Abstract: A Digital Power-Amplifier (DPA) system includes a power amplifier (PA) circuit having control inputs and an output for generating output signals, and an adaptive control circuit that comprises an input interface, an output interface, a memory storing an adaptive control algorithm and a processor performing instructions based on the adaptive control algorithm in connection with the memory, wherein the input interface receives input-state signals and output signals of the DPA circuit, wherein the adaptive control algorithm determines, in response to the input-state signals and the output signals, control parameters of control signals transmitted to the control inputs from the output interface for controlling operations of the DPA circuit.

Abstract: A controller for controlling a system having uncertainties in its dynamics subject to constraints on an operation of the system is provided. The controller is configured to acquire historical data of the operation of the system, and determine, for the system in a current state, a current control action transitioning a state of the system from the current state to a next state. The current control action is determined according to a robust and constraint Markov decision process (RCMDP) that uses the historical data to optimize a performance cost of the operation of the system subject to an optimization of a safety cost enforcing the constraints on the operation, wherein a state transition for each of state and action pairs in the performance cost and the safety cost is represented by a plurality of state transitions capturing the uncertainties of the dynamics of the system.

Abstract: An apparatus for controlling an operation of a system is provided. The apparatus comprises an input interface configured to receive a state trajectory of the system, and a memory configured to store a model of dynamics of the system including a combination of at least one differential equation and a closure model. The apparatus further comprises a processor configured to update the closure model using reinforcement learning (RL) having a value function reducing a difference between a shape of the received state trajectory and a shape of state trajectory estimated using the model with the updated closure model, and determine a control command based on the model with the updated closure model. Further, the apparatus comprises an output interface configured to transmit the control command to an actuator of the system to control the operation of the system.

Abstract: A Digital Power-Amplifier (DPA) system includes a power amplifier (PA) circuit having control inputs and an output for generating output signals, and an adaptive control circuit that comprises an input interface, an output interface, a memory storing an adaptive control algorithm and a processor performing instructions based on the adaptive control algorithm in connection with the memory, wherein the input interface receives input-state signals and output signals of the DPA circuit, wherein the adaptive control algorithm determines, in response to the input-state signals and the output signals, control parameters of control signals transmitted to the control inputs from the output interface for controlling operations of the DPA circuit.

Abstract: A controller for optimizing a local control policy of a system for trajectory-centric reinforcement learning is provided. The controller includes performing steps of learning a stochastic predictive model for the system using a set of data collected during trial and error experiments performed using an initial random control policy, estimating mean prediction and uncertainty associated, determining a local set of deviations of the system using the learned stochastic system model, from a nominal system state upon use of a control input at a current time-step, determining a system state with a worst-case deviation, determining a gradient of the robustness constraint, providing and solving a robust policy optimization problem using non-linear programming to obtain system trajectory and stabilizing local policy simultaneously, updating the control data according to the solved optimization problem, and output the updated control data via the interface.

Abstract: A controller for controlling a system is provided.

Abstract: A controller for controlling a system is provided.

Abstract: A vehicle control system for driving a vehicle toward a source while avoiding an obstacle includes a first sensor to measure a first intensity of a source signal from the source, a second sensor to detect an obstacle and a second vehicle. The system includes an interface to receive data of a second intensity of the source signal measured by the second vehicle and transmit the data of the first and second intensities via a wireless channel, a memory to store the data of the first and second intensities, an autonomous program, a leader algorithm and a follower algorithm for autonomously driving the vehicle, a processor to select and perform one of the leader algorithm and the follower algorithm and generate control signals, and a machinery control circuit to drive a machinery of the vehicle according the control signals.

Abstract: A system for controlling an operation of an air-conditioning system generating airflow in a conditioned environment, includes a set of sensors to produce measurements of the airflow in a set of points in the conditioned environment, a memory to store a model of the airflow dynamics including a combination of a first term transitioning a previous state of the airflow to a current state of the airflow and a second term assisting the transitioning, an observer to estimate the current state of the airflow in the conditioned environment by transitioning the previous state of the airflow forward in time according to the model of airflow dynamics to reduce the observation error in the current state of the airflow, and a controller to control the air-conditioning system based on the current state of the airflow. The first term in the model includes a projection of a physical model of the airflow on a finite-dimensional space.

Abstract: A Digital Power-Amplifier (DPA) system includes a power amplifier (PA) circuit having control inputs and an output for generating output signals, and an adaptive control circuit that comprises an input interface, an output interface, a memory storing an adaptive control algorithm and a processor performing instructions based on the adaptive control algorithm in connection with the memory, wherein the input interface receives input-state signals and output signals of the DPA circuit, wherein the adaptive control algorithm determines, in response to the input-state signals and the output signals, control parameters of control signals transmitted to the control inputs from the output interface for controlling operations of the DPA circuit.

Abstract: A vehicle control system for driving a vehicle toward a source while avoiding an obstacle includes a first sensor to measure a first intensity of a source signal from the source, a second sensor to detect an obstacle and a second vehicle. The system includes an interface to receive data of a second intensity of the source signal measured by the second vehicle and transmit the data of the first and second intensities via a wireless channel, a memory to store the data of the first and second intensities, an autonomous program, a leader algorithm and a follower algorithm for autonomously driving the vehicle, a processor to select and perform one of the leader algorithm and the follower algorithm and generate control signals, and a machinery control circuit to drive a machinery of the vehicle according the control signals.

Abstract: A system for controlling an operation of an air-conditioning system generating airflow in a conditioned environment, includes a set of sensors to produce measurements of the airflow in a set of points in the conditioned environment, a memory to store a model of the airflow dynamics including a combination of a first term transitioning a previous state of the airflow to a current state of the airflow and a second term assisting the transitioning, an observer to estimate the current state of the airflow in the conditioned environment by transitioning the previous state of the airflow forward in time according to the model of airflow dynamics to reduce the observation error in the current state of the airflow, and a controller to control the air-conditioning system based on the current state of the airflow. The first term in the model includes a projection of a physical model of the airflow on a finite-dimensional space.

Abstract: A method for estimating a state of a battery determines, using a sensor, physical quantities of the battery indicative of a charge of the battery to produce a measured charge of the battery. The method also estimates the physical quantities of the battery using a model of the battery stored in a memory to produce an estimated charge of the battery and updates at least one parameter of the model of the battery to reduce a difference between the measured charge of the battery and the estimated charge of the battery. The method determines the state of the battery using the updated model of the battery.

Abstract: A Digital Power-Amplifier (DPA) system includes a power amplifier (PA) circuit having control inputs and an output for generating output signals, and an adaptive control circuit that comprises an input interface, an output interface, a memory storing an adaptive control algorithm and a processor performing instructions based on the adaptive control algorithm in connection with the memory, wherein the input interface receives input-state signals and output signals of the DPA circuit, wherein the adaptive control algorithm determines, in response to the input-state signals and the output signals, control parameters of control signals transmitted to the control inputs from the output interface for controlling operations of the DPA circuit.

Abstract: Systems and methods for determining flows by acquiring a video of the flows with a camera, wherein the flows are pedestrians in a scene. The video includes a set of frames, wherein motion vectors are extracted from each frame in the set, and a data matrix is constructed from the motion vectors in the set of frames. A low rank Koopman operator can be determined from the data matrix and a spectrum of the low rank Koopman operator can be analyzed to determine a set of Koopman modes. Then, the frames are segmented into independent flows according to a clustering of the Koopman modes.

Abstract: An elevator system includes an elevator car supported by an elevator rope wrapped around a sheave, such that a rotation of the sheave changes a length of the elevator rope between the sheave and the elevator car thereby controlling a movement of the elevator car within an elevator shaft of the elevator system. An elevator cable is connected to the elevator car and the elevator shaft to carry electrical signals to the elevator car. The operation of the elevator system is controlled in response to receiving a call for a movement of the elevator car requesting a change of the length of the elevator rope. A motion profile of the elevator car causing the requested change of the length of the elevator rope that minimizes the sway of the cable is determined according to a model of a cable relating a sway of the cable to a motion profile. Next, the motion of the elevator car is controlled according to the determined motion profile.

Abstract: A method determines values of the airflow measured in the conditioned environment during the operation of the air-conditioning system and selects, from a set of regimes predetermined for the conditioned environment, a regime of the airflow matching the measured values of the airflow. The method selects, from a set of models of the airflow predetermined for the conditioned environment, a model of airflow corresponding to the selected regime and models the airflow using the selected model. The operation of the air-conditioning system is controlled using the modeled airflow.

Abstract: An elevator system includes an elevator car supported by an elevator rope wrapped around a sheave, such that a rotation of the sheave changes a length of the elevator rope between the sheave and the elevator car thereby controlling a movement of the elevator car within an elevator shaft of the elevator system. An elevator cable is connected to the elevator car and the elevator shaft to carry electrical signals to the elevator car. The operation of the elevator system is controlled in response to receiving a call for a movement of the elevator car requesting a change of the length of the elevator rope. A motion profile of the elevator car causing the requested change of the length of the elevator rope that minimizes the sway of the cable is determined according to a model of a cable relating a sway of the cable to a motion profile. Next, the motion of the elevator car is controlled according to the determined motion profile.

Abstract: A voltage at a point of common coupling (PCC) between a photovoltaic (PV) system and a power grid is regulated by a controller having a gain determined according to a gain function that is a function of a time. The gain function is determined based on an error between the voltage measured at the PCC and the reference voltage, and the gain is updated according to the updated gain function and a current instance of time. The controller generates a modulating signal using the updated gain and the voltage at the PCC is regulated according to the modulating signal.

Abstract: Systems and methods for determining flows by acquiring a video of the flows with a camera, wherein the flows are pedestrians in a scene. The video includes a set of frames, wherein motion vectors are extracted from each frame in the set, and a data matrix is constructed from the motion vectors in the set of frames. A low rank Koopman operator can be determined from the data matrix and a spectrum of the low rank Koopman operator can be analyzed to determine a set of Koopman modes. Then, the frames are segmented into independent flows according to a clustering of the Koopman modes.