This paper presents an evolutionary algorithm with a new goal-sequence domination scheme for better decision support in multi-objective optimization. The approach allows the inclusion of advanced hard/soft priority and constraint information on each objective component, and is capable of incorporating multiple specifications with overlapping or non-overlapping objective functions via logical "OR" and "AND" connectives to drive the search towards multiple regions of trade-off. In addition, we propose a dynamic sharing scheme that is simple and adaptively estimated according to the on-line population distribution without needing any a priori parameter setting. Each feature in the proposed algorithm is examined to show its respective contribution, and the performance of the algorithm is compared with other evolutionary optimization methods. It is shown that the proposed algorithm has performed well in the diversity of evolutionary search and uniform distribution of non-dominated individuals along the final trade-offs, without significant computational effort. The algorithm is also applied to the design optimization of a practical servo control system for hard disk drives with a single voice-coil-motor actuator. Results of the evolutionary designed servo control system show a superior closed-loop performance compared to classical PID or RPT approaches.

The ever increasing demand for higher storage capacity and smaller magnetic hard disk drives have driven the need of developing a high performance head positioning servo control system. To meet the challenge, this paper presents the design and real-time implementation of a robust two-degree-of-freedom servo system for physical 3.5-in. hard disk drive with single voice-coil-motor actuator using a multi-objective evolutionary algorithm toolbox. Besides the simplicity in controller structure, such an evolutionary servo control system is capable of meeting various performance specifications of hard disk drives in both the time and frequency domains. It is shown that the servo system optimally moves the magnetic head onto the desired track with minimal control effort, and keeps it on the track robustly against plant uncertainties or runout disturbances. Validation results of the evolutionary servo control system are compared with classical PID and RPT controllers, which show excellent closed-loop response and robustness in the face of practical perturbations in HDD.

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