Abstarct: Lyapunov theory was the only method to stabilize linear and nonlinear systems for a long time. Scientists knew the problems of this method after applying it in causal systems. One of the most important problems of this method is finding a control Lyapunov function. To solve this problem many methods were presented which one of them is backstepping method. In backstepping method with feedback states and combine them in a particular equations can stabilize system and find control Lyapunov function, but one of the problem of this method is limited range of systems that this method is used for them. In this thesis for solving this problem a new method is proposed. Because of similarity the baxse of new method to backstepping but expanded range of application this new method, this is called to "Generalized Backstepping Method". To show ability of this new method to control causal systems, chaos is selected as a case study and design controller with generalized backstopping method. Two chaotic systems are selected; one of them is SISO and other is MIMO. Controlling these systems has either stabilization or tracking input reference. Simulations prove the abilities of generalized backstepping method. Finally designed controller is optimized by using genetic algorithm.