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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.

The main function of the DC-DC converter in a grid-connected photovoltaic (PV) system is to regulate the terminal voltage of the PV arrays to ensure delivering the maximum power to the grid. The purpose of this paper is to design and practically implement a robust continuous-time model predictive control (CTMPC) for a dc-dc boost converter, feeding a three-phase inverter of a grid-connected PV system to regulate the PV output voltage. In CTMPC, the system behavior is predicted based on Taylor series expansion, raising concerns about the prediction accuracy in the presence of parametric uncertainty and unknown external disturbances. To overcome this drawback, a disturbance observer is designed and combined with CTMPC to enhance the steady-state performance in the presence of model uncertainty and unknown disturbance such as the PV current, which varies nonlinearly with the operating point. An interesting feature is that the composite controller reduces to a conventional PI controller plus a predictive term that allows further improvement of the dynamic performance over the whole operating range. The effectiveness of the proposed controller was tested numerically and validated experimentally with the consideration of the grid-connected PV inverter system and its controller.

Abstract: A nonlinear predictive controller (NPC) for a permanent magnet synchronous motor (PMSM) is proposed in this paper. Its objective is high performance tracking of the rotor speed trajectory while maintaining the d-axis component of the armature current at zero. The load torque and the mismatched parameters are considered to be unknown perturbations. To ensure robustness against these perturbations, a disturbance observer is designed using a new gain function, and integrated into the control law. The combination of the nonlinear predictive controller and the disturbance observer works as a nonlinear controller. The overall closed-loop system is proved to be globally asymptotically stable depending on the design parameters. The validity of the proposed controller was tested by simulations. Satisfactory results were obtained with respect to the tracking of the speed trajectory and disturbance rejection. [ABSTRACT FROM AUTHOR]

Abstract Artificial gas-lift (AGL) is one of the most widely used methods in oil production to maintain acceptable oil flow to the processing equipment and sales when the reservoir pressure is not high enough. In spite of its popularity, the AGL process is prone to casing-heading instability, which is revealed as significant flow oscillation. This is undesirable as it results in production losses and unstable behavior that has negative impact on the downstream equipment. Controller design for such a process is very challenging as it exhibits highly nonlinear dynamics. In this work, the predictive generalized minimum variance control (NPGMV) is employed to derive a robust controller based on the state estimation to stabilize AGL process when casing-heading phenomenon occurs. A closed-form optimal control law is obtained based on the Taylor series approximation. Further, a nonlinear state observer is produced and combined with the controller to ensure closed-loop control through variables that are most beneficial to the system performance, which are unmeasurable and can be obtained only via estimation. Through simulation studies, the effectiveness of the proposed controller is demonstrated. [ABSTRACT FROM AUTHOR]