Particle Swarm Optimization (PSO) tuned Linear Quadratic Gaussian (LQG) Controller Design for Surface to Air Missile Guidance System
| dc.contributor.advisor | Dereje Shiferaw (PhD) | |
| dc.contributor.author | Getasew Mekonnen | |
| dc.date.accessioned | 2024-09-03T08:21:32Z | |
| dc.date.available | 2024-09-03T08:21:32Z | |
| dc.date.issued | 2018-06 | |
| dc.description.abstract | Missile guidance system is a well-known nonlinear control engineering area of research. Many technologies have been developed to improve control performance, robustness and to overcome environmental disturbances. This thesis employs a particle swarm optimization (PSO) algorithm to solve the weighting matrices selection problem of linear quadratic Gaussian (LQG) for controlling surface to air Missile guidance system. One of the major challenges in the design of LQG for real time applications is the optimal choice of the state and input weighting matrices (Q and R) respectively, which play a vital role in determining the performance and optimality of the controller. Commonly, trial and error approach is employed for selecting the weighting matrices, which not only burdens the design but also results in non-optimal response. Hence, to choose the elements of Q and R matrices optimally, a PSO algorithm is formulated and applied in the design of linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) for control of surface to air Missile. It is also intended to produce better robustness with the help of particle swarm optimization (PSO) algorithm as an optimization tool. Indeed, the system’s mathematical model has been developed and also the properties of the uncontrolled system have been analyzed. The model developed shows that the Missile system considered is a 2x2 MIMO (multiple input multiple output) system. Since the system is MIMO, the interaction of the inputs with the outputs has been analyzed using relative gain array (RGA) analysis and frequency domain analysis of the system transfer functions. Also, the condition number of the missile system is calculated and it has small value i.e. “1” which implies there is no control problem for the plant. Then, optimal state feedback controllers have been developed. Here, LQR and LQG controllers are developed. The performance of the controllers designed by manual tuning and PSO-tuning has been analyzed and compared. Besides the performance, the robustness of the controllers developed has been analyzed. The robustness analysis is done by evaluating the singular values of the loop gains using singular value decomposition (SVD) at a certain frequency and for a specified frequency range. Finally, comparative analysis between the designed controllers is carried out. The proposed PSO tuned design methodology has resulted good Performance i.e. The PSO tuned LQR and LQG controller improved the steady state error and peak response from (0.1043 to 0), (1.043 to 1) and (0.1723 to 0), (1.1723 to 1) m/s2 respectively in Y direction. In addition, the PSO tuned design has also resulted improvements in robustness of the control systems i.e. The PSO and manually tuned LQG PM is 65.0010and 30.31220 respectively. Indeed, the loop transfer recovery (LTR) approach is employed at the input to recover the robustness of the manual linear quadratic Gaussian (LQG) controller, which resulted in the improvement of the robustness at the input i.e. the singular value increases or altered from -17.345dB to -5.625dB. The thesis has also suggested further research work in the control of Missile system. | |
| dc.identifier.uri | https://etd.aau.edu.et/handle/123456789/3453 | |
| dc.language.iso | en_US | |
| dc.publisher | Addis Ababa University | |
| dc.subject | PSO | |
| dc.subject | LQR | |
| dc.subject | Kalman filter | |
| dc.subject | LQG | |
| dc.subject | LTR | |
| dc.subject | RGA | |
| dc.subject | Surface to air Missile. | |
| dc.title | Particle Swarm Optimization (PSO) tuned Linear Quadratic Gaussian (LQG) Controller Design for Surface to Air Missile Guidance System | |
| dc.type | Thesis |