Abstract: Agglomerate tile structures and ceiling tile structures: The agglomerate tile structures can be of a single layer having an intermixed granular base medium comprised of one or more subcomponent materials (e.g., powdered, crushed, chips, and/or other broken pieces of varying sized particles, of quartz, granite, limestone, marble, glass, ceramic, semiprecious stones, etc.), plus a binder material and a PCM component; or the agglomerate tile structures can be of multiple layers, such as having an outer wear-layer substantially absent of PCM component—this outer wear-layer being bonded or otherwise incorporated with a second layer comprised of a binder material and a PCM component, substantially absent of the granular base medium.

Abstract: A neural network controller in parallel with a proportional-plus-integral (PI) feedback controller in a control system. At least one input port of the neural network for receiving an input signal representing a condition of a process is included. A first set of data is obtained that includes a plurality of output values of the neural network obtained during a training period thereof using a plurality of first inputs representing a plurality of conditions of the process. The process/plant condition signals generally define the process/plant, and may include one set-point as well as signals generated using measured systems variables/parameters. In operation, the neural network contributes to an output of the PI controller only upon detection of at least one triggering event, at which time a value of the first set of data corresponding with the condition deviation is added-in thus, contributing to the proportional-plus-integral feedback controller.

Abstract: Agglomerate tile structures and ceiling tile structures: The agglomerate tile structures can be of a single layer having an intermixed granular base medium comprised of one or more subcomponent materials (e.g., powdered, crushed, chips, and/or other broken pieces of varying sized particles, of quartz, granite, limestone, marble, glass, ceramic, semiprecious stones, etc.), plus a binder material and a PCM component; or the agglomerate tile structures can be of multiple layers, such as having an outer wear-layer substantially absent of PCM component-this outer wear-layer being bonded or otherwise incorporated with a second layer comprised of a binder material and a PCM component, substantially absent of the granular base medium.

Abstract: A feedback control system for automatic on-line training of a controller for a plant, the system having a reinforcement learning agent connected in parallel with the controller. The learning agent comprises an actor network and a critic network operatively arranged to carry out at least one sequence of a stability phase followed by a learning phase. During the stability phase, a multi-dimensional boundary of values is determined. During the learning phase, a plurality of updated weight values is generated in connection with the on-line training, if and until one of the updated weight values reaches the boundary, at which time a next sequence is carried out to determine a next multi-dimensional boundary of values followed by a next learning phase.

Abstract: A feedback control system for automatic on-line training of a controller for a plant, the system having a reinforcement learning agent connected in parallel with the controller. The learning agent comprises an actor network and a critic network operatively arranged to carry out at least one sequence of a stability phase followed by a learning phase. During the stability phase, a multi-dimensional boundary of values is determined. During the learning phase, a plurality of updated weight values is generated in connection with the on-line training, if and until one of the updated weight values reaches the boundary, at which time a next sequence is carried out to determine a next multi-dimensional boundary of values followed by a next learning phase.

Abstract: A neural network controller in parallel with a proportional-plus-integral (PI) feedback controller in a control system. At least one input port of the neural network for receiving an input signal representing a condition of a process is included. A first set of data is obtained that includes a plurality of output values of the neural network obtained during a training period thereof using a plurality of first inputs representing a plurality of conditions of the process. The process/plant condition signals generally define the process/plant, and may include one set-point as well as signals generated using measured systems variables/parameters. In operation, the neural network contributes to an output of the PI controller only upon detection of at least one triggering event, at which time a value of the first set of data corresponding with the condition deviation is added-in thus, contributing to the proportional-plus-integral feedback controller.

Abstract: An apparatus and method for evaluation of a material having a first and second contact-surface. The apparatus includes a computer-controlled thermally-variable central element comprising a first and second outer surface, at least one outer surface having at least one temperature sensor thereon. Facing the first outer surface is a first exterior surface of a first thermally-variable side element, and facing the second outer surface is a second exterior surface of a second thermally-variable side element. A mechanism is a second exterior surface of a second thermally-variable side element. A mechanism is included that operates to move at least the first exterior surface toward the thermally-variable central element to apply a generally uniform pressure against the material contact-surfaces once the material has been so positioned.