This thesis describes new developments in nonlinear controllers for industrial applications. It first introduces the Nonlinear Generalised Minimum Variance (NGMV) control algorithm, for Linear Parameter Varying systems (LPV). This combines the benefits of the basic NGMV algorithm in dealing with nonlinearities, where a black box input model can be used, and adds an option to also approximate a nonlinear system with an LPV output subsystem. The models can therefore represent LPV systems and characteristics including saturation, discontinuities and time-varying dynamics. The next major contribution is in the nonlinear predictive control algorithms proposed that are also using the LPV model structure. The simplest is the Nonlinear Generalized Predictive Control (NGPC) algorithm that relates to the best known model predictive control law for linear systems. The final predictive control solution is one that may be specialized to either the NGMV or NGPC cases and is therefore the most general. This is referred to as a Nonlinear Predictive Generalized Minimum Variance Controller (NPGMV). When the algorithms use only the LPV structure to approximate the nonlinear system the solutions are particularly simple in unconstrained and constrained versions, and are relatively light computationally for implementation. Three representative industrial design examples have been chosen to validate the algorithms for different Bandwidth (BW) and nonlinear characteristics. All three examples were based on real application problems with company interest. In the first example (small BW) the basic state-space and LPV versions of the algorithm are used for the auto-manoeuvring and dynamic positioning of marine vessel. In this application the parameter variations were representative of wave disturbance changes with sea state, rather than due to approximating nonlinear behaviour.Actuator constraints were considered in the design. In the second industrial example (medium BW) the LPV-NPGMV was implemented for controlling the blade pitch and generator torque of a 5MW offshore wind turbine. The main objective here was to maintain the power produced at the rated value which requires compensation against wind disturbances, so that wind speed is the varying parameter. The LPV-NPGMV controller produced here used a parameterised system model involving the wind speed so that the controller performance changed with wind conditions. Actuator constraints were included and statistical performance assessed. The third example (fast BW) explores the stabilisation of a 2-axis gyroscopic electro-optical turret used in surveillance applications. This application was designed and employed on a real system. Because of the limitations imposed by BW requirements and the memory of the digital controller, only the basic state-space version of the algorithm was possible to implement. The main objective in this problem was to improve the tracking performance around the NADIR singularity point (a discontinuity) in the trajectory. In all three examples the NGMV controllers showed notable improvement in comparison to the baseline controllers without the need for scheduled gains or re-configuration when moving across different operating points.
|Date of Award||7 May 2017|
- University Of Strathclyde
|Supervisor||Michael Grimble (Supervisor) & Reza Katebi (Supervisor)|