This paper studies the problem of the parameter estimation for control systems by means of the discrete observations under a sine excitation signal. In order to seize the dynamical characteristics of systems and obtain higher estimation accuracy, an objective function by using the dynamical data is constructed and optimized by the negative gradient search. For the purpose of obtaining fast convergence speed, a conjugate gradient algorithm is developed to estimate the system parameters, in which the search direction, i.e., the step-size can be determined in accordance with the variation of the objective function. Finally, a numerical example is provided to test the performance to the proposed method and the simulation results show that the presented algorithm based on the conjugate gradient is effective for process systems.
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