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Abstract In this thesis,we present the parameter adaptive self-tuning controllers for single-input single-output systems with known and unknown orders.Combinations of different estimation methods and control algorithms are simulated.The exyension to the multivariable case is also presented and simulation examples are given for testing the control algorithms.Also we studied the parameter adaptive self-tuning controllers for single input single output systems with unknown orders.We suggested and introduced a modified criterion[3] o chen’s work[15]to estimate the orders.Hence the Adaptive control is designed for output tracking,deadbeat,PID,and minimum variance controllers.Simulation examples are introduced to compare between the modified algorithm and the algorithm introduced by Chen[15].the overall results obtained showed better convergence for the parameters and orders in addition to smooth output and control signals for some control algorithms.This thesis is divided into six chapters and four appendices.Chapter one is devoted to the introduction there given a historical survey,the review of literature and thesis organization. Chapter two presents the background needed for system identification and adaptive control systems.The probability background to generate normal deviates white gaussian noise and the wiener process is also presented. |