In this paper, we investigate the challenges of controlling the ARAS-Diamond robot for robotic-assisted eye surgery. To eliminate the system’s inherent uncertainty effects on its performance, a cascade architecture control structure is proposed in this paper. For the inner loop of this structure, two different robust controls, namely, [Formula: see text] and μ-synthesis, with stability and performance analysis, are synthesized. The outer loop of the structure, on the other hand, controls the orientation of the surgical instrument using a well-tuned PD controller. The stability of the system as a whole, considering both inner and outer loop controllers, is analyzed in detail. Furthermore, implementation results on the real robot are presented to illustrate the effectiveness of the proposed control structure compared to that of conventional controller designs in the presence of inherent uncertainties of the system and external disturbances, and it is observed that using [Formula: see text] controller in the inner loop has superior robust performance.

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In this study, due to the innate trans-atmospheric nature of flight of the space transportation system, assessment of the control discipline interaction with aerodynamic, weights and sizing, external fin-stabilizers configuration, and trajectory disciplines in an multidisciplinary design optimization-based platform has been addressed. Parameters considered for the control sub-system optimization are external stabilizing fins geometrical characteristics and attitude control vernier motors thrust value. Specifically, this article addresses optimization of fin–body combinations with geometric constraints for minimizing control moment required by vernier motors as well as total possible control sub-system weight satisfying design constraints. Results show that using external stabilizer fins is not economical from energetic stand point for space transportation system, but is necessary for control subsystems when there are deflection constraints for vernier motors.

Robustness and reliability of the designed trajectory are crucial for flight performance of launch vehicles. In this paper, robust trajectory design optimization of a typical LV is proposed. Two formulations of robust trajectory design optimization problem using single-objective and multi-objective optimization concept are presented. Both aleatory and epistemic uncertainties in model parameters and operational environment characteristics are incorporated in the problem, respectively. In order to uncertainty propagation and analysis, the improved Latin hypercube sampling is utilized. A comparison between robustness of the single-objective robust trajectory design optimization solution and deterministic design optimization solution is illustrated using probability density functions. The multi-objective robust trajectory design optimization is executed through NSGA-II and a set of feasible design points with a good spread is obtained in the form of Pareto frontier. The final Pareto frontier presents a trade-off between two conflicting objectives namely maximizing injection robustness and minimizing gross lift-off mass of launch vehicle. The resulted Pareto frontier of the multi-objective robust trajectory design optimization shows that with 1% increase in gross mass, the robustness of the design point to the considered uncertainties can be increased about 80%. Also, numerical simulation results show that the multi-objective formulation is a necessary approach to achieve a good trade-off between optimality and robustness.

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