32 results about "MRAS" patented technology

Motor drives, motor speed controllers, motor speed estimation systems, and methods are presented for controlling motor speed and for estimating motor speed, in which a speed estimate controller provides a rotor speed estimate based on a first error term from a torque-based MRAS component for a first range of motor speeds and based on a second error term from a rotor flux-based MRAS component for a second range of speeds.

The invention discloses a rotary speed estimation method for a bearingless asynchronous motor, and provides a rotary speed detection system and method for the bearingless asynchronous motor and based on POPOV hyper-stability so as to solve the problem of inaccurate rotary speed identification of the current bearingless asynchronous motor. Two sets of rotor magnetic linkage voltage model observation values are obtained according to actually measured stator voltage and current signals through a magnetic linkage observer formed by a common integrator and a magnetic linkage observer formed based on an improved second-order generalized integrator; the observed rotor magnetic linkage is used as a reference value; and the rotor magnetic linkage is solved by a rotor magnetic linkage current model to be used as an adjustable value to form two sets of rotor magnetic linkage-based model reference adaptive systems (MRAS). Through a proper adaptive law, the rotary speed of the bearingless asynchronous motor is identified; then a proper rotary speed identification observer is controlled to be selected through a regulation and control module to obtain an accurate real-time rotary speed value; and the invention does not give unnecessary details on a suspension force control part of the bearingless asynchronous motor.

The invention discloses a fuzzy-control-improved permanent-magnet-motor speed-less speed measurement system. The fuzzy-control-improved permanent-magnet-motor speed-less speed measurement system comprises a PMSM module, a Clark conversion module, a Park conversion module, a voltage-and-current conversion module, an MRAS module, a first comparator module, a fuzzy controller module, a second comparator module, a first PI adjusting module, a third comparator module, a second PI adjusting module, a Park inverse conversion module, an SVPWM module and an inverter module; the fuzzy-control-improved permanent-magnet-motor speed-less speed measurement system is used for detecting the position and the speed of a motor; in the actual running process, model reference self-adaptive control is that the actual running condition of the motor serves as a reference model, a motor model containing parameters such as the to-be-estimated rotating speed and a current serves as an adjustable module, an equation free of an unknown parameter serves as a reference model, the adjustable module is adjusted through a difference value between an actual measurement current and an estimated current of the motor, the estimated value tracks the actual value, an output difference value of the two models tends to be zero, and therefore the aim of the rotor stably runs is achieved.

The invention discloses a rotor flux linkage observation and rotation speed recognition method for a bearing-free asynchronous motor, provides a rotation speed detection system and method for the bearing-free asynchronous motor based on POPOV superstability and aims at solving the problem that existing bearing-free asynchronous motor rotation speed recognition is inaccurate. A rotor flux linkage voltage model observation value can be obtained through a flux linkage observer which is formed by an improved second-order generalized-frequency self-adaption integrator according to measured stator voltage and current signals, observed rotor flux linkage serves as a reference value, rotor flux linkage solved through a rotor flux linkage current model serves as an adjustable value, and a model reference adaptive system (MRAS) based on the rotor flux linkage can be formed. The real-time rotation speed of the bearing-free asynchronous motor can be accurately recognized through an appropriate self-adaption law.

The invention discloses a position sensorless control method for a permanent magnet synchronous motor based on a simplified MRAS method, which belongs to the field of motor control systems and includes the following steps: S1: constructing a reference model of a permanent magnet synchronous motor position sensorless identification system based on the MRAS method and Adjustable model, S2: Constructing the IPMSM position identification system based on MRAS method, S3: Performing simulation analysis on the constructed IPMSM position identification system based on MRAS method, S4: Constructing an improved system with no position sensor algorithm after adding resistance identification, S5 : Simulate and analyze the improved system without position sensor algorithm after adding resistance identification. The position sensorless control method of permanent magnet synchronous motor based on the simplified MRAS method is more scientific and reasonable. On the premise of not affecting the control effect, the MRAS method is simplified and stator resistance identification is added, which makes the motor model more accurate and improves the rotor position identification. precision.

The invention belongs to the technical field of inertia identification, and discloses an inertia identification method, system and storage medium based on speed interpolation, and uses different improved MRAS inertia identification algorithms for inertia identification based on different input speed waveforms. Determine whether the input speed waveform is a triangle wave or square wave; when the input speed waveform is a triangle wave, select the improved MRAS inertia identification algorithm based on the triangle wave input for MRAS inertia identification; when the input speed waveform is a square wave, select the improved MRAS based on the square wave input. The inertia identification algorithm performs the MRAS inertia identification. The present invention uses triangular wave and square wave as the input speed signal to perform inertia identification, which has the problem of low precision. A targeted and improved MRAS inertia identification algorithm is proposed to improve the accuracy of inertia identification results. Compared with other improved solutions of MRAS, the present invention has the characteristics of less computational burden and more practicality.

The invention discloses a method for asynchronous motor rotor flux linkage observation and rotation speed identification, which comprises the following steps of: according to stator voltage and current signals measured in real time, observing to obtain a rotor flux linkage through a sliding mode observer based on a super-twisting theory and using the rotor flux linkage as a reference value; using a rotor flux linkage calculated according to a rotor flux linkage current model as an adjustable value; constructing a model reference self-adaptive system (MRAS) based on the rotor flux linkages; and identifying the asynchronous motor rotation speed through the self-adaptive law. The rotation speed identification method provided by the invention has high robustness for the variation of stator resistance, and can provide accurate rotor flux linkages and rotation speed values, thereby being especially suitable for an asynchronous motor vector control system.

The invention discloses a permanent magnet synchronous motor speed-sensor-free speed measuring method based on fuzzy control and an MRAS. The method is used for position and speed detection of a motor. In the actual running process, according to model reference adaptive control, the actual running condition of the motor serves as a reference model, a motor model containing to-be-estimated rotating speed, current and other parameters serves as an adjustable model, an equation not containing unknown parameters serves as a reference model, the two models have the same output quantity in physical significance, the output value of the reference model serves as ideal response, the two selected models both output current values, the adjustable model is adjusted through the difference between actually measured current and estimated current of the motor, the actual value is tracked through the estimated value, the output difference between the two models approaches zero, and therefore the purpose that output of the reference model can be tracked through output of a control object, and then the motor runs stably is achieved.