Distributed Robust Set-Invariance for Interconnected Linear Systems

We introduce a class of distributed control policies for networks of discrete-time linear systems with polytopic additive disturbances. The objective is to restrict the network-level state and controls to user-specified polyhedral sets for all times. This problem arises in many safety-critical applications. We consider two problems. First, given a communication graph characterizing the structure of the information flow in the network, we find the optimal distributed control policy by solving a single linear program. Second, we find the sparsest communication graph required for the existence of a distributed invariance-inducing control policy. Illustrative examples, including one on platooning, are presented.Comment: 8 Pages. Submitted to American Control Conference (ACC), 201

A decentralized linear quadratic control design method for flexible structures

A decentralized suboptimal linear quadratic control design procedure which combines substructural synthesis, model reduction, decentralized control design, subcontroller synthesis, and controller reduction is proposed for the design of reduced-order controllers for flexible structures. The procedure starts with a definition of the continuum structure to be controlled. An evaluation model of finite dimension is obtained by the finite element method. Then, the finite element model is decomposed into several substructures by using a natural decomposition called substructuring decomposition. Each substructure, at this point, still has too large a dimension and must be reduced to a size that is Riccati-solvable. Model reduction of each substructure can be performed by using any existing model reduction method, e.g., modal truncation, balanced reduction, Krylov model reduction, or mixed-mode method. Then, based on the reduced substructure model, a subcontroller is designed by an LQ optimal control method for each substructure independently. After all subcontrollers are designed, a controller synthesis method called substructural controller synthesis is employed to synthesize all subcontrollers into a global controller. The assembling scheme used is the same as that employed for the structure matrices. Finally, a controller reduction scheme, called the equivalent impulse response energy controller (EIREC) reduction algorithm, is used to reduce the global controller to a reasonable size for implementation. The EIREC reduced controller preserves the impulse response energy of the full-order controller and has the property of matching low-frequency moments and low-frequency power moments. An advantage of the substructural controller synthesis method is that it relieves the computational burden associated with dimensionality. Besides that, the SCS design scheme is also a highly adaptable controller synthesis method for structures with varying configuration, or varying mass and stiffness properties

MIT Space Engineering Research Center

The Space Engineering Research Center (SERC) at MIT, started in Jul. 1988, has completed two years of research. The Center is approaching the operational phase of its first testbed, is midway through the construction of a second testbed, and is in the design phase of a third. We presently have seven participating faculty, four participating staff members, ten graduate students, and numerous undergraduates. This report reviews the testbed programs, individual graduate research, other SERC activities not funded by the Center, interaction with non-MIT organizations, and SERC milestones. Published papers made possible by SERC funding are included at the end of the report

Resource Orchestration in Softwarized Networks

Network softwarization is an emerging research area that is envisioned to revolutionize the way network infrastructure is designed, operated, and managed today. Contemporary telecommunication networks are going through a major transformation, and softwarization is recognized as a crucial enabler of this transformation by both academia and industry. Softwarization promises to overcome the current ossified state of Internet network architecture and evolve towards a more open, agile, flexible, and programmable networking paradigm that will reduce both capital and operational expenditures, cut-down time-to-market of new services, and create new revenue streams. Software-Defined Networking (SDN) and Network Function Virtualization (NFV) are two complementary networking technologies that have established themselves as the cornerstones of network softwarization. SDN decouples the control and data planes to provide enhanced programmability and faster innovation of networking technologies. It facilitates simplified network control, scalability, availability, flexibility, security, cost-reduction, autonomic management, and fine-grained control of network traffic. NFV utilizes virtualization technology to reduce dependency on underlying hardware by moving packet processing activities from proprietary hardware middleboxes to virtualized entities that can run on commodity hardware. Together SDN and NFV simplify network infrastructure by utilizing standardized and commodity hardware for both compute and networking; bringing the benefits of agility, economies of scale, and flexibility of data centers to networks. Network softwarization provides the tools required to re-architect the current network infrastructure of the Internet. However, the effective application of these tools requires efficient utilization of networking resources in the softwarized environment. Innovative techniques and mechanisms are required for all aspects of network management and control. The overarching goal of this thesis is to address several key resource orchestration challenges in softwarized networks. The resource allocation and orchestration techniques presented in this thesis utilize the functionality provided by softwarization to reduce operational cost, improve resource utilization, ensure scalability, dynamically scale resource pools according to demand, and optimize energy utilization

Using Distributed Energy Resources to Improve Power System Stability and Voltage Unbalance

The increasing penetration of renewables has driven power systems to operate closer to their stability boundaries and makes maintaining power quality more difficult. The goals of this dissertation are to develop methods to control distributed energy resources to improve power system stability and voltage unbalance. Specifically, demand response (DR) is used to realize the former goal, and solar photovoltaic (PV) systems are used to achieve the latter. We present a new DR strategy to change the consumption of flexible loads while keeping the total load constant, improving voltage or small-signal stability without affecting frequency stability. The new loading pattern is only maintained temporarily until the generators can be re-dispatched. Additionally, an energy payback period maintains the total energy consumption of each load at its nominal value. Multiple optimization problems are proposed for determining the optimal loading pattern to improve different voltage or small-signal stability margins. The impact of different system models on the optimal solution is also investigated. To quantify voltage stability, we choose the smallest singular value (SSV) of the power flow Jacobian matrix and the distance to the closest saddle-node bifurcation (SNB) of the power flow as the stability margins. We develop an iterative linear programming (ILP) algorithm using singular value sensitivities to obtain the loading pattern with the maximum SSV. We also compare our algorithm's performance to that of an iterative nonlinear programming algorithm from the literature. Results show that our ILP algorithm is more computationally scalable. We formulate another problem to maximize the distance to the closest SNB, derive the Karush–Kuhn–Tucker conditions, and solve them using the Newton-Raphson method. We also explore the possibility of using DR to improve small-signal stability. The results indicate that DR actions can improve small-signal characteristics and sometimes achieve better performance than generation actions. Renewables can also cause power quality problems in distribution systems. To address this issue, we develop a reactive power compensation strategy that uses distributed PV systems to mitigate voltage unbalance. The proposed strategy takes advantage of Steinmetz design and is implemented via both decentralized and distributed control. We demonstrate the performance of the controllers on the IEEE 13-node feeder and a much larger feeder, considering different connections of loads and PV systems. Simulation results demonstrate the trade-offs between the controllers. It is observed that the distributed controller achieves greater voltage unbalance reduction than the decentralized controller, but requires communication infrastructure. Furthermore, we extend our distributed controller to handle inverter reactive power limits, noisy/erroneous measurements, and delayed inputs. We find that the Steinmetz controller can sometimes have adverse impacts on feeder voltages and unbalance at noncritical nodes. A centralized controller from the literature can explicitly account for these factors, but requires significantly more information from the system and longer computational times. We compare the performance of the Steinmetz controller to that of the centralized controller and propose a new controller that integrates centralized controller results into the Steinmetz controller. Results show that the integrated controller achieves better unbalance improvement compared with that of the centralized controller running infrequently. In summary, this dissertation presents two demand-side strategies to deal with the issues caused by the renewables and contributes to the growing body of literature that shows that distributed energy resources have the potential to play a key role in improving the operation of the future power system.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162969/1/mqyao_1.pd

Damping of electromechanical oscillations using power system stabilizers

Includes bibliographical references.This thesis deals with the damping of electromechanical oscillations using Power System Stabilizers (PSS). The thesis focuses on three problems associated with the damping of these oscillations, namely the determination of the optimal locations of the PSS, the determination of the best control structure of the PSS and the design of robust PSS. We develop two new methods for determining the optimal locations of the PSS. These two methods are based on Total Modified Coupling Factors (TMC) and optimization by Simulated Annealing (SA). The TMC is a measure of the damping influence of each machine pair on several power system modes. The TMC incorporates the effect of the performance and the type of excitation system of the generator. The method based on TMC is tested on a nine-bus benchmark network. In the method based on SA, we formulate the PSS placement problem as a discrete nonlinear optimization problem. The objective function corresponds to the damping of the electromechanical modes of the system. In this method, the placement is performed simultaneously for all PSS. Using SA, we obtain a placement scheme which guarantees that the undesired poles can be controlled with finite control energy. As a result of the optimization formulation, the method based on SA is computationally more intensive than the method based on TMC. We demonstrate the method based on SA on two networks namely, a seven-bus network and a 35-bus equivalent of the Eskom network. The problem of determining the control structure for damping of the electromechanical oscillations is composed of three aspects namely, the type of feedback, the type of signal and the type of control