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Unmanned aircraft systems (UAS) often encounter turbulent fields that perturb the aircraft from its desired target trajectory, or in a manner that increases the load factor. The aircraft's fixed dihedral angle, providing passive roll-stiffness, is often selected based on lateral-directional stability requirements for the vehicle. A study to predict the effect of an active dihedral system on lateral-directional stability and vertical gust rejection capability was conducted to assess the performance and feasibility of the system. Traditionally, the dihedral location begins at the root to maintain wing structural requirements, however, the active dihedral system was also evaluated for dynamic stability and gust rejection performance at alternative dihedral breakpoint locations. Simulations were completed using linear parameter-varying (LPV) models, derived from traditional Newtonian aircraft dynamics and associated kinematic equations, to improve the modeling of the nonlinear active dihedral system. The stability of the LPV system was evaluated using Lyapunov stability theory applied to switched linear systems, assessing bounds of operation for the dihedral angle and flapping rate. An ideal feedback controller was developed using a linear–quadratic regulator (LQR) for both a discrete gust model and a continuous gust model, and a gain scheduled LQR controller was implemented to show the benefits of gain scheduling with a parameter varying state and input model. Finally, a cost analysis was conducted to investigate the real-world benefit of altering the dihedral breakpoint location. The effects of the active dihedral system on battery capacity and consumption efficiency were observed and compared with the gust rejection authority.

This thesis addresses a number of problems in the area of distributed leader-follower consensus control for certain classes of large-scale systems, including physically interconnected systems, interconnected parameter varying systems and decoupled multi-agent systems. In all situations considered, the state matrices of the constituent subsystems are assumed to be identical. First we consider the guaranteed performance leader-follower tracking control for physically interconnected systems connected over undirected or directed topologies. The physical interactions between subsystems pose a difficulty in using the existing distributed leader-follower control techniques that are developed for independent multi-agent systems. The existing decentralized control schemes are limited in achieving a desired group behavior as decentralized controllers do not communicate with each other. This thesis aims to combine the strengths of the two approaches of leader-follower and decentralized control to provide advanced methods for coordinated control of interconnected systems. The main contribution of this work is to take physical interactions between subsystems into consideration, and propose leader-follower consensus control protocols for interconnected systems to achieve a suboptimal guaranteed performance. Then we extend the previous problem to address the leader-follower tracking control for interconnected parameter varying systems. For this problem, we propose a continuous gain-scheduled consensus-type control protocol using a control interpolation technique. Motivated by realities of practical network control systems which make it difficult to realize continuous-time communications, we develop the event-triggered leader-follower tracking control for multivariable multi-agent systems. We propose event triggering rules to reduce the usage of communication resources, guarantee uniformly ultimately bounded consensus tracking errors, and exclude Zeno behavior for all nodes. The important contribution of this work is the event-triggered control protocols that do not require the neighboring agents to communicate continuously. Instead, the combinational state required for the event triggering conditions is generated continuously within the control algorithm using judiciously chosen samples and one-way communications between neighbors. Finally, numerical comparisons are carried out to illustrate the developed theory.

This study takes advantage of wide area measurements to propose a centralized nonlinear controller that acts on power system stabilizers, to cooperatively increase the damping of problematic small signal oscillations all over the system. The structure based on decision trees results in a simple, efficient, and dependable methodology that imposes much less computational burden than other nonlinear design approaches, making it a promising candidate for actual implementation by utilities and system operators. Details are given to utilize existing stabilizers while causing minimum changes to the equipment, and warranting improvement or at least no detriment of current system behavior. This enables power system stabilizers to overcome their inherent limitation to act only on the basis of local measurements to damp a single target frequency. This study demonstrates the implications of this new input on mathematical models, and the control functionality that is made available by its incorporation to conventional stabilizers. In preparation of the case of study, a heuristic dynamic reduction methodology is introduced that preserves a physical equivalent model, and that can be interpreted by any commercial software package. The steps of this method are general, versatile, and of easy adaptation to any particular power system model, with the aggregated value of producing a physical model as final result, that makes the approach appealing for industry. The accuracy of the resulting reduced network has been demonstrated with the model of the Central American System.

A brief analysis of the nonresonant-coupled parallel resonant converter is performed. The converter is modeled and a reference classical analog controller is designed and simulated. Infrastructure required for digital control of the converter (including anti-aliasing filters and a modulator) is designed and a classical digital controller is designed and simulated, yielding a ~30% degradation in control bandwidth at the worst-case operating point as compared with the analog controller. Based on the strong relationship observed between low-frequency converter gain and operating point, a gain-scheduled digital controller is proposed, designed, and simulated, showing 4:1 improved worst-case control bandwidth as compared with the analog controller. A complete prototype is designed and built which experimentally validates the results of the gain-scheduled controller simulation with good correlation. The three approaches that were investigated are compared and conclusions are drawn. Suggestions for further research are presented.

Gain scheduling via control signal interpolation: The ball and beam example.

Realistic models of engineering systems often are nonlinear. As a consequence, the dynamical behavior of a system to be controlled changes with the operating region. In recent years, one design methodology to control this effect, called Gain Scheduling, has proven to be successful. The basic idea of gain scheduling is to break the control design process into two steps. The first step is to linearize the model about one or more operating points. Then linear design methods are applied to the linearized model at each operating point in order to obtain the stabilized system within the design objectives. The final step, the actual gain scheduling, is obtained by scheduling or interpolating the gains of the local operating points designs in order to handle the nonlinear aspects of the design problem. In this thesis, a nonlinear controller will be designed using a gain scheduling technique for a hypothetical missile model. The missile considered here is the same as discussed in recent papers on gain scheduling. Here, a nonlinear autopilot is designed using classical servomechanism theory and state feedback/state observer based techniques.