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This paper proposes the use of backstepping technique to address the stabilization problem of a dc-dc boost converter characterized by non-minimum phase property. The backstepping technique is used in conjunction with a disturbance observer to counteract the effect of model uncertainties and unmeasured disturbance. Therefore, not only does the developed controller achieve the task of stabilization, but it can also guarantee zero steady-state error in the presence of model uncertainties and unknown load. The asymptotic regulation of the composite controller follows from the integral action property of the disturbance observer. What is more interesting is that the composite controller can also compensate for the effect of control saturation during transients. This means that the proposed controller does not require an anti-windup scheme to maintain stable and graceful response during control saturation. Another feature of the proposed controller is its ability to achieve good tracking performances in response to a smooth voltage trajectory. Simulation and experimental tests have been conducted to investigate the performances of the proposed controller considering different operating conditions and different load types, including constant power load (CPL). The obtained results revealed that the proposed controller is able to achieve stable, accurate, and good response regardless of the load type.

This paper presents the design and real-time implementation of a composite controller consisting of a state-feedback control law and high-gain observer for grid-tied inverter with LCL filter. The state-feedback controller is designed in the $dq$ reference frame to stabilize the closed-loop system. High-gain observer serves as a disturbance observer to estimate a fictitious variable, representing the effect of model uncertainties and unknown disturbances, which is then canceled by the state-feedback controller. Thus, asymptotic regulation can be guaranteed under the composite controller even in the presence of parametric uncertainties and unknown inputs. High-gain observer has a rate of convergence that is dependent on its gain which is required to be large enough to ensure fast disturbance estimation, and then nominal performance recovery. However, high observer gain can lead to poor steady-state performances due to the effect of measurement noise. This concern is overcome in this work by using an existing adaptive technique to adjust the observer gain on-line. Moreover, the resulting high-gain observer is further simplified to provide a less-complex estimator and to show its integral action property. The performance of the composite controller was experimentally tested. The obtained results demonstrated the ability of the proposed controller to meet the nominal performance specifications while reducing the effect of measurement noise in steady-state.