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The paper presents a state-space approach for dealing with self-tuning control problems. A joint algorithm for system-parameter identification and system-state estimation is derived. With the joint algorithm, modern control techniques can be easily applied to systems having stochastic disturbances. The state-space version of the self-tuning control with pole assignment is investigated. Based on the state-space approach, the proposed self-tuning control algorithm can be applied to time-invariant linear systems including the unstable and nonminimum-phase systems.