system buffeting is weakened.

The invention discloses a low-energy-consumption high-pollution-resistance ultrahigh-frequency-response digital hydraulic servo control system and a control method. The system comprises digital hydraulic switch valves, a hydraulic cylinder, a displacement sensor, pressure sensors and a digital controller, main pressure oil is respectively connected with main pressure oil ports of a first digital hydraulic switch valve and a second digital hydraulic switch valve, main return oil is respectively connected with secondary pressure oil ports of a third digital hydraulic switch valve and a fourth digital hydraulic switch valve, a secondary pressure oil port of the first digital hydraulic switch valve and a main pressure oil port of the third digital hydraulic switch valve are respectively connected with a hydraulic cylinder piston cavity oil port, a secondary pressure oil port of the second digital hydraulic switch valve and a main pressure oil port of the fourth digital hydraulic switch valve are respectively connected with a hydraulic cylinder rod cavity oil port, the displacement sensor, a first pressure sensor and a second pressure sensor are respectively connected with a comparator, and a signal generator is respectively connected with magnet exciting coils of the four digital hydraulic switch valves. According to the system, ultrahigh-frequency fluid pulse signals are directly converted, and therefore accurate control of hydraulic servo is realized.

The invention, which belongs to the technical field of permanent magnet synchronous motor controlling, relates to a permanent-magnet synchronous motor, and a power generation alternating operation system and adjusting method. On the basis of a bidirectional transmission circuit of energy, the permanent-magnet synchronous motor converts the electric energy into the mechanical energy in a motor operating state and converts the mechanical energy into the electric energy in a generator operating state, and then the electric energy is returned back to a power supply. With a direct-current voltage variable circuit of a direct-current link, the direct-current voltage is reduced when the permanent magnet synchronous motor works at a low speed; and the direct-current voltage is boosted when the permanent magnet synchronous motor works at a high speed. The direct-current voltage matches the operating speed of the permanent magnet synchronous motor, so that the control performance of the permanent magnet synchronous motor is improved.

The invention discloses a hybrid magnetic bearing LM neural network inverse decoupling controller for flywheel energy storage, the output ends of two dynamic prediction modules are connected in series with the input end of an LM neural network inverse system, the first dynamic prediction module is composed of two series branches, and the second dynamic prediction module is composed of three series branches and a composite signal calculation module. Each series branch is formed by sequentially connecting a feedback correction module, a control increment calculation module, a predicted value calculation module and an optimal value calculation module in series; the input of the first series branch is a weight value and a reference weight value, the output of the first series branch is an optimal initial weight value, the input of the second series branch is a threshold value and a reference threshold value, the output of the second series branch is an optimal initial threshold value, the advantages of dynamic prediction, LM neural network control and an inverse system are combined, the initial weight value and the threshold value of the LM neural network are optimized by adopting a dynamic prediction module, and the optimal initial weight value is obtained. And independent accurate control among three degrees of freedom of the hybrid magnetic bearing for flywheel energy storage is realized.