No description available.

No description available.

We investigate the stabilization of unstable multidimensional partially observed single-station, multi-sensor (single-controller) and multi-controller (single-sensor) linear systems controlled over discrete noiseless channels under fixed-rate information constraints. Stability is achieved under communication requirements that are asymptotically tight in the limit of large sampling periods. Through the use of similarity transforms, sampling and random-time drift conditions we obtain a coding and control policy leading to the existence of a unique invariant distribution and finite second moment for the sampled state. We use a vector stabilization scheme in which all modes of the linear system visit a compact set together infinitely often. / Thesis (Master, Mathematics & Statistics) -- Queen's University, 2012-12-06 15:06:37.449

NR 20140805

Many successful control schemes for land-based or air-based groups, or platoons, of autonomous vehicles cannot be implemented in underwater applications because of their dependence upon high-bandwidth communication. In current strategies for controlling groups of autonomous underwater vehicles (AUVs), platoon size remains limited by communication bandwidth requirements. So, there is great need for advances in low-bandwidth control techniques for arbitrarily large platoons of AUVs. This thesis presents a new approach to multiple vehicle control. The concepts described herein enable an arbitrarily large platoon to be controlled while utilizing minimal inter-vehicle communication. Specifically, this thesis examines a sufficient condition on platoon commands in order for a low-bandwidth decentralized controller to exist. Knowing from this sufficient condition the necessary general form of platoon commands, a number of higher-order statistics were tested. This thesis describes and analyzes their utility as platoon commands. In addition to these theoretical developments, this thesis presents the practical design needs for the Virginia Tech miniature autonomous underwater vehicle as well as their resolution. / Master of Science

There is an emerging need to develop new techniques for control system design that better address the challenges posed by modern large-scale cyber-physical systems. These systems are often massive networks of interconnected and interoperating subsystems that fuse physical processes, embedded computation, automation technologies, and communication. The resulting problems are dimensionally large, exhibit significant time-varying structural variations during operation, and feature complex dynamics, constraints and objectives across local and global-system scales. These properties are difficult to address using traditional control theoretic methods without substantial loss of performance and robustness. To overcome these limitations, this dissertation presents new concepts and methods for control of modern large-scale variably-structured systems through self-assembling and self-configuring control constructs that allow for fundamental restructuring of the control system’s topology in response to the current system structure. We present the System Component Graph (SCG) formulation as a mathematical framework that generalizes and extends directed graph methods from decentralized control. We present algorithms, methods, and metrics for real-time decentralization and control-structure optimization, utilizing the inclusion principle for addressing interconnected overlapping dynamics and optimal linear-quadratic (LQ) methods for local decentralized subsystem control. Global system control and performance is achieved through a centralized planner that provides continuous real-time optimized trajectories as guidance command inputs to each subsystem. We present the method of Random Subcomplement Trees (RST) for pseudo-optimal real-time trajectory planning of large-scale systems which formalizes and extends the method of rapidly-exploring random trees in a control optimization framework. The RST method defines transformations from the higher-dimension state space into an intermediate lower-dimensional search space, where optimal transitions between subspace states are defined. In the context of this approach, the resulting decentralized topology found within the SCG framework provides the RST subspace definition and requisite transformations, and optimal transitions in the search space are found through forward evaluation of the closed-loop decentralized subsystem dynamics. The methods developed in this thesis are applied to a set of real-world problems spanning various domains and demonstrate the application of these methods from first-principle modeling through control system analysis, design, implementation, and evaluation in experimental tests and simulation.

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Environmental targets set by governments around the world are leading to high penetrations of small to medium-scale renewable distributed generation (DG). High penetration of DG in distribution networks, however, can result in voltage and thermal issues among other technical problems. The traditional 'Fit & Forget' approach that refers to the passive use of assets with limited or no control, in the context of distribution network planning, is used to meet maximum demand or generation requirements. However, to ensure that more renewable generation is cost-effectively connected to distribution networks, it is imperative to adopt a more active control of network elements and participants. The active control of future distribution networks requires understanding the corresponding dependencies between voltage magnitudes and DG active/reactive power outputs to mitigate voltage issues. One classical method to calculate these dependencies is to use sensitivity approaches such as those based on the Jacobian matrix. However, during operation, updating the Jacobian matrix requires the network to be fully observable making it unfeasible for decentralized control approaches. Therefore, it is critical to develop a sensitivity approach only requiring local real-time information. This thesis proposes a novel approach to produce voltage sensitivity coefficients using the surface fitting technique based solely on knowledge of network characteristics and, therefore, no remote monitoring is required. To assess the performance of the proposed voltage sensitivity approach, a decentralized (local) voltage control algorithm that simultaneously caters for both the active and reactive power outputs of a single DG plant is adopted. Comparisons with classical sensitivity approaches are carried out using the 16-bus UK GDS test network, 1-min resolution demand and wind generation data. Persistence forecasting (i.e., assuming no changes in demand and wind in a short time period) is considered in this case. The lower Mean Squared Error (MSE) shows that the coefficients of the proposed sensitivity approach are close to those of the Jacobian matrix and better than the perturb-and-observe approach. In the context of voltage management, results highlight that the proposed sensitivity approach is more effective than the Jacobian matrix inverse and perturb-and-observe, resulting in better voltage compliance and energy harvesting (better capacity factor). It should be highlighted that this performance is achieved without the need of full network observability. Furthermore, to cater for the more realistic and complex case of multiple DG plants, this thesis proposes a time-delay based decentralized control algorithm. A comparison with an ideal AC Optimal Power Flow (OPF) is carried out using the same 16-bus UK GDS network but with seven DG plants. The results demonstrate that the proposed sensitivity approach and time delays are very effective when compared to the AC OPF. This, in turn, proves that the combined use of the proposed voltage sensitivity approach and the decentralized controller is an implementable, cost-effective solution to manage DG plants in distribution networks without the need of further communication infrastructure. Finally, a decentralized DG control logic with the capability of using wind forecasting techniques is proposed to tackle the unpredictable nature of wind power. In this work, a time-series based forecasting technique is incorporated to the proposed decentralized controller. The results confirm that the use of more advanced forecasting technique can further improve the management of renewable DG plants.

This dissertation presents the results of a series of studies on dynamic stabilisation of CoMan, which is actuated by series elastic actuators. The main goal of this dissertation is to dynamically stabilise the humanoid robot on the floor by the simplest multivariate feedback control for the purpose of walking. The multivariable scheme is chosen to take into account the joints' interactions, as well as providing a systematic way of designing the feedback system to improve the bandwidth and tracking performance of CoMan's existing PID control. A detailed model is derived which includes all the motors and joints state variables and their multibody interactions which are often ignored in the previous studies on bipedal robots in the literature. The derived dynamic model is then used to design multivariable optimal control feedback and observers with a mathematical proof for the relative stability and robustness of the closed loop system in face of model uncertainties and disturbances. In addition, two decentralized optimal feedback design algorithms are presented that explicitly take the compliant dynamics and the multibody interactions into account while providing the mathematical proof for the stability of the overall system. The purpose of the proposed decentralized control methods is to provide a systematic model based PDPID design to replace the existing PID controllers which are derived by a trial and error process. Moreover, the challenging constrained and compliant motion of the robot in double support is studied where a novel constrained feedback design is proposed which directly takes the compliance dynamics, interactions and the constraints into account to provide a closed loop feedback tracking system that drives the robot inside the constrained subspace. This method of control is particularly interesting since most control methods applied to closed kinematic chains (such as the double support phase) are over complicated for implementation purposes or have an ad-hoc approach to controller design. In terms of walking trajectory generation, an extension to the ZMP walking trajectory generation is proposed to utilise the CoMan's upper body to tackle the non-minimum phase behaviour that is faced in trajectory generation. Simple inverted pendulum models of walking are then used to study the maximum feasible walking speed and step size where parameters of CoMan are used to provide numerical upperbounds on the step size and walking speed. Use of straight knee and toe push-off during walking is shown to be beneficial for taking larger step lengths and hence achieving faster walking speeds. Subsequently, the designed tracking systems are then applied to a dynamic walking simulator which is developed during this PhD project to accurately model the compliant walking behaviour of the CoMan. A walking gait is simulated and visualized to show the effectiveness of the developed walking simulator. Moreover, the experimental results and challenges faced during the implementation of the designed tracking control systems are discussed where it is shown that the LQR feedback results in 50% less control effort and tracking errors in comparison with CoMan's existing independent PID control. This advantage directly affects the feasible walking speed. In addition, a set of standard and repeatable tests for CoMan are designed to quantify and compare the performance of various control system designs. Finally, the conclusions and future directions are pointed out.

Layered structures are commonly used in communication systems, but their roles in decentralized control are not understood well. In the first part of this thesis, a theoretical study of consensus (a typical decentralized control task) in layered structures is conducted. The unique graph topology approach permits explicit characterization of consensus performance based on simple graphical characteristics of MLMG structures. In the second part of this thesis, a generic LEGO test-bed to mimic multi-domain communication with layered structures is described. A search-and-rescue scenario is implemented to demonstrate the use of the test-bed.