<p>This work presents an integral-order compensator-based control design for a Lane Keeping Assistance System (LKAS), with emphasis on enhancing robustness against unmodelled dynamics and parametric sensitivity. To address the challenge of degraded lane-keeping performance under such conditions, the proposed approach enforces a flat Bode phase plot, where the phase derivative with respect to frequency becomes zero at a specific frequency, thereby improving system robustness. Previous methods, such as fractional-order PID controllers, have attempted to achieve phase flatness and iso-damping but often faced limitations due to their complexity and the time required to realize optimal phase characteristics across a broad frequency range. To overcome these limitations, particle swarm optimization (PSO) is employed to fine-tune the compensator parameters. By integrating PSO with the baseline design, optimal values are efficiently determined to ensure both a flat Bode phase profile and an iso-damped response. A PID controller tuned via genetic algorithm (GA), together with the PSO-optimized compensator, achieves the desired iso-damped step response. The effectiveness of the proposed controller is validated through extensive simulations on a nonlinear vehicle model under varying road friction conditions and parametric uncertainties. Although the controller is derived from a linearized LKAS model, it demonstrates robust applicability to real-world conditions. Comparative analysis against conventional PID and fuzzy PID controllers shows that the proposed design achieves the lowest root-mean-square values for lateral deviation (0.0907 m), yaw error (0.0282 rad), and lateral acceleration (0.5372 m/s²), confirming its effectiveness in ensuring robust LKAS performance.</p>