A method for synchronizing virtual and real statuses of a digital twin system of an unmanned aerial vehicle (UAV) includes: performing parameter configuration for a virtual object system and a physical object system of the UAV; performing time synchronization between the virtual object system and the physical object system; detecting an event trigger type, wherein the event trigger type is a training event or a monitoring event; and triggering a corresponding synchronization controller based on the detected event trigger type, such that the synchronization controller performs result synchronization and process synchronization for the virtual object system and the physical object system based on the event trigger type, where a synchronization controller corresponding to the training event is a controller for synchronizing a physical object to a virtual object, and a synchronization controller corresponding to the monitoring event is a controller for synchronizing the virtual object to the physical object.

A two-wheeled vehicle is provided. The two-wheeled vehicle includes a chassis, and a first wheel carriage moveably coupled to, and longitudinally displaceable relative to the chassis. At least a first wheel is rotationally mounted on the first wheel carriage, and coupled to the chassis through the first wheel carriage. The two-wheeled vehicle further includes a first linear actuator system coupled to the first wheel carriage, and configured to longitudinally displace the first wheel carriage relative to the chassis. A first motor is mounted to the first wheel and the first wheel carriage. The first motor is configured to provide a drive energy to the first wheel, and to be displaced along with the first wheel carriage as the first wheel is displaced by the first linear actuator system.

A method for event processing includes accepting for processing, as accepted events and according to a target rate limit, at least a subset of received events; associating respective ingested timestamps with the accepted events; associating respective processing completion timestamps with processed events of the accepted events; determining an average measured lag time using at least a subset of the respective processing completion timestamps and corresponding respective ingested timestamps; obtaining a throttled rate limit using a proportional-integral-derivative (PID) controller; and accepting subsequent events according to the throttled rate limit. The PID controller can be configured to use, as an input, an error value that is a difference between a target lag time and the average measured lag time. An integral part of the PID controller can be set to zero responsive to an accumulated average lag time being less than the target lag time.

A method for event processing includes accepting for processing, as accepted events and according to a target rate limit, at least a subset of received events; associating respective ingested timestamps with the accepted events; associating respective processing completion timestamps with processed events of the accepted events; determining an average measured lag time using at least a subset of the respective processing completion timestamps and corresponding respective ingested timestamps; obtaining a throttled rate limit using a proportional-integral-derivative (PID) controller; and accepting subsequent events according to the throttled rate limit. The PID controller can be configured to use, as an input, an error value that is a difference between a target lag time and the average measured lag time. An integral part of the PID controller can be set to zero responsive to an accumulated average lag time being less than the target lag time.

A device for digitally controlling a system, operating by discrete time steps, based on an error vector received at each time step, which includes: an estimator determining a homogenous canonical norm value range for a current time step, an error vector of a current time step, an expansion generator matrix, a Lyapunov matrix, lower and upper limits; and a computer that returns a control for the current time step based on the sum between the error vector of the current time step multiplied by a factor of a feedback gain matrix, the homogenous canonical norm value range for a current time step, proportional and derivative coefficients and the expansion generator matrix, and the integral between the first time step and the current time step of a product associating an integral coefficient, the expansion generator matrix, the homogenous canonical norm value range for all the time steps and the error vector.

Systems and methods for dynamic predictive control of autonomous vehicles are disclosed. In one aspect, an in-vehicle control system for a semi-truck includes one or more control mechanisms configured to control movement of the semi-truck and a processor. The system further includes computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the processor to receive a desired trajectory and a vehicle status of the semi-truck, determine a dynamic model of the semi-truck based on the desired trajectory and the vehicle status, determine at least one quadratic program (QP) problem based on the dynamic model, generate at least one control command for controlling the semi-truck by solving the at least one QP problem, and provide the at least one control command to the one or more control mechanisms.

An aerosol provision device includes a housing; circuitry; and a coupler or a receptacle structured to engage and hold a consumable including aerosol-generating material. The aerosol provision device or the consumable includes an aerosol generator powered to energize the aerosol-generating material. The circuitry includes a pressure sensor and a temperature sensor. The circuitry also includes a high-side load switch coupled to or coupleable with the aerosol generator, and processing circuitry coupled to the high-side load switch, the pressure sensor, and the temperature sensor. The processing circuitry is configured to output a modulated signal with an adjustable duty cycle to cause the high-side load switch to connect and disconnect power to the aerosol generator based on the measurements of pressure and temperature. The processing circuitry is configured to implement a proportional-integral-derivative (PID) algorithm to adjust the duty cycle based on pressure and temperature according to a predetermined relationship.

A method of automatically tuning a proportional-integral-derivative (PID) controller (102) controlling a DC-DC converter (100) includes substituting the PID controller (102) with a modified relay feedback test (MRFT) (104) controller having a threshold parameter (β) and a magnitude parameter (h), iteratively determining a current error signal (e [k]) by measuring an output voltage (Vo[k]) of the DC-DC converter (100) and comparing it to a desired reference output voltage (Vo-ref), input the error signal (e[k]) to the MRFT (104), determining an output value (u[k]) of the MRFT, update the duty cycle (D) based on the output value (u[k]), operating the DC-DC converter (100) using the updated duty cycle (D), exciting oscillations in the loop containing the MRFT (104) and the DC-DC converter (100), measuring a frequency (Ω0) and amplitude (α0) of the output voltage (Vo[k]), updating PID controller parameters based on the frequency (Ω0) and amplitude (α0), and substituting the MRFT (104) with the PID controller (102).

Accepted events are processed. Each accepted event is associated with a respective ingested timestamp, a respective processing-start timestamp, and a respective processing-complete timestamp. Events are accepted at a rate of a target rate limit. A current error value is obtained as a difference between a target lag time and a second value. The target lag time indicates a configured maximum time within which an accepted event is to be processed. The second value is an average of differences between the respective processing-complete timestamps and the respective ingested timestamps. A base throttle is obtained based on previous error values and the current error value. The base throttle is smaller than the target rate limit and indicates a maximum number of events per a unit of time to be accepted for processing. Subsequent events are accepted at a new rate obtained from the base throttle.

The present disclosure provides systems and methods for controlling temperature in a radiofrequency (RF) ablation system. A temperature control system includes a subtractor circuit configured to calculate a temperature error as a difference between a target temperature and a measured temperature at a tip of a cannula, and a proportional-integral-derivative (PID) controller coupled to the subtractor circuit and configured to apply an RF voltage to the tip of the cannula, the PID controller configured to determine the RF voltage based on the temperature error and a proportional coefficient, an integral coefficient, and a derivative coefficient of the PID controller. The temperature control system further includes a PID coefficient controller coupled to the PID controller, the PID coefficient controller configured to dynamically adjust the proportional, integral, and derivative coefficients of the PID controller during operation of the RF ablation system.