Recursive algorithms for on-line combined identification and control of linear discrete-time multivariable systems is presented. A variant of the observable canonical model with one-way coupling form of the state model is used to develop a solution of the problem. Exploiting the canonical structure of the model, the proposed solution turns out to be simpler than that obtained by El-Sherief (1983) and moreover, a combined decentralized state and parameter estimation based control scheme can be developed in three stages. In Stage I, the parameters of the system matrices are estimated by a recursive least-square algorithm or by a normalized stochastic approximation algorithm in decoupled manner. These parameters are then employed for state estimation in Stage 2 using a centralized conventional Kalman filter or by a decentralized adaptive Kalman filter which in turn reduces instrumentation and telemetry costs. Estimated parameters and states are then utilized in Stage 3 to implement the square-root based control law along with the good numerical behaviour of the control problem. The proposed algorithms are tested by considering an example of a third-order state-space model.