Mitsubishi Electric Research Laboratories, Inc.

Claus Danielson

Stefano Di Cairano

Ankush Chakrabarty

Karl Berntorp

Avishai Weiss

Yebin Wang

Scott Bortoff

Rien Quirynen

Christopher Laughman

Daniel J Burns

Heejin Ahn

Di Chen

Weinan Gao

Junqiang Zhou

An extremum seeking control system and a method for controlling a system is provided. The method comprises receiving a tracking error, consecutive measurements of a system output, and consecutive measurements of a cost function of the system, and estimating a gradient based on the tracking error, the consecutive measurements of the system output, and the consecutive measurements of the cost function of the system. The method further comprises determining a step-size based on a ratio of a covariance of the gradient to the gradient, and determining a set-point optimizing performance of the system, based on the gradient and the step-size. The method further comprises controlling the system based on the set-point optimizing performance of the system.

Extremum seeking control system and a method for controlling a system

A controller and a method for controlling motion of a vehicle is provided. The method comprises acquiring motion information including a current state of the vehicle and a desired state of the vehicle, determining a combination of a steering angle of the wheels and motor forces for moving the vehicle from the current state into the desired state by using a first model of the motion of the vehicle and a second model of the motion of the chassis of the vehicle, determining a cost function of the motion of the vehicle, optimizing the cost function of the motion of the vehicle to compute a command signal for controlling the steering wheel and the plurality of electric motors, and controlling the steering angle of the wheels and the motor forces based on the command signal.

System and method for controlling motion of a vehicle technical field

A control system for wheel-slip prevention in a railway vehicle with a pneumatic brake is provided. The control system comprises an input interface configured to accept a deceleration reference for controlling the pneumatic brake, and a memory configured to store a reference governor providing executable instructions for modifying the deceleration reference upon its violation of a wheel-slip constraint, and configured to store a controller providing executable instructions for mapping the modified deceleration reference to a sequence of control commands for controlling pressure applied by the pneumatic brake. The control system further comprises a processor configured to execute the reference governor to modify the deceleration reference and configured to execute the controller to map the modified deceleration reference to the sequence of control commands. Further, an output interface of the control system is configured to output the sequence of control commands to control the pneumatic brake.

System and method for wheel-slip prevention in railway vehicles with pneumatic brakes

A control system for controlling a set of actuators of a system. The control system comprising a switcher configured to select a subset of setpoints from a set of setpoints that control the corresponding set of actuators. An extremum-seeking controller (ESC) configured to perturb a subset of setpoints at each iteration based on a probabilistic distribution of partial gradients of a cost function relating values of the subset of setpoints to a cost of operation of the system. A stochastic gradient estimator is configured to estimate a full gradient of the cost function and update the estimation of the full gradient based on the probabilistic distribution of the partial gradients generated at each ESC iteration. A feedback controller is configured to drive a state of the subset of actuators of the system towards the corresponding perturbed subset of setpoints.

Extremum seeking control with stochastic gradient estimation

A computing system for generating optimal tracking control (TC) policies for controlling a machine to track a given time-varying reference (GTVR) trajectory. An updated augmented state of the machine is obtained. Stored in memory is the GTVR trajectory, a constraint-admissible invariant set (CAIS) of machine states satisfying machine state constraints and a corresponding TC policy mapping a machine state within the CAIS to a control input satisfying control input rate constraints. A processor jointly controls the computing system to control the operation to drive an augmented state of the machine to zero, and update the CAIS and TC policy. Joint control includes using a sequence of control inputs and a sequence of augmented machine states within CAIS corresponding to the sequence of tracking control inputs. Execute a constrained tracking approximate dynamic programming (TADP) using the received data to update the value function, update the CAIS and the corresponding TC policy.

System and method for feasibly positioning servomotors with unmodeled dynamics

A receding horizon state estimator estimates state of a vehicle such as to reduce total communication cost of acquiring external measurements over a prediction horizon, in which state estimation accuracy for a time step is a function of state estimation accuracy for a previous time step. For each time step of the prediction horizon, estimator selects a subset of external sensors with external measurements sufficient to estimate the state with accuracy satisfying the constraint on state estimation accuracy for the corresponding time step while reducing a total communication cost of acquiring the external measurements over the prediction horizon. The estimator requests the external measurements from the subset of external sensors determined for a current time step and estimates the state of the vehicle using the internal and the requested external measurements.

Receding horizon state estimator

A machine subject to state and control input constraints is control, while the control policy is learned from data collected during an operation of the machine. To ensure satisfaction of the constraints, the state of machine is maintained within a constraint admissible invariant set (CAIS) satisfying the constraints and the machine is controlled with corresponding control policy mapping a state of the system within the CAIS to a control input satisfying the control input constraints. The machine is controlled using a constrained policy iteration, in which a constrained policy evaluation updates CAIS and value function and a constrained policy improvement updates control policy that improves the cost function of operation according to the updated CAIS and the corresponding updated value function.

System and method for data-driven control of constrained system

A control system of a vehicle for controlling motion of the vehicle traveling on a road shared with a set of moving objects include a memory to store a set of regions of states of lateral dynamic of the vehicle corresponding to a set of equilibrium points. Each region defines a control invariant set of the states of the lateral dynamic determined for different speeds of the vehicle, such that the vehicle having a state within a region determined for a speed is capable to maintain its states within the region while moving with the speed. Each region includes a corresponding equilibrium point and intersects with at least one adjacent region. Each equilibrium point is associated with one or multiple regions determined for different speeds. A collision detector to detect a collision of each region with at least one object at each time step of control in a time horizon when a trajectory of the object at the time step of control intersects a space defined by a longitudinal displacement of the vehicle at the time step of control and a range of values of the lateral displacement of the region to produce a data structure indicating a collision-free region at different time steps of control. A path planner determines a time sequence defining a collision free sequence of regions forming a union of regions in space and time connecting a region including an initial displacement with a region including a target displacement to produce a trajectory within the union connecting the initial displacement with the target displacement. A controller controls the vehicle according to the trajectory.

System and method for controlling motion of vehicle with variable speed

A control system uses a set of regions of states of lateral dynamic of the vehicle corresponding to a set of equilibrium points to control a vehicle. Each region defines a control invariant set of the states of the lateral dynamic determined such that the vehicle having a state within a region is capable to maintain its states within the region. Each region includes a corresponding equilibrium point and intersects with at least one adjacent region. The control system identifies collision-free regions at different time steps of control to produce a collision free sequence of regions forming a union of regions in space and time connecting a region including an initial displacement with a region including a target displacement. The control system produces a trajectory within the union connecting the initial displacement with the target displacement and control the vehicle according to the trajectory.

System and method for controlling lateral motion of vehicle

A method for controlling an operation of a machine exhibiting symmetries in dynamics of the machine, a cost of the operation of the machine, and constraints on the operation of the machine performs iteratively a control optimization until a termination condition is met to produce an optimal control input and controls the machine according to the optimal control input. An iteration includes transforming control inputs to the machine, a state of the machine, an output of the machine, and dual variables from an original domain to a symmetric domain using a symmetric transformation, solving an optimal control problem of the control inputs and the state for fixed values of the output and the dual variables in the symmetric domain, transforming the control inputs and the state from the symmetric domain into the original domain using an inverse of the symmetric transformation; projecting the outputs corresponding to the control inputs and the state in the original domain onto the constraints, and updating the dual variable based on the projected outputs.

Symmetry alternating direction method of multipliers

A computer-implemented system for generating a controller to control a heating, ventilation, and air conditioning (HVAC) system decomposes a model of the HVAC system into a collection of transformed models defining relationship between input channels and output channels with decoupled dynamics, such that a single input channel affects only one corresponding output channel Each input channel is defined by a weighted combination of control inputs to the HVAC system, and each output channel is defined by a weighted combination of temperatures affected by operation of the HVAC system. The collection of decoupled transformed models includes a first transformed model modeling dynamics of the outdoor unit as a relationship between uniform control for the set of indoor units and the average temperature in the set of rooms and includes a set of second transformed models. Each second transformed model models a difference between room dynamics and room coupling dynamics. The system generates a decouple controller for each transformed model to form a collection of decoupled controllers, wherein, each decouple controller defines a relationship between measurements the output channel and inputs to the input channel of the corresponding transformed model.

System and method for generating a controller for multi-zone heating, ventilation, and air conditioning system

An operation of the machine is iteratively controlled with control inputs determined from an optimization of a cost function along a prediction horizon subject to constraints on the control inputs. The optimization is performed according to the model and the cost function includes at least one parameter of the model. During at least some iterations of the control, the parameter of the model is updated resulting in updating the cost function.

Model predictive control with uncertainties

A system controls a multi-zone vapor compression system (MZ-VCS). The system includes a controller to control a vapor compression cycle of the MZ-VCS using a set of control inputs determined by optimizing a cost function including a set of control parameters. The optimizing is subject to constraints, and wherein the cost function is optimized over a prediction horizon. The system also includes a memory to store an optimization function parameterized by a configuration of the MZ-VCS defining active or inactive modes of each heat exchanger, the optimization function modifies, according to a current configuration, values of the control parameters of the cost function determined for a full configuration that includes all heat exchangers in the active mode. The system also includes a processor to determine the current configuration of the MZ-VCS and to update the cost function by submitting the current configuration to the optimization function.

System and method for controlling multi-zone vapor compression system

Methods and systems for controlling a train movement to a stop at a stopping position between a first position and a second position. Determining constraints of a velocity of the train with respect to a train position forming a feasible region (FR) for a state of the train during the movement, such that a lower curve bounding the FR has a zero velocity only at the first position, and an upper curve bounding the FR has a zero velocity only at the second position. Determining a control invariant subset (CIS) of the FR, wherein for each state within the CIS there is at least one control action having a value selected from a finite set of values that maintains the state of the train within the CIS. Controlling train movement subject to constraints by selecting a control action maintaining the state of the train within the CIS of the FR.

Train automatic stopping control with quantized throttle and braking

Systems and methods for controlling a motion of an object from an initial location to a final location within a region while avoiding a set of obstacles located in the region. The systems and methods include selecting, the equilibrium points within the obstacle-free region of the region, and each equilibrium point includes a corresponding controller driving the object to the equilibrium point, such that each controller includes a corresponding state partition. Designing the controller and the corresponding state partition, based on the obstacle-free region around the equilibrium point, to produce a collection of controllers and corresponding equilibrium points and corresponding state partitions, that connect the initial location with the final location. Determining actuator commands at time T using a controller corresponding to a state partition that includes the location of the object at time T, and the resulting sequence over a period of time of actuator commands, moves the object.

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Somerville, MA, United States of America

Claus Danielson