Research on adaptive LQR suspension attitude compensation control based on operating condition identification

To enhance vehicle comfort and roll behavior across varying driving conditions, an adaptive LQR suspension attitude compensation control strategy based on driving condition recognition is proposed. This method employs a fuzzy driving condition recognizer to assess driving aggressiveness in real time, dynamically adjusting the LQR weighting matrix to achieve an adaptive trade-off between comfort and stability. Concurrently, a fuzzy feedforward compensator is introduced to provide a rapid response to steering inputs, thereby enhancing roll resistance. MATLAB/Simulink simulations show that under step steering conditions, the adaptive control system achieves better attitude control and reduces roll acceleration by 56.6%. Under the double-lane-change condition, the adaptive control strategy reduces roll acceleration by 54.0% compared with the passive suspension. The results indicate that the proposed adaptive attitude control strategy significantly improves vehicle stability while maintaining ride comfort.