A balance car system and its control method

Abstract

The invention discloses a balancing vehicle system and a control method thereof. According to a difference equation model and a drift error model of attitude signals of the balancing vehicle system, astate equation of an extended Kalman filter and a mathematical model of a permanent magnet linear motor are established. A second-order dynamic Terminal sliding film is used to drive permanent magnetsynchronous motor. Particle Swarm Optimization (PSO) is used to optimize the parameters of tracking controller, synchronization controller, clearance elimination controller and switching function ina two-motor system. The invention realizes that the signal collected by the sensor of the balancing vehicle has large noise and zero drift error, and solves the problem of poor robustness and the problem that the Brush motor structure is complex, fault, maintenance workload, short life, commutation spark easy to produce electromagnetic interference, as well as in the balance of the car in the process of running jitter, deviation is too large, and low security.

Description

technical field [0001] The invention belongs to the technical field of balance car control, and in particular relates to a balance car system and a control method thereof. Background technique [0002] Two-wheeled self-balancing vehicles have gradually entered people's lives because of their low price, small size, light weight, and ease of movement and portability. At present, the related technologies of self-balancing vehicles are constantly being updated, the control of the self-balancing system is more flexible and sensitive, and the human-computer interaction system tends to be more detailed and humanized. But in terms of driving mode, most of the mainstream self-balancing car brands on the market currently use DC brushed motors, and the electric energy enters the armature winding through the brushes and commutator to drive the motor. Due to the existence of brushes and commutators, brushed motors have characteristics such as complex structure, many faults, heavy mainte...

AI Technical Summary

Problems solved by technology

Due to the existence of brushes and commutators, brushed motors have characteristics such as complex structure, many faults, heavy maintenance workload, short life, and easy electromagnetic interference caused by commutation sparks, which increase production costs and maintenance costs to a certain extent.

Traditional self-balancing vehicles have disadvantages such as poor battery life, low precision of the control system, and single functions.

[0003] Although there are many types of self-balancing vehicles on the market, most of them have deficiencies in motor control design. Traditional control methods are prone to balance accidents due to their own defects.

PID control, based on T_S fuzzy control, adaptive control, etc. all have the following defects: the control variable armature voltage indirectly controls the body balance, so it is difficult to guarantee the dynamic performance of the electric vehicle; the signal collected by the sensor has large noise and zero drift error ; Poor robustness, not suitable for the application of nonlinear systems

[0004] To sum up, the existing driving control methods of balancing vehicles do not comprehensively consider the tracking and monitoring of the performance of the permanent magnet synchronous motor by the controller, and often appear jitter, excessive deviation, and low safety during the implementation process. question

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