31results about How to "Reduce phase lag" patented technology

The embodiment of the present invention discloses a method for controlling the master end of a vascular interventional robot system based on adaptive force feedback, wherein the method includes: constructing a motor model; constructing a slide rail model; acquiring a slave end sensor signal, and filtering the slave end sensor signal; Constructing the reference model of the motor, based on the reference model, setting the controller to correct the parameters of the motor model in real time; based on the corrected motor model and the slide rail model, estimating the friction force, and compensating the friction force; based on the processed sensor signal, the torque force received by the restored slave device and the horizontal resistance received by the restored slave device act on the operating rod, and act on the restored operating rod The force is the force feedback. The method can realize precise force feedback, make the vascular interventional robot system have strong anti-interference and robustness, and can largely avoid output fluctuations.

The present invention discloses a permanent magnet synchronous motor fuzzy neural network control system for an electric car, relates to an electrical transmission and control technology field, and provides a speed controller based on the fuzzy mathematics and neural network theory and a novel sliding-mode observer based on a tracking differentiator. The system comprises a fuzzy neural network control unit, a sensorless unit, a flux linkage and current calculation unit, a dual- current-loop vector control unit and a control object unit, can realize parameter autotuning of the permanent magnet synchronous motor and high-precision speed regulation in the condition without a mechanical speed sensor, can be applied on an electric car taking the permanent magnet synchronous motor as a power device, and is simple in structure and reliable in operation. Compared to a traditional PID speed controller and a sliding-mode observer, the permanent magnet synchronous motor fuzzy neural network control system for an electric car is higher in tracking precision, stronger in robustness and smaller in counter electromotive force buffeting; and when parameter perturbation of the controller or load disturbance, the permanent magnet synchronous motor fuzzy neural network control system for the electric car also can perform online regulation of parameters of the controller and accurately estimate the position and the speed of a motor rotor.

Integrated circuits, for example, gyrator circuits include transistors that are preferably MOS devices and that are provided with series feedback networks, which compensate for the effects of channel delay in the MOS devices.

The invention discloses a digital converter of a magnetic encoder, comprising a magnetic encoder, a signal processor, a phase-sensitive detector, a feedforward signal generator and a state observer. The signal processor caries out amplitude conditioning and analog-to-digital conversion to the output signal of the magnetic encoder; the phase-sensitive detector can generate an error signal containing phase information according to the output signal of the magnetic encoder and an angle estimation value output by the state observer; the feedforward signal generator calculates a feedforward angular velocity value needed by the state observer according to the output signal of the signal processor; and the state observer demodulates the angle and the angular velocity of a tested rotating device according to the error signal and the feedforward angular velocity value. The invention can greatly reduce the phase lag of the demodulated signal when the rotating device continuously rotates and hashigh demodulation accuracy and strong anti-interference capability.

The invention discloses a method for detecting motor kinematics parameters based on pulse feedback. The method comprises the following steps: by continuously collecting the pulse count of N times before the signal reading time, linearly fitting the collected N pulse count and the corresponding time thereof to an N-1 order function, so as to obtain a relational function of a motor position and the time; solving a first-order derivative of the relational function of the motor position and the time to obtain a relational function of motor speed and the time; solving the first-order derivative of the relational function of the motor speed and the time to obtain a relational function of accelerated speed of a motor and the time; judging whether the signal reading time and the pulse count time are synchronous, and putting corresponding constraint conditions to obtain the detection results of the position, the speed and the accelerated speed of the motor. According to the method, the position, the speed and the accelerated speed of the motor as well as the speed range of expanded speed measurement at the signal reading time are calculated at the same time, so that the calculation accuracy and instantaneity of the position, the speed and the accelerated speed of the motor are improved.