Abstract: In view of the difficult problem of multi-disturbance control of coal mine belt conveyors, an intelligent collaborative control model fusing Improved Bird Swarm Algorithm (IBSA) and T-S fuzzy neural network is proposed. Through Gaussian-triangular mixture membership function, nonlinear working conditions are dynamically characterized, by combining time-delay compensation polynomials, the consequent parameters are optimized and adaptive reconstruction of the fuzzy rule library is achieved; A dual time scale optimization framework is established (macro IBSA structure optimization, micro gradient descent parameter update) and a vibration suppression module for vibration spectrum is integrated. The practical applications show that the band speed fluctuation is decreased by 68%, energy consumption is reduced by 4%, and the tension response time is shortened to 0.7 s when the system is under extreme working conditions. The spectral analysis shows that the suppression of mechanical resonance energy at 0.5-2 Hz reaches 56.6%, significantly improving disturbance resistance and operational efficiency.