Establishing and maintaining successful communication stands as a critical prerequisite for achieving the goals of inducing and studying advanced computation in small-scale living neuronal networks. The following work establishes a novel and effective method for communicating arbitrary "sensory" input information to cultures of living neurons, living neuronal networks (LNNs), consisting of approximately 20 000 rat cortical neurons plated on microelectrode arrays (MEAs) containing 60 electrodes. The sensory coding algorithm determines a set of effective codes (symbols), comprised of different spatio-temporal patterns of electrical stimulation, to which the LNN consistently produces unique responses to each individual symbol. The algorithm evaluates random sequences of candidate electrical stimulation patterns for evoked-response separability and reliability via a support vector machine (SVM)-based method, and employing the separability results as a fitness metric, a genetic algorithm subsequently constructs subsets of highly separable symbols (input patterns). Sustainable input/output (I/O) bit rates of 16-20 bits per second with a 10% symbol error rate resulted for time periods of approximately ten minutes to over ten hours. To further evaluate the resulting code sets' performance, I used the system to encode approximately ten hours of sinusoidal input into stimulation patterns that the algorithm selected and was able to recover the original signal with a normalized root-mean-square error of 20-30% using only the recorded LNN responses and trained SVM classifiers. Response variations over the course of several hours observed in the results of the sine wave I/O experiment suggest that the LNNs may retain some short-term memory of the previous input sample and undergo neuroplastic changes in the context of repeated stimulation with sensory coding patterns identified by the algorithm.

Over the last decade, power systems have evolved dramatically around the world, owing to higher demand, stringent requirements on quality and environmental concerns that are becoming increasingly critical. With the introduction of new technologies like large-scale renewable energy, wide-area measurement based on phasor measurement units (PMUs) and consumer interaction in the distribution system, the power grid today has become more potent than ever before. Most of the defining features of the smart grid today rest on the integration of advanced communication capabilities into the grid. While communication infrastructure has become a key enabler for the smart grid, it also introduces new and complex control challenges that must be addressed. As we increasingly rely on information transmitted to distant areas over communication networks, it becomes imperative to model the effects of the communication system on the stability of the power grid. Several approaches exist in control theory to study such systems, widely referred to as Networked Control Systems (NCS). Networked control theory provides mathematical tools for system stability analysis and control in the presence of communication delays, packet dropouts and disordering due to transmission of sensor and actuator signals via a limited communication network. In this thesis, a networked control framework for smart grids with integrated commu-nication infrastructure (ICT) is developed. In particular, a networked control systems perspective is developed for two scenarios - wide-area monitoring control, and coordinated control of distributed generation sources. The effects of communication delays and packet dropouts on power system stability are modeled in detail. In the wide-area monitoring control problem, system state measurements are trans-mitted from remote locations through a communication network. The system is modeled as an NCS and a control design approach is presented to damp inter-area oscillations arising from various power system disturbances in the presence of communication constraints. In the coordinated control scenario, a power system with geographically dispersed sources is modeled as an NCS. A networked controller is designed to stabilize the system in the presence of small signal disturbances when system measurements are subject to communication delays and packet dropouts. A realistic output feedback networked control scheme that only uses voltage measurements from PMUs is also developed for practical implementation. The networked controllers designed in this thesis are validated against controllers designed by standard methods, by simulation on standard test systems. The networked controllers are found to enhance power system stability and load transfer capability even in the presence of severe packet dropouts and delays. Several extensions and theoretical problems motivated by this thesis are also proposed.