The design and integration of a software configurable and parallelized coprocessor architecture for LQR control

An implementation of optimal control methods (LQI, LQG, LTR) for geostationary satellite attitude control

“…There are many methods available of calculating and minimizing the expected cost E[J]. The implementation of a LQG control design method [23] to linearized port Hamiltonian system defined by (6) to derive the dynamic observer based controller Figure 5. Where the state of the controller x represents the estimation of the state x of the system, the feedback gains are:…”

“…The attitude control of geostationary spacecrafts [1][2][3][4], has important applications for telecommunication space missions such as pointing and for motion flying, the Attitude Determination and Control Subsystem (ADCS) provides attitude information and maintains the required spacecraft attitude during all phases of the mission, starting at spacecraft separation from the launch vehicle and throughout its operational lifetime [5][6][7][8].The selection of an ADCS is a function of many factors, Including mission objectives, satellite design, distributions torques, design constraints and stabilization required. Several control methods have been developed over the past years since the first satellite was launched.…”

Hardware/Software frameworks for control techniques to support real-time systems and runtime verification

“…The loop terminates when H RV future steps have been reached. There exist fully pipelined hardware architecture [139] for LQR and architecture [140] for MPC using the method of ADMM [95]. The clever twist here is that the computation of the state-space model, LQR, and MPC can all be converted into the matrix-vector multiplication (MVM) (MPC involves extra operations "Saturation and Dual" after the MVM) as is shown in Table 6.1.…”

“…There are many solutions to speed up the MVM. Here we use the solution from [139], which adopts the MVM tree and the reduce circuit [145] to adjust the computation parallelism to meet system requirements.…”

“…The transform equation Table 6.1: Model predictor in MVM form. Refer [139,140] for the explanation of those parameter matrices.…”