Mehrjardi et al. Table 1. Summaries of Some Popular Spacecraft Control Algorithms Control Technique Multiple-Input Multiple-Output (MIMO) Research Methodology Advantage Extending the frequency-domain methodology System representation in terms of vectors and matrices Disadvantage Ref. Optimality and stability Highest information requirements [62]-[64] Singular values are an effective measure of gain Eigenvalues are a poor measure of gain Cross coupling between inputs and outputs Single-Input SingleOutput (SISO) Control system in frequency domain using Nyquist and Bode diagrams High performance and robustness - [65], [66] Linear Quadratic Gaussian (LQG) Kalman filter to estimating plant states and LQR Time-varying feedback State feedback in linear plant [67], [68] PID Development of the pole-placement theory Robustness and simplicity Tuning of the control parameters [69]-[77] Linear Quadratic Regulator (LQR) State space and timedomain framework High stability Usually, state must be estimated (such as Kalman filter) [78]-[80] Optimal control Need accurate model of the system obtaining an analytical solution to the Ricatti equation Table 2. The Optimization Algorithms in the Controller Techniques Ref. Optimization Algorithms [82] GA Fuzzy Logic Control (FLC) and PI Interface card [83] GA PI MATLAB/Simulink [84] GA FLC DSP [85] GA Sliding MATLAB/Simulink [86] GA PI - [87] PSO intelligent model MATLAB/Simulink [88] PSO FLC - [89] PSO FLC MATLAB/Simulink [90] PSO ANFIS MATLAB/Simulink [91] PSO FLC MATLAB/Simulink [92] BSA State feedback control law MATLAB/Simulink [93] BSA PI and PID MATLAB/Simulink JULY 2018 Controller Techniques IEEE A&E SYSTEMS MAGAZINE Platform 67