Attitude Control Of Satellite Using Computationall

Abstract

Attitude control System (ACS) of spacecraft performs the attitude control to counter the effects of disturbances present in the space environment. MPC (Model Predictive Control), controller is a control algorithm which uses the mathematical model of the plant and also considers input and output constraints for the calculation of optimal control law in real-time. The issues with the conventional MPC are its computational time and feasibility at each sampling instant. The larger computational time and infeasible optimization solution in real-time applications is a cause of concern. Previous work has only considered the implementation of MPC by considering the inputs constraints. The use of MPC to consider output constraints and effect of feasibility and computation time has not been explored. Therefore computationally efficient two variant algorithms of MPC i.e., Optimal MPC (OMPC) and Laguerre OMPC (LOMPC), have been selected as control algorithms to study feasibility and computational time by linking dual mode, closed-loop paradigm and Laguerre function techniques for linear and non-linear model. Linear model approximates non-linear model because of small angle approximations. Also changes in satellites attitude angles because of disturbances fall in the domain of small angles approximation regions. The effect of changing the position of Laguerre Poles on the closed loop performance and computation time was explored. The input constraints were considered on the control torque, whereas output constraints were considered for roll, pitch and yaw angles. The conclusion is that the in the case of linear approximated model, use of OMPC algorithms with Laguerre functions improves computational time. Both OMPC and LOMPC do not affect the closed loop performance even if infeasible solutions are produced. When OMPC and LOMPC algorithms were applied to the non-linear model, diverging non-zero steady-state errors were introduced and plant became unstable. It was evident from the results that OMPC and LOMPC were not able to control the non-linear model.