ABSTRACT
Chapter 13 discusses model predictive control (MPC) and its application to the spacecraft attitude control problems. Since MPC needs extensive on-board computation, it was not widely used in spacecraft control. As more powerful computers are installed on spacecraft, MPC is expected to find more applications in aerospace in the future. Section 13.1 provides some technical lemmas that will be used in the rest of the chapter. Section 13.2 establishes the relation between constrained MPC and convex quadratic programming (QP) with box constraints. Section 13.3 introduces central path concept and interior-point method that will be used in the following sections. Section 13.4 proposes an efficient interior-point algorithm for the convex QP problem with box constraints. Section 13.5 provides the detailed convergence analysis. Implementation issues are presented in section 13.6, including an explicit feasible initial point, which makes it possible to use more efficient feasible interior-point algorithms. Section 13.7 considers again the orbit-raising attitude control problem with constraint on thruster power. This control system design problem is used to demonstrate that MPC is a more powerful design tool than the traditional LQR optimal control system design. Most mathematical proofs are given in section 13.8 to enhance the readability of the chapter.
