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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.

A redundant Inertial Measurement Unit (IMU) is an inertial sensing device composed of more than three accelerometers and three gyroscopes. This paper analyses the performance of redundant IMUs and their various sensor configurations. The inertial instruments can achieve high reliability for long periods of time only by redundancy. By suitable geometric configurations it is possible to extract the maximum amount of reliability and accuracy from a given number of redundant single-degree-of-freedom gyros or accelerometers. This paper gives a general derivation of the optimum matrix which can be applied to the outputs of any combination of three or more sensors to obtain three orthogonal vector components based on their geometric configuration and error characteristics. Certain combinations of four or more instruments are able to detect an instrument malfunction, and combinations of five have the additional capability of isolating that malfunction to a particular sensor. Finally, this paper offers a major improvement in reliability, although the improvement in accuracy is minor.

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Development of time-optimal strategy for non-linear problem of planetary landing mission by using perturbation technique is investigated on two scenarios in this study. The first scenario includes finding an optimal control policy for descent in the variable gravitational field of the target planet analytically. In the second scenario, the optimal policy is derived by considering the effect of spacecraft mass variations in an analytic solution. To validate the accuracy of each generated policy, a numeric method such as steepest descent is employed. Afterwards, the fuzzy algorithm is followed to achieve the closed-loop guidance strategy for this non-linear system. The training process of the fuzzy system is based on the achieved perturbation solution of variable mass landing problem by utilizing a set of states-related non-dimensional variables for faster convergence rate. Finally, the lunar landing mission is demonstrated as a viable example of the non-linear planetary landing mission. Simulation results show that the presented optimal guidance laws are so effective which can be utilized in the real world spacecraft applications.

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