© 2019 Aliyu Bhar Kisabo, Aliyu Funmilayo Adebimpe and Sholiyi Olusegun Samuel. This open access article is distributed under a Creative Commons Attribution (CC-BY) 3.0 license. Journal of Aircraft and Spacecraft Technology Original Research Paper Pitch Control of a Rocket with a Novel LQG/LTR Control Algorithm Aliyu Bhar Kisabo, Aliyu Funmilayo Adebimpe and Sholiyi Olusegun Samuel Centre for Space Transport and Propulsion (CSTP), Epe Lagos-State Nigeria Article history Received: 06-02-2019 Revised: 11-02-2019 Accepted: 11-03-2019 Corresponding Author: Bhar Kisabo Aliyu Centre for Space Transport and Propulsion (CSTP) Epe Lagos-State Nigeria E-mail: aliyukisabo@yahoo.com Abstract: This paper presents the design, simulation and analysis of a novel LQG and LQG/LTR control algorithm for the pitch angle of a sounding rocket. These improved LQG and LQG/LTR control algorithms stem from the fact that a Riccati Differential Equation (RDE) rather than the popular Algebraic Riccati Equation (ARE) is used to obtaining the Kalman gain in the observer of the traditional Linear Quadratic Gaussian (LQG) control algorithm. Thus, eight (8) different controllers were design, simulated and analysed, three (3) of such controllers are novel and two out of these novel controllers were able to recover completely the robustness lost in the traditional LQG controller. All controllers synthesized were analysed using time response characteristics of closed-loop system and compared with the LQR and LQG control system. Using the LQR controller as the benchmark for best performance and the LQG as the worst. This study shows an application option that demonstrates optimal control system design in MATLAB/Simulink® and the approach put forward here proves to be very effective. Keywords: Rocket, LQG Control, LQG/LTR Control, Differential Riccatti Equation Introduction Classical control system design is generally a trial- and error process in which various methods of analysis are used iteratively to determine the design parameters of an “acceptable” system. Acceptable performance is genrally defined in terms of time and frequency domain criteria such as rise time, settling time, peak overshoot, gain and phase margin, and band width. To meet the demands of modern technology, different performance criteria must be satisfied, in a complex multiple-input multiple-out systems requirement. For example, the design of a spacecraft attitude control system that minimizes fuel expenditure is not amenable to solution by classical methods. A new and direct approach to the synthesis of these complex systems, called optimal control theory, has been made feasible by the development of digital computer. The objective of the optimal control theory is to determine the control signals that will cause a process to satisfy the physical constraints and at the same time minimize (or maximize) some performance criterion. In certain cases, the problem statement may clearly indicate what to select for a performance measure (Kirk, 1998). A lot of work has been done in the area of optimal controller design for aerospace vehicles (Jianqiao et al., 2011; Das and Halder, 2014; Moshen Ahmed et al., 2011; Liu, 2017; Zhang et al., 2016; Nair and Harikumar, 2015) but non derives it Kalman gain from a diffferential reccati equation as we will demonstrate in this study. Also, in previous works, the synthesied LQG/LTR (Barzanooni, 2015; Barbosa et al., 2016; Ishihara and Zheng, 2017) did not restore completely the robustenses of the LQR or that of the Kalman filter. The first stage of any control system theory is to obtain or formulate the system dynamics. There refers to modeling in terms of dynamical equations such as differential or difference equations. With such equations, the system is called the plant. This aspect has been addressed fully in Chapter One. In this Chapter, the realized plant will be used to design and analyse Optimal control algorithms (Brian and Moore, 1989) in MATLAB/Simulink ® . This chapter is divided into five sections. Section two presents the adotped mathematical model. In section three, stability analysis was done for the rocket mathematical model. Optimal Control theory was introduced in section four hence, the design of LQR, LQG and their two novel variants. Also, LQG/LTR was