An Adaptive Robust Guidance Strategy for Interceptor with Input Quantization

Abstract The computational capabilities of processors have increased many folds over the last few decades. However, due to constraint on space, weight, and cost, the state-of-art onboard processors cannot be generally installed in a missile, which is required to perform multiple parallel computations for a successful interception. An efficient way of minimizing the computational burden can be ensured by reducing the number of updates of the control input, thereby minimizing the load on the onboard processors. A logarithmic quantizer technique is explored in this work for designing a guidance strategy for a two-dimensional interceptor problem. The proposed guidance strategy is capable of tackling disturbances and quantization errors while achieving the primary objective of capturing the target. An adaptive law has also been incorporated to eliminate the need of apriori knowledge about the disturbance bound. Lyapunov theory has been used to show Uniformly Ultimately Bounded (UUB) convergence of the closed-loop system states under the application of the quantized control approach. The proposed scheme is implemented through numerical simulations for the tail-chase and headon engagement scenarios. A comparative analysis of the proposed guidance strategy with the periodic sampling time technique is also included in this work.