Supervisory control of switching control systems

In this thesis, we show that the problem of designing a switching policy for an adaptive switching control system can be formulated as a problem of Supervisory Control of a Discrete-Event System (DES). Two important problems in switching control are then addressed using the DES formulation and the theory of supervisory control under partial observation. First we examine whether for a given set of controllers, a switching policy satisfying a given set of constraints (on the transitions among controllers) exists. If so, then we design a minimally restrictive switching policy. Next, we introduce an iterative algorithm for finding a minimal set of controllers for which a switching policy satisfying the switching constraints exists. In our study we show that in the supervisory control problem considered in this thesis, limitation on event observation is the factor that essentially restricts supervisory control. In other words, once observation limitations are respected, limitation on control will be automatically satisfied. We use the above result to simplify our iterative algorithm for finding minimal controller set

Adaptive supervisory switching control system design for active noise suppression of duct-like application

Active noise suppression for applications where the controlled system response varies with time is a difficult problem, especially for time varying nonlinear systems with large model error. On the basis of adaptive switching supervisory control theory, an adaptive supervisory switching control algorithm is proposed with a new controller switching strategy for active noise suppression of duct-like application. Real time experimental verification tests show that the proposed algorithm is effective with good noise suppression performance

Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems

The first-ever Ukraine cyberattack on power grid has proven its devastation by hacking into their critical cyber assets. With administrative privileges accessing substation networks/local control centers, one intelligent way of coordinated cyberattacks is to execute a series of disruptive switching executions on multiple substations using compromised supervisory control and data acquisition (SCADA) systems. These actions can cause significant impacts to an interconnected power grid. Unlike the previous power blackouts, such high-impact initiating events can aggravate operating conditions, initiating instability that may lead to system-wide cascading failure. A systemic evaluation of "nightmare" scenarios is highly desirable for asset owners to manage and prioritize the maintenance and investment in protecting their cyberinfrastructure. This survey paper is a conceptual expansion of real-time monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework that emphasizes on the resulting impacts, both on steady-state and dynamic aspects of power system stability. Hypothetically, we associate the combinatorial analyses of steady state on substations/components outages and dynamics of the sequential switching orders as part of the permutation. The expanded framework includes (1) critical/noncritical combination verification, (2) cascade confirmation, and (3) combination re-evaluation. This paper ends with a discussion of the open issues for metrics and future design pertaining the impact quantification of cyber-related contingencies

New Topologies and Advanced Control of Power Electronic Converters for Renewable Energy based Microgrids

Solar energy-based microgrids are increasingly promising due to their many features, such as being environmentally friendly and having low operating costs. Power electronic converters, filters, and transformers are the key components to integrate the solar photovoltaic (PV) systems with the microgrids. The power electronic converters play an important role to reduce the size of the filter circuit and eliminate the use of the bulky and heavy traditional power frequency step-up transformer. These power converters also play a vital role to integrate the energy storage systems such as batteries and the superconducting magnetic energy storage (SMES) unit in a solar PV power-based microgrid. However, the performance of these power converters depends upon the switching technique and the power converter configuration. The switching techniques can improve the power quality, i.e. lower total harmonic distortion at the converter output waveform, reduce the converter power loss, and can effectively utilize the dc bus voltage, which helps to improve the power conversion efficiency of the power electronic converter. The power converter configuration can reduce the size of the power converter and make the power conversion system more efficient. In addition to the advanced switching technique, a supervisory control can also be integrated with these power converters to ensure the optimal power flow within the microgrid. First, this thesis reviews different existing power converter topologies with their switching techniques and control strategies for the grid integration of solar PV systems. To eliminate the use of the bulky and heavy line frequency step-up transformer to integrate solar PV systems to medium voltage grids, the high frequency magnetic linkbased medium voltage power converter topologies are discussed and compared based on their performance parameters. Moreover, switching and conduction losses are calculated to compare the performance of the switching techniques for the magnetic-linked power converter topologies. In this thesis, a new pulse width modulation technique has been proposed to integrate the SMES system with the solar PV system-based microgrid. The pulse width modulation technique is designed to provide reactive power into the network in an effective way. The modulation technique ensures lower total harmonic distortion (THD), lower switching loss, and better utilization of dc-bus voltage. The simulation and experimental results show the effectiveness of the proposed pulse width modulation technique. In this thesis, an improved version of the previously proposed switching technique has been designed for a transformer-less PV inverter. The improved switching technique can ensure effective active power flow into the network. A new switching scheme has been proposed for reactive power control to avoid unnecessary switching faced by the traditional switching technique in a transformer-less PV inverter. The proposed switching technique is based on the peak point value of the grid current and ensures lower switching loss compared to other switching techniques. In this thesis, a new magnetic-linked multilevel inverter has been designed to overcome the issues faced by the two-level inverters and traditional multilevel inverters. The proposed multilevel inverter utilizes the same number of electronic switches but fewer capacitors compared to the traditional multilevel inverters. The proposed multilevel inverter solves the capacitor voltage balancing and utilizes 25% more of the dc bus voltage compared to the traditional multilevel inverter, which reduces the power rating of the dc power source components and also extends the input voltage operating range of the inverter. An improved version magnetic-linked multilevel inverter is proposed in this thesis with a model predictive control technique. This multilevel inverter reduces both the number of switches and capacitors compared to the traditional multilevel inverter. This multilevel inverter also solves the capacitor voltage balancing issue and utilizes 50% more of the dc bus voltage compared to the traditional multilevel inverter. Finally, an energy management system has been designed for the developed power converter and control to achieve energy resiliency and minimum operating cost of the microgrid. The model predictive control-based energy management system utilizes the predicted load data, PV insolation data from web service, electricity price data, and battery state of charge data to select the battery charging and discharging pattern over the day. This model predictive control-based supervisory control with the advanced power electronic converter and control makes the PV energy-based microgrid more efficient and reliable

A discrete event simulation model for unstructured supervisory control of unmanned vehicles

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 33).Most current Unmanned Vehicle (UV) systems consist of teams of operators controlling a single UV. Technological advances will likely lead to the inversion of this ratio, and automation of low level tasking. These advances will also lead to a growth in UV use in large-scale applications such as urban search and rescue, which will require the use of both teams of operators and teams of UVs. This growth will in turn require research and development in the area of team supervisory control of multiple UVs. Human-in-the- loop experimentation is often used during this research but can be time consuming and expensive. The time and cost of experimentation can often be drastically reduced by using predictive models. However there is a lack of such models in the area of multiple-operator supervisory control of multiple- UVs. This problem is addressed in this thesis through the following method: First, current predictive models of human supervisory control of UVs are analyzed, and attributes of systems related to this modeling space are identified. Second, a queuing-based multiple-operator multiple-vehicle discrete event simulation model (MO-MUVDES) is developed which captures these attributes, including the ability to predict performance in situations with low observable exogenous event arrivals. MO-MUVDES also incorporates traditional system variables such as level of vehicle autonomy, vehicle and operator team structure, and operator switching strategy. The accuracy and robustness of the MO-MUVDES model were measured by a two-stage validation process using data from a human-in-the-loop supervisory control experiment, and a Monte Carlo simulation. The first stage of the validation process used data from the experiment as input for the MOMUVDES model which was then used to generate predictions of operator performance. In the second stage of validation, a sensitivity analysis was performed on the MO-MUVDES model. This validation process achieved confidence in the model's ability to predict operator performance and a measurement of the robustness of the model under varying input conditions. Additionally, the process indicated that discrete event simulation is an effective technique for modeling team supervisory control of UVs in a situation where exogenous event arrivals are not clearly observable. As a result, the MO-MUVDES model could be used to reduce development time for systems within its modeled space.by Anthony D. McDonald.S.B