Reliability of Dynamic Load Scheduling with Solar Forecast Scenarios

This paper presents and evaluates the performance of an optimal scheduling algorithm that selects the on/off combinations and timing of a finite set of dynamic electric loads on the basis of short term predictions of the power delivery from a photovoltaic source. In the algorithm for optimal scheduling, each load is modeled with a dynamic power profile that may be different for on and off switching. Optimal scheduling is achieved by the evaluation of a user-specified criterion function with possible power constraints. The scheduling algorithm exploits the use of a moving finite time horizon and the resulting finite number of scheduling combinations to achieve real-time computation of the optimal timing and switching of loads. The moving time horizon in the proposed optimal scheduling algorithm provides an opportunity to use short term (time moving) predictions of solar power based on advection of clouds detected in sky images. Advection, persistence, and perfect forecast scenarios are used as input to the load scheduling algorithm to elucidate the effect of forecast errors on mis-scheduling. The advection forecast creates less events where the load demand is greater than the available solar energy, as compared to persistence. Increasing the decision horizon leads to increasing error and decreased efficiency of the system, measured as the amount of power consumed by the aggregate loads normalized by total solar power. For a standalone system with a real forecast, energy reserves are necessary to provide the excess energy required by mis-scheduled loads. A method for battery sizing is proposed for future work.Comment: 6 pager, 4 figures, Syscon 201

Control of linear switched systems using state feedback with saturation constraints

This thesis considers the stabilization of discrete time switched systems using average output variance as the performance criterion, incorporating actuator saturation constraints into this optimal synthesis. Necessary and sufficient conditions are presented for the existence of a stabilizing static state feedback controller subject to saturation constraints, together with a constructive method to find this controller. These are presented as semi-definite optimization problems

Hybrid modeling and control of mechatronic systems using a piecewise affine dynamics approach

This thesis investigates the topic of modeling and control of PWA systems based on two experimental cases of an electrical and hydraulic nature with varying complexity that were also built, instrumented and evaluated. A full-order model has been created for both systems, including all dominant system dynamics and non-linearities. The unknown parameters and characteristics have been identi ed via an extensive parameter identi cation. In the following, the non-linear characteristics are linearized at several points, resulting in PWA models for each respective setup. Regarding the closed loop control of the generated models and corresponding experimental setups, a linear control structure comprised of integral error, feed-forward and state-feedback control has been used. Additionally, the hydraulic setup has been controlled in an autonomous hybrid position/force control mode, resulting in a switched system with each mode's dynamics being de ned by the previously derived PWA-based model in combination with the control structure and respective mode-dependent controller gains. The autonomous switch between control modes has been de ned by a switching event capable of consistently switching between modes in a deterministic manner despite the noise-a icted measurements. Several methods were used to obtain suitable controller gains, including optimization routines and pole placement. Validation of the system's fast and accurate response was obtained through simulations and experimental evaluation. The controlled system's local stability was proven for regions in state-space associated with operational points by using pole-zero analysis. The stability of the hybrid control approach was proven by using multiple Lyapunov functions for the investigated test scenarios.publishedVersio

Towards a Taylor-Carleman bilinearization approach for the design of nonlinear state-feedback controllers

The Carleman bilinearization is an approach that performs an exact conversion of a finite-dimensional nonlinear system into an infinite-dimensional bilinear system. A finite-dimensional system is later obtained through a truncation for analysis and control purposes. This paper investigates the linear matrix inequality (LMI)-based design of a switched state-feedback control law for the model obtained via Carleman bilinearization of a first-order nonlinear system. It is shown that in order to obtain feasible design conditions, the performance requirements must be relaxed in a neighborhood of the zero equilibrium point, so that problems arising from the uncontrollability of the linear part of the model can be avoided. The effectiveness of the proposed approach is shown using a numerical example and experimental results using a multi-input tank system.publishedVersio

Towards an access economy model for industrial process control

With the ongoing trend in moving the upper levels of the automation hierarchy to the cloud, there has been investigation into supplying industrial automation as a cloud based service. There are many practical considerations which pose limitations on the feasibility of the idea. This research investigates some of the requirements which would be needed to implement a platform which would facilitate competition between different controllers which would compete to control a process in real-time. This work considers only the issues relating to implementation of the philosophy from a control theoretic perspective, issues relating to hardware/communications infrastructure and cyber security are beyond the scope of this work. A platform is formulated and all the relevant control requirements of the system are discussed. It is found that in order for such a platform to determine the behaviour of a controller, it would need to simulate the controller on a model of the process over an extended period of time. This would require a measure of the disturbance to be available, or at least an estimate thereof. This therefore increases the complexity of the platform. The practicality of implementing such a platform is discussed in terms of system identification and model/controller maintenance. A model of the surge tank from SibanyeStillwater’s Platinum bulk tailings treatment (BTT) plant, the aim of which is to keep the density of the tank outflow constant while maintaining a steady tank level, was derived, linearised and an input-output controllability analysis performed on the model. Six controllers were developed for the process, including four conventional feedback controllers (decentralised PI, inverse, modified inverse and H¥) and two Model Predictive Controllers (MPC) (one linear and another nonlinear). It was shown that both the inverse based and H¥ controllers fail to control the tank level to set-point in the event of an unmeasured disturbance. The competing concept was successfully illustrated on this process with the linear MPC controller being the most often selected controller, and the overall performance of the plant substantially improved by having access to more advanced control techniques, which is facilitated by the proposed platform. A first appendix presents an investigation into a previously proposed switching philosophy [15] in terms of its ability to determine the best controller, as well as the stability of the switching scheme. It is found that this philosophy cannot provide an accurate measure of controller performance owing to the use of one step ahead predictions to analyse controller behaviour. Owing to this, the philosophy can select an unstable controller when there is a stable, well tuned controller competing to control the process. A second appendix shows that there are cases where overall system performance can be improved through the use of the proposed platform. In the presence of constraints on the rate of change of the inputs, a more aggressive controller is shown to be selected so long as the disturbance or reference changes do not cause the controller to violate these input constraints. This means that switching back to a less aggressive controller is necessary in the event that the controller attempts to violate these constraints. This is demonstrated on a simple first order plant as well as the surge tank process. Overall it is concluded that, while there are practical issues surrounding plant and system identification and model/controller maintenance, it would be possible to implement such a platform which would allow a given plant access to advanced process control solutions without the need for procuring the services of a large vendor.Dissertation (MEng)--University of Pretoria, 2020.Electrical, Electronic and Computer EngineeringMEngUnrestricte