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Recently introduced Colonial Competitive Algorithm (CCA) has shown its excellent capability on diverse optimization tasks. This optimization algorithm is inspired by socio-political process of imperialistic competition. In this study a uniform linear array (ULA) adaptive antenna that uses this global search heuristic is developed. The obtained results are compared with those of a Genetic Algorithm (GA) and Least Mean Square (LMS). The evolutionary algorithms are applied to the problem of beamforming in two separate parts based on minimizing signal-to-interference-plus-noise-ratio (SINR). First the antenna array is considered static. In the second part the antenna is assumed to be dynamic and is moving with a constant speed that an optimization task with a cost function varying over the time. The results show not only GA and CCA perform better than LMS in both parts, but also CCA outperforms GA and LMS in these parts.

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This paper presents an application of adaptive control techniques to the design of skid-to-turn missile autopilot. The involved simplified adaptive controller is developed by combining gain scheduling approach with the eigenstructure assignment control design. A linear interpolation method is proposed to generate linear parameter-varying controller from a finite set of linear time-invariant controllers. Results of simulations are reported to demonstrate the performance, stability, and robustness of the considered autopilot.