Abstract:
A computer-implemented method is provided. The computer-implemented includes a data-driven model and a robust closure model stored in a memory by using a processor for controlling a system. The computer-implemented method includes steps of acquiring sensor signals from at least one sensor of the system via an interface, computing a state of the system based on the sensor signals, determining a gain of the robust closure model based on the state of the system, reproducing a state of the system based on the determined gain, estimating a physics-based model of the system by combining the data-driven model and the robust closure model, and generating control commands by mapping the state of the system using the estimated physics-based model.
Abstract:
A system for parameter tuning for robotic manipulators is provided. The system includes an interface configured to receive a task specification, a plurality of physical parameters, and a plurality of control parameters, wherein the interface is configured to communicate with a real-world robot via a robot controller. The system further includes a memory to store computer-executable programs including a robot simulation module, a robot controller, and an auto-tuning module a processor, in connection with the memory. In this case, the processor is configured to acquire, in communication with the real-world robot, state values of the real-world robot, state values of the robot simulation module, simultaneously update, by use of a predetermined optimization algorithm with the auto-tuning module, an estimate of one or more of the physical, and said control parameters, and store the updated parameters.
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:
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 method controls an operation of an elevator system including an elevator car moving within an elevator shaft and at least one elevator cable connected to the elevator car and the elevator shaft. The method determines, during the operation of the elevator system, a velocity of a sway of the elevator cable and modifies, in response to the determining, a damping coefficient of a semi-active damper actuator connected to the elevator cable according to a function of the velocity of the sway.
Abstract:
A method and system determines flows by first acquiring a video of the flows with a camera, wherein the flows are pedestrians in a scene, wherein the video includes a set of frames. 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 is determined from the data matrix and a spectrum of the low rank Koopman operator is 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:
A method controls an operation of an elevator system including an elevator car moving within an elevator shaft and at least one elevator cable connected to the elevator car and the elevator shaft. The method determines, during the operation of the elevator system, a velocity of a sway of the elevator cable and modifies, in response to the determining, a damping coefficient of a semi-active damper actuator connected to the elevator cable according to a function of the velocity of the sway.
Abstract:
A method controls an operation of an air-conditioning system generating airflow in a conditioned environment. The method updates a model of airflow dynamics connecting values of flow and temperature of air conditioned during the operation of the air-conditioning system. The model is updated interactively iteratively to reduce an error between values of the airflow determined according to the model and values of the airflow measured during the operation. Next, the method models the airflow using the updated model and controls the operation of the air-conditioning system using the model.
Abstract:
A distributed energy resource (DER) exchanges with each neighboring DER portions of the total demand for power accumulated by the DER and each neighboring DER and portions of a total capability of the network to generate the total power accumulated by the DER and each neighboring DER before each communication step. The DER updates the portion of the total demand for power and total capability accumulated by the DER using the portions of the total demand and the portions of the total capability received from the neighboring DERs. After the fixed number of communication steps, the DER accumulates the total demand for power and the total capability of the network and generates an amount of the power as a product of the total demand for the power and a ratio of a maximum capability of the DER to generate the power and the total capability of the network.
Abstract:
A method reduces a sway of an elevator rope supporting an elevator car within an elevator system using an elevator sheave. The method controls, using a movement of the elevator sheave, a tension of the elevator rope according to a control law of the tension of the elevator rope between a first point and a second point. The first point is associated with a contact of the elevator rope with the elevator sheave. The second point is associated with a contact of the elevator rope with the elevator car or a counterweight of the elevator car. The control law is a function of one or combination of a relative position, a relative velocity and a relative acceleration between the first and the second points.