A gas-lifted system in a mature oil well can experience casing-heading instability, which reduces the mean oil production and it is not healthy for the downstream equipment. This instability was removed by implementing a terminal equality-constrained nonlinear model predictive control (NMPC) having input targets with control zones in the system. The input-dependent stability behaviour of the gas-lifted system was visualised through the bifurcation diagram and the step responses of the linearised model at various operating points. The controller was then presented. Then, the close-loop feasibility, as well as the convergence, were discussed. The controller stabilised the undisturbed gas-lifted system, improving production by 5.63% compared to the open-loop operation when the system was in casing-heading instability. For the two input case, the steady-state production, aided by the high-input target, reached 12.25 kg/s, which was far more than 9.57 kg/s for the one input case. This controller showed a 3.76% improvement over the PI controller for the same purpose.

The gas-lifted system has inherent ability to hide the effect of fault hence the system can inject gas into the annulus and oil will still be produced even in the presence of fault of significant value. This however affects the optimal operation of the system and could move the system towards the undesirable casing-heading instability. Faults of step decrease in the valves coefficients in addition to limitation on the valve affect the optimal flow of the liquids through the system. We detect and isolate these faults using generalised likelihood ratio test (GLRT) and Dedicated observer scheme (DOS) respectively. The states of the system are estimated using extended Kalman filter (EKF). Model predictive control based fault-tolerant control is then implemented on the system by using the robustness property of the zone control MPC and limiting the input bound in the optimiser. Both passive and active fault-tolerant control (FTC) were used to improve oil production or stabilise the system. Passive fault-tolerant control (FTC) provides more robustness but it does not change oil production noticeably enough. Reducing the upper control bound ensures stability but production could decline. Increasing the controller cost that prioritises the input target increases production but it is prone to casing-heading instability.

The focus of this work is the extension of nonlinear state estimation methods to gas-lifted systems. The extended Kalman filter (EKF), unscented Kalman filter (UKF) and particle filter (PF) were used to estimate the nonlinear states. Brief descriptions of the filters were first presented starting from the linear Kalman filter. Hypothesis tests on the expectation of the residuals were performed to show how close to optimal the estimation methods are and it showed the UKF estimates to be slightly better than EKF while PF performs the worst. The PF has poor accuracy using residual visualisation, hypothesis test and the root mean squared error (RMSE) values of the residuals. The gas-lifted system exhibits casing heading instability where the states show oscillatory behaviour depending on the value of the input but the results here do not change in a known way for each filter as the input is changed from the non-oscillatory region to the oscillatory region. Therefore, for this noise distribution and model assumption, either the EKF or UKF can be used for nonlinear state estimation with UKF better preferred if computational cost is not considered when control solutions are used in gas-lifted system.

The permanent magnet synchronous motor (PMSM) is usually deployed as an actuator in applications where precision is a top priority. However, in applications requiring better power density, higher torque to inertia ratio, and more torque per unit supplied power, among others, brushless direct current (BLDC) motor is more applicable than a PMSM. The PMSM precision is improved by the complex field-oriented control (FOC). Although the BLDC motor is controlled by trapezoidal commutation which reduces precision, it can also be controlled by FOC with improved precision compared with trapezoidal control. Each positioner of the Multi-Object Spectrograph for Astrophysics, Intergalactic-medium studies and Cosmology, an instrument for the Extremely Large Telescope (ELT) deploys five motors as actuators to actuate the robot joints, the pickoff mirror, and the atmospheric dispersion corrector prisms. The tight constraints in the ELT require the advantages of the BLDC motor and the FOC; hence, the need to examine how close the performance of the FOC-controlled BLDC motor approaches the FOC-controlled PMSM for deployment in the positioner subsystem. It is shown in this article that the performance of the FOC-controlled BLDC motor is nearly identical to that of the FOC-controlled PMSM in terms of kinematic variables such as speed and position tracking. The FOC-controlled BLDC motor outperforms the FOC-controlled PMSM by 16.5%, 71.3%, 26.4%, 68.0%, and 49.55% in dynamic ratio variables or energy ratio variables such as torque per input power, torque per inertia, mean positive volumetric power density, mean positive gravimetric power density, and heat produced per torque, respectively. FOC-controlled BLDC motor can therefore be used for actuating the positioner subsystem because the performance in the kinematic metrics approaches FOC-controlled PMSM while having better performance in metrics related to energy ratio or dynamic ratio variables.