Abstract: Embodiments of the present disclosure disclose a method and a system for controlling a motion of an electric vehicle (EV). The method includes determining a velocity profile moving the EV from an initial velocity over a period of time by minimizing the energy dissipation according to an energy-loss function. The energy-loss function maps values of acceleration and velocity of the EV to energy dissipation of the EV resulting from controlling one or multiple electric motors of the EV to move the EV at corresponding acceleration and velocity values. The velocity profile is a function of time. The method further includes controlling the one or multiple electric motors of the EV to generate a torque for moving the EV according to the velocity profile.

Abstract: An artificial intelligence (AI) low-latency processing system is provided. The low-latency processing system includes a processor; and a memory having instructions stored thereon. The low-latency processing system is configured to collect a sequence of frames jointly including information dispersed among at least some frames in the sequence of frames, execute a timing neural network trained to identify an early subsequence of frames in the sequence of frames including at least a portion of the information indicative of the information, and execute a decoding neural network trained to decode the information from the portion of the information in the subsequence of frames, wherein the timing neural network is jointly trained with the decoding neural network to iteratively identify the smallest number of subframes from the beginning of a training sequence of frames containing a portion of training information sufficient to decode the training information.

Abstract: A satellite for implementing a protocol associated with a distributed satellite position verification system is provided. The satellite, on implementing the protocol, verifies records of positions of one or more other satellites in the distributed satellite position verification system. According to the protocol, the satellite performs, at different time instances, a first operation, a second operation, or a third operation to act as a first satellite, a second satellite, or a third satellite, respectively in the distributed satellite position verification system. When the first satellites performs the first operation, the first satellite verifies at least some positions in the records of positions of the second satellite such that the first satellite: determines a verified position of the second satellite; calculates a deviation between the verified position and a prior estimated position of the second satellite; and records the verified position into the records, based on the calculated deviation.

Abstract: A system jointly estimates states of GNSS receivers moving in a region using measurements of a Global Navigation Satellite System (GNSS). The system clusters the GNSS receivers into different clusters subject to a constraint on an upper bound on each cluster and executes a set of probabilistic filters corresponding to the set of clusters to estimate the states of GNSS receivers in each cluster. Each probabilistic filter estimates the states of the GNSS receivers in a corresponding cluster by fusing the GNSS data collected from the GNSS receivers in the cluster to jointly reduce an estimation error of each of the GNSS receivers in the cluster. The DES updates the cluster assignments based on a measure of estimation error in the states of different GNSS receivers in different clusters.

Abstract: Embodiments for distributing energy for an energy system having an energy generation source, an energy storage system and a load. The method including identifying a risk level for the energy system, the risk level having objectives prioritized relative to one another. Calculating an objective function based on values including energy market values, electricity rates, and power producing, storing and consumption. Identifying an Optimized solution for charging or discharging the energy storage system based on the objective function. Controlling the distribution of energy to the energy storage system for charging according to the Optimized solution based on the objective function and discharging according to the Optimized solution. The objective function is Optimized using feasibility constraints, again Optimized using technical constraints and additional constraints.

Abstract: A controller controls a motion of an object performing a task for changing a state of the object from a start state to an end state while avoiding collision of the object with an obstacle according to an optimal trajectory determined by solving an optimization problem of the dynamics of the object producing an optimal trajectory for performing the task subject to constraints on a solution of first-order stationary conditions modeling a minimum distance between the convex hull of the object and the convex hull of the obstacle using complementarity constraints.

Abstract: A controller of a machine determines jointly a sequence of control inputs defining a state trajectory of the machine and a desired knowledge of the environment by solving a multivariable constrained optimization of a model of dynamics of the machine relating the state trajectory with the sequence of control inputs subject to a constraint on admissible values of the states and the control inputs defined based on the desired knowledge of the surrounding environment represented by the state of the environment and the uncertainty of the state of the environment determined from the measurements of the environment. In such a manner, the controller performs joint but imbalance optimization of the control inputs and the sensing instructions to the sensor for learning the environment.

Abstract: A system and a method for tracking an expanded state of an object including a kinematic state indicative of a position of the object and an extended state indicative of one or combination of a dimension and an orientation of the object is provided herein. The system comprises at least one sensor configured to probe a scene including a moving object with one or multiple signal transmissions to produce one or multiple measurements of the object per the transmission, and a processor configured to execute a probabilistic filter tracking a joint probability of the expanded state of the object estimated by a motion model of the object and a measurement model of the object, wherein the measurement model includes a center-truncated distribution having predetermined truncation intervals. The system further comprises an output interface configured to output the expanded state of the object.

Abstract: A device for controlling an operation of a system performing a task determines a current control input based on the feedback signal by solving a polynomial optimization of a polynomial function with a reformulation derived by introducing additional variables reducing the degree of the polynomial function till a target degree subject to constraints on a structure of the additional variables. The device solves a mixed-integer optimization problem to find a subset of encodings among all possible encodings of factorizations of the polynomial function that reduce the degree of the polynomial function to the target degree with a predetermined minimum number of additional variables and selects an optimal encoding from the subset of encodings with an optimal relaxation bound.

Abstract: Devices and methods of a field effect transistor device that include a source, a gate and a drain. The transistor includes a semiconductor region position is under the source, the gate and the drain. Such that the semiconductor region can include a gallium nitride (GaN) layer and an III Nitride (III-N) layer. Wherein the GaN layer includes a band gap, and the III-N layer includes a band gap. Such that the III-N layer band gap is higher than the GaN layer band gap. A sub-region of the semiconductor region is located underneath the gate and is doped with Mg ions at selective locations in the sub-region.

Abstract: Systems and methods for image processing for determining a registration map between a first image of a scene with a second image of the scene, include solving an optimal transport (OT) problem to produce the registration map by optimizing a cost function that determines a minimum of a ground cost distance between the first and the second images modified with an epipolar geometry-based regularizer including a distance that quantifies the violation of an epipolar geometry constraint between corresponding points defined by the registration map. The ground cost compares a ground cost distance of features extracted within the first image with a ground cost distance of features extracted from the second image.

Abstract: An autotuning controller is provided for improving power efficiency and linearity of digital power amplifiers (DPAs). The controller includes an interface including input and output terminals connected to the DPAs, the interface being configured to acquire input signals and output signals, a digital pre-distortion (DPD)-DPA adaptive controller including a processor and a memory running and storing a DPD algorithm, an efficiency enhancement method and a learning cost function.

Abstract: An anomaly detector for detecting anomaly in input data comprises an auto-encoder trained to encode the input data and decode the encoded input data to reconstruct the input data. Further, the anomaly detector comprises a classifier trained to determine a reconstruction loss indicative of a difference between the accepted input data and the reconstructed input data, where the reconstruction loss includes a weighted combination of a plurality of loss functions evaluating reconstruction losses of a plurality of parts of the reconstructed input data, different types of loss functions, or both. The classifier is further configured to detect an anomaly in the reconstructed input data when the reconstruction loss is above a threshold.

Abstract: A global multi-vehicle decision making system is disclosed for providing real-time motion planning and coordination of one or multiple connected and automated and/or semi-automated vehicles (CAVs) in an interconnected traffic network that includes one or multiple non-controlled vehicles (NCVs), one or multiple conflict zones and one or multiple conflict-free road segments. The system includes a receiver configured to acquire infrastructure sensing signals, at least one memory configured to store map and programs, and at least one processor configured to perform steps of formulating a global mixed-integer programming (MIP) problem using the infrastructure sensing signals, computing a motion plan for each CAV and each NCV in the traffic network by solving the global MIP problem, computing an optimal sequence of entering/exiting times and a sequence of average velocities for each CAV and each NCV, and computing a velocity profile and/or one or multiple planned stops for each CAV.

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: Drift-based rendezvous control system for controlling an operation of a spacecraft to rendezvous the spacecraft to a goal region over a finite time (FT) horizon. The system including accepting data including values of spacecraft states at a specified time period within the FT horizon. A processor at the specified time period selects a set of drift regions corresponding to a desired goal region at a location on an orbit where the target is located at the specified time period. Update a controller having a model of dynamics of the spacecraft with the accepted data. Formulate the set of drift regions as a penalty in a cost function of the updated controller. Generate control commands resulting in a real-time drift-based control policy where upon entering the drift region, the thrusters are turned off in order to minimize an amount of operation of the thrusters while rendezvousing with the desired goal region.

Abstract: To control a motion of a device subject to constraints, a sequence of states and corresponding control inputs are transformed into a lifted space to determine a linear model of the dynamics of the device in the lifted space by minimizing fitting errors between the lifted states and approximation of the lifted states according to the linear control law. The fitting errors define an error model as a function bounding a data-driven envelope of a Lipschitz continuity on the fitting errors allowing to solve an optimal control problem in the lifted space according to the linear model subject to the constraints reformulated based on an evolution of the error model. The control input in the lifted space is transformed back to the original space for control.

Abstract: An artificial intelligence (AI) system that includes a processor configured to execute modules of the AI system. The modules comprise a feature extractor, an adversarial noise generator, a compressor and a classifier. The feature extractor is trained to process input data to extract features of the input data for classification of the input data. The adversarial noise generator is trained to generate noise data for distribution of features of the input data such that a misclassification rate of corrupted features that include the extracted features corrupted with the generated noise data is greater than a misclassification rate of the extracted features. The compressor is configured to compress the extracted features. The compressed features are closer to the extracted features than to the corrupted features. The classifier is trained to classify the compressed features.

Abstract: Systems and methods controlling an operation of a vehicle in real time to rendezvous the vehicle with a target over a finite time horizon having multiple specified time periods. Select a set of unsafe regions from stored unsafe regions, the set of unsafe regions represents regions of space around the target in which any operation of the PSNO thrusters does not avoid collision with the target, guaranteeing collision trajectories with the target. Formulating the set of unsafe regions as safety constraints, and updating a controller having a model of dynamics of the vehicle with the accepted data. Generating control commands by subjecting the updated controller to the safety constraints to produce a rendezvous trajectory that avoids the set of unsafe regions, guaranteeing an operation of at least the PSNO thrusters, in the event of partial vehicle thruster failure results in a trajectory that does not collide with the target.

Abstract: A system a method for controlling an operation of HVAC system is provided. The system comprises at least one processor; and memory having instructions stored thereon that, when executed by the at least one processor, cause the system to receive data indicative of the operation of the HVAC system and optimize a cost function to reduce a difference between a full thermal state of the conditioned environment simulated from the received data based on a physical model of airflow including a partial differential equation (PDE) and a thermal state of the conditioned environment reconstructed by an observer using a reduced order model (ROM) of airflow including an ordinary differential equation (ODE) from values of the full thermal state at a set of locations, wherein optimization of the cost function is a multivariable optimization of a structure of the observer and a structure of the ODE.