Guaranteed Cost Tracking for Uncertain Coupled Multi-agent Systems Using Consensus over a Directed Graph

This paper considers the leader-follower control problem for a linear multi-agent system with directed communication topology and linear nonidentical uncertain coupling subject to integral quadratic constraints (IQCs). A consensus-type control protocol is proposed based on each agent's states relative to its neighbors and leader's state relative to agents which observe the leader. A sufficient condition is obtained by overbounding the cost function. Based on this sufficient condition, a computational algorithm is introduced to minimize the proposed guaranteed bound on tracking performance, which yields a suboptimal bound on the system consensus control and tracking performance. The effectiveness of the proposed method is demonstrated using a simulation example.Comment: Accepted for presentation at the 2013 Australian Control conferenc

Information Theory and Cooperative Control in Networked Multi-Agent Systems with Applications to Smart Grid

This dissertation focuses on information theoretic aspects of and cooperative control techniques in networked multi-agent systems (NMAS) with communication constraints. In the first part of the dissertation, information theoretic limitations of tracking problems in networked control systems, especially leader-follower systems with communication constraints, are studied. Necessary conditions on the data rate of each communication link for tracking of the leader-follower systems are provided. By considering the forward and feedback channels as one cascade channel, we also provide a lower bound for the data rate of the cascade channel for the system to track a reference signal such that the tracking error has finite second moment. Finally, the aforementioned results are extended to the case in which the leader system and follower system have different system models. In the second part, we propose an easily scalable hierarchical decision-making and control architecture for smart grid with communication constraints in which distributed customers equipped with renewable distributed generation (RDG) interact and trade energy in the grid. We introduce the key components and their interactions in the proposed control architecture and discuss the design of distributed controllers which deal with short-term and long-term grid stability, power load balancing and energy routing. At microgrid level, under the assumption of user cooperation and inter-user communications, we propose a distributed networked control strategy to solve the demand-side management problem in microgrids. Moreover, by considering communication delays between users and microgrid central controller, we propose a distributed networked control strategy with prediction to solve the demand-side management problem with communication delays. In the third part, we consider the disturbance attenuation and stabilization problem in networked control systems. To be specific, we consider the string stability in a large group of interconnected systems over a communication network. Its potential applications could be found in formation tracking control in groups of robots, as well as uncertainty reduction and disturbance attenuation in smart grid. We propose a leader-following consensus protocol for such interconnected systems and derive the sufficient conditions, in terms of communication topology and control parameters, for string stability. Simulation results and performance in terms of disturbance propagation are also given. In the fourth part, we consider distributed tracking and consensus in networked multi-agent systems with noisy time-varying graphs and incomplete data. In particular, a distributed tracking with consensus algorithm is developed for the space-object tracking with a satellite surveillance network. We also intend to investigate the possible application of such methods in smart grid networks. Later, conditions for achieving distributed consensus are discussed and the rate of convergence is quantified for noisy time-varying graphs with incomplete data. We also provide detailed simulation results and performance comparison of the proposed distributed tracking with consensus algorithm in the case of space-object tracking problem and that of distributed local Kalman filtering with centralized fusion and centralized Kalman filter. The information theoretic limitations developed in the first part of this dissertation provide guildlines for design and analysis of tracking problems in networked control systems. The results reveal the mutual interaction and joint application of information theory and control theory in networked control systems. Second, the proposed architectures and approaches enable scalability in smart grid design and allow resource pooling among distributed energy resources (DER) so that the grid stability and optimality is maintained. The proposed distributed networked control strategy with prediction provides an approach for cooperative control at RDG-equipped customers within a self-contained microgrid with different feedback delays. Our string stability analysis in the third part of this dissertation allows a single networked control system to be extended to a large group of interconnected subsystems while system stability is still maintained. It also reveals the disturbance propagation through the network and the effect of disturbance in one subsystem on other subsystems. The proposed leader-following consensus protocol in the constrained communication among users reveals the effect of communication in stabilization of networked control systems and the interaction between communication and control over a network. Finally, the distributed tracking and consensus in networked multi-agent systems problem shows that information sharing among users improves the quality of local estimates and helps avoid conflicting and inefficient distributed decisions. It also reveals the effect of the graph topologies and incomplete node measurements on the speed of achieving distributed decision and final consensus accuracy

Robust Distributed Stabilization of Interconnected Multiagent Systems

Many large-scale systems can be modeled as groups of individual dynamics, e.g., multi-vehicle systems, as well as interconnected multiagent systems, power systems and biological networks as a few examples. Due to the high-dimension and complexity in configuration of these infrastructures, only a few internal variables of each agent might be measurable and the exact knowledge of the model might be unavailable for the control design purpose. The collective objectives may range from consensus to decoupling, stabilization, reference tracking, and global performance guarantees. Depending on the objectives, the designer may choose agent-level low-dimension or multiagent system-level high-dimension approaches to develop distributed algorithms. With an inappropriately designed algorithm, the effect of modeling uncertainty may propagate over the communication and coupling topologies and degrade the overall performance of the system. We address this problem by proposing single- and multi-layer structures. The former is used for both individual and interconnected multiagent systems. The latter, inspired by cyber-physical systems, is devoted to the interconnected multiagent systems. We focus on developing a single control-theoretic tool to be used for the relative information-based distributed control design purpose for any combinations of the aforementioned configuration, objective, and approach. This systematic framework guarantees robust stability and performance of the closed-loop multiagent systems. We validate these theoretical results through various simulation studies

Analyzing the Impact of Wireless Multi-Hop Networking On Vehicular Safety

One of the core challenges of Intelligent Transportation System is the dissemination of timely and accurate vehicle information (e.g. speed, position) to geographically large distances without compromising data supply rates from immediate neighbors. This feature is critical for the design of vehicle safety and navigation applications. Single hop broadcasting is often inadequate to ensure vehicle safety when the platoon size is arbitrarily large due to its upper bound on rate and range of wireless message transmission. Existing wireless multi-hop protocols do not ensure reliable message delivery while avoiding network congestion in the shared channel. In this thesis, we make two separate but related investigations to address this challenge - (1) Analyze the impact of distance sensitive multi-hop broadcasting in realistic traffic network (2) Analyze the impact of wireless multi-hop network in vehicle safety. For investigating the first part, we used VCAST, a distance sensitive information propagation technique, in which information is forwarded at a rate that decreases linearly with distance from the source. VCAST is evaluated by using extensive simulations in ns-3, a discrete event simulator for wireless and mobile ad-hoc networks, under different density, source broadcast rates and communication range. To simulate realistic traffic movement, we used 2d grids of different sizes and used both uniform and non-uniform mobility. The results show that VCAST is scalable for - large number of vehicles and large source broadcast rates. It is further shown that successful scaling is achieved by reduced number of vehicle records transmitted per second per vehicle for varying network sizes and varying source broadcast rates. Vehicle safety messages for VCAST are piggy backed on heart beat messages and does not require any modifications to the existing vehicular communication standards. For investigating the second part, we implemented a realistic car following model and used string stability analysis as a metric for measuring vehicle safety. The basic idea is to exploit the small network propagation time in disseminating safety messages over large distances, instead of relying on just the predecessor vehicle\u27s state. This enables distant vehicles in a traffic stream to plan well in advance against rear end collisions which could lead to string instability. We also proposed one such proactive method of planning - and that is by controlling the headway time. Through extensive simulations, we obtained results for vehicle safety when some incident is detected abruptly on its course. The results show that proactive planning using multi-hop network makes the entire platoon string stable in the presence of emergency road incidents

Coordinated Control of Distributed Energy Resources in Islanded Microgrids

As the penetration of the distributed energy resources (DERs) in the power grid increases,new challenges are revealed, including: stability issues, frequency fluctuations, voltage control, protection system coordination, etc. A systematic approach for dealing with those issues is to view the DERs and associated loads as a subsystem or a microgrid (MG). MGs can operate either in the grid connected or islanded modes. As opposed to the grid connected mode, the voltage and frequency regulation and load/generation balancing during islanded mode is solely dependent on the local generation units. Therefore, stable and reliable operation of islanded MGs requires a real time coordinated control scheme. Conventionally, such coordination is achieved by means of the active power-frequency and reactive powervoltage droop control schemes. The conventional droop method, which is based on P-f droop concept in power systems, lacks compatibility with the resistive nature of networks as well as the low inertia of electronically interfaced DER units in MGs. As a result, it features a slow dynamic response but also a low power quality due to frequency and voltage fluctuations. This PhD research proposes a novel droop concept based on the global positioning system (GPS) and voltage-current (V-I) droop characteristics for coordination of inverter-based DER units in islanded MGs. The concept of V-I droop control is introduced in Chapter 2. In this control approach, each DER is equipped with a GPS receiver, which produces a pulse at frequency of 1Hz (1PPS). Since all GPS receivers are locked to atomic clocks of the GPS satellites, the 1PPS signal can be utilized to synchronize the time reference of the DER units. Using the common time reference and fixing the frequency at the nominal value, all of the units can share a common synchronous rotating reference frame (SRRF). Furthermore, proportional load sharing is achieved by drooping the d and q axis components of the reference voltage with respect to the d and q axis components of current, respectively. The proposed scheme not only circumvents the issue of frequency fluctuations but also is in accordance with the fast dynamics of inverter-based DER units and resistive nature of the networks in islanded MGs. The V-I droop scheme, in its basic form, relies on availability of GPS signals at each of the DER units. With the intention of improving the MG robustness with respect to GPS signal failure, a new control strategy based on V-I droop concept is presented Chapter 3. In this method, an adaptive reactive power-frequency droop scheme is used as a backup for the V-I droop controller to ensure synchronization in case of a GPS signal failure. Droop control schemes in general, and the proposed V-I droop strategy in particular are characterized by non-ideal sharing of current among the DER units due to the variations of voltage along the MGs. In order to improve the sharing accuracy of the V-I droop scheme iv while regulating the average voltage at the nominal value, a new distributed secondary control method based on consensus protocol is proposed in Chapter 4. In this method, the daxis droop characteristics is altered so as to regulate the average microgrid voltage to the rated value but also guarantee proper sharing of active power among the DERs. Additionally, the q-axis component of voltage is adjusted to perform proper sharing of current. Generally, DERs might be supplied from different energy sources, including renewables and storage systems. The intermittency of renewable energy resources on one hand and the limited capacity of the energy storage systems on the other hand, necessitate modification of droop characteristics based on an energy management plan. In Chapter 5, a novel distributed secondary control strategy is introduced for power management of integrated photovoltaicbattery DER units in islanded MGs. The distributed secondary controllers are coordinated based on a leader-follower framework, where the leader restores the MG voltage to the rated value and the followers pursue energy management. Unbalanced and nonlinear loads, which are quite common in MGs, adversely affect the power quality and sharing accuracy. In order to mitigate those issues, two new solutions are proposed in this thesis. In the first approach (Chapter 6), a new supplementary droop control scheme is added to the V-I droop controller to reduce the voltage unbalance while preventing current and power overload under unbalanced loading conditions. In the second approach (Chapter 7), a hierarchical control scheme, consisting of primary (modified V-I droop) and distributed secondary control levels is introduced to mitigate harmonic distortions and prevent overcurrent stresses under nonlinear and unbalanced loading conditions. Finally, the conclusions and possible future work are addressed in Chapter 8

Cooperative control of autonomous connected vehicles from a Networked Control perspective: Theory and experimental validation

Formation control of autonomous connected vehicles is one of the typical problems addressed in the general context of networked control systems. By leveraging this paradigm, a platoon composed by multiple connected and automated vehicles is represented as one-dimensional network of dynamical agents, in which each agent only uses its neighboring information to locally control its motion, while it aims to achieve certain global coordination with all other agents. Within this theoretical framework, control algorithms are traditionally designed based on an implicit assumption of unlimited bandwidth and perfect communication environments. However, in practice, wireless communication networks, enabling the cooperative driving applications, introduce unavoidable communication impairments such as transmission delay and packet losses that strongly affect the performances of cooperative driving. Moreover, in addition to this problem, wireless communication networks can suffer different security threats. The challenge in the control field is hence to design cooperative control algorithms that are robust to communication impairments and resilient to cyber attacks. The work aim is to tackle and solve these challenges by proposing different properly designed control strategies. They are validated both in analytical, numerical and experimental ways. Obtained results confirm the effectiveness of the strategies in coping with communication impairments and security vulnerabilities

DECENTRALIZED ROBUST NONLINEAR MODEL PREDICTIVE CONTROLLER FOR UNMANNED AERIAL SYSTEMS

The nonlinear and unsteady nature of aircraft aerodynamics together with limited practical range of controls and state variables make the use of the linear control theory inadequate especially in the presence of external disturbances, such as wind. In the classical approach, aircraft are controlled by multiple inner and outer loops, designed separately and sequentially. For unmanned aerial systems in particular, control technology must evolve to a point where autonomy is extended to the entire mission flight envelope. This requires advanced controllers that have sufficient robustness, track complex trajectories, and use all the vehicles control capabilities at higher levels of accuracy. In this work, a robust nonlinear model predictive controller is designed to command and control an unmanned aerial system to track complex tight trajectories in the presence of internal and external perturbance. The Flight System developed in this work achieves the above performance by using: 1 A nonlinear guidance algorithm that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2 A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3 An artificial neural network, designed to adaptively estimate and provide aerodynamic and propulsive forces in real-time; and 4 A mixed sensitivity approach that enhances the robustness for a nonlinear model predictive controller overcoming the effect of un-modeled dynamics, external disturbances such as wind, and measurement additive perturbations, such as noise and biases. These elements have been integrated and tested in simulation and with previously stored flight test data and shown to be feasible