Browsing by Subject "Convex optimization"
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Item An attitude determination and control system for small satellites(2015-05) Tam, Margaret Hoi Ting; Fowler, Wallace T.; Lightsey, E. GlennA flexible, robust attitude determination and control (ADC) system is presented for small satellite platforms. Using commercial-off-the-shelf sensors, reaction wheels, and magnetorquers which fit within the 3U CubeSat form factor, the system delivers arc-minute pointing precision. The ADC system includes a multiplicative extended Kalman filter for attitude determination and a slew rate controller that acquires a view of the Sun for navigation purposes. A pointing system is developed that includes a choice of two pointing controllers -- a proportional derivative controller and a nonlinear sliding mode controller. This system can reorient the spacecraft to satisfy a variety of mission objectives, but it does not enforce attitude constraints. A constrained attitude guidance system that can enforce an arbitrary set of attitude constraints is then proposed as an improvement upon the unconstrained pointing system. The momentum stored by the reaction wheels is managed using magnetorquers to prevent wheel saturation. The system was thoroughly tested in realistic software- and hardware-in-the-loop simulations that included environmental disturbances, parameter uncertainty, actuator dynamics, and sensor bias and noise.Item Decentralized probabilistic density control of swarm of autonomous agents with conflict avoidance constraints(2014-08) Demir, Nazlı; Açıkmeşe, BehçetThis report describes a method to control the density distribution of a large number of autonomous agents. The approach is based on the fact that there are a large number of agents in the system, and hence the time evolution of the probabilistic density distribution of agents can be described as a Markov chain. The main contribution of this paper is the synthesis of a Markov matrix which will guide the multi-agent system density to a desired steady-state density distribution, in a probabilistic sense, while satisfying some motion and safety constraints. Also, an adaptive density control method based on real time density feedback is introduced to synthesize a time-varying Markov ma- trix, which leads to better convergence to the desired density distribution. Finally, a decentralized density computation method is described. This method guarantees that all agents will have a best, and common, density estimate in a finite, with an explicit bound, number of communication updates.Item Lossless convexification of optimal control problems(2014-05) Harris, Matthew Wade; Açıkmeşe, BehçetThis dissertation begins with an introduction to finite-dimensional optimization and optimal control theory. It then proves lossless convexification for three problems: 1) a minimum time rendezvous using differential drag, 2) a maximum divert and landing, and 3) a general optimal control problem with linear state constraints and mixed convex and non-convex control constraints. Each is a unique contribution to the theory of lossless convexification. The first proves lossless convexification in the presence of singular controls and specifies a procedure for converting singular controls to the bang-bang type. The second is the first example of lossless convexification with state constraints. The third is the most general result to date. It says that lossless convexification holds when the state space is a strongly controllable subspace. This extends the controllability concepts used previously, and it recovers earlier results as a special case. Lastly, a few of the remaining research challenges are discussed.