An explainer system includes a system-monitor machine learning model trained to predict states of a monitored system, a perturbator applying predetermined perturbations to original sample data collected from the monitored system to produce perturbed sample data. The system is configured to input the perturbed sample data to the prediction system. The explainer comprises a tester that receives model output from the prediction system, the model output comprising original model output produced by the system-monitor machine learning model based on the original sample data and deviated model output produced by the system-monitor machine learning model based on the perturbed sample data, the deviated model output comprising deviations from the original model output, the deviations resulting from the applied perturbations. An extractor receives data defining the perturbations and the resulting deviations and extracts therefrom important features for explaining the model output.

A method for automating system identification includes performing a system identification experiment, and performing a system identifying processing by fitting a model to data from the system identification experiment. The method also includes performing model reduction to generate a model numerically suitable for controller synthesis by removing inconsequential states that cause controller optimization methods to fail. The method further includes performing control synthesis using the generated model or reduced models, including disturbance spectrum estimates, to generate a candidate controller design to be used during system operation. The method also includes checking for controller robustness using the identified model to ensure stability of the system while maximizing closed-loop bandwidth and performance.

Trajectory optimization is process of designing a trajectory of operating variables that optimizes measure of performance while satisfying a set of constraints, when the system moves from one state to another. It is very necessary to achieve optimization in real time. A system and method for real-time trajectory optimization has been provided. The trajectory optimization of a process can be performed in any dynamical automated system. The system is configured to optimize the trajectory in both online and offline mode. In the online mode, the system optimizes the trajectory of the process in real-time. The system has the ability to handle both machine learning and deep learning based time series models along with first principles based models represented by ordinary/partial differential equation or differential algebraic equation based dynamic models of the process to estimate process variables given the disturbance profile and the actuation profile of manipulated variables.

A synchronous machine includes a stator with stator windings connected with stator terminals to an electrical grid and a rotor with rotor windings rotatable mounted in the stator, wherein a voltage regulator of the synchronous machine is adapted for outputting an excitation signal to adjust a current in the rotor windings for controlling the synchronous machine. A method for determining control parameters for the voltage regulator includes (i) receiving a first time series of values of the excitation signal and a second time series of measurement values of the terminal voltage in the stator terminals, (ii) determining coefficients of a system transfer function of the synchronous machine, and (iii) determining the control parameters for the voltage regulator from the coefficients of the system transfer function.

Systems and methods for generating an action strategy to be executed by an autonomous system are disclosed. The action strategy comprises a series of actions to be performed by the autonomous system to accomplish a corresponding active objective in response to detecting an abnormal event, the abnormal events occurring or having occurred in an environment where the autonomous system is configured to operate. The method comprises accessing a first database populated with event descriptions corresponding to abnormal events and accessing a second database populated with candidate objectives. Each candidate objective defines a task accomplishable by the autonomous system and comprises an activation condition and a progressive task unit structure describing a hierarchy of actions to be performed in order to accomplish the corresponding candidate objective. An execution of a candidate objective generating an action strategy from the progressive task unit structure of the active objective and executing the action strategy.

A system and method for performing management and diagnostic functions in an advanced process control (APC) system. An APC management computer retrieves operating process data from an APC control computer and performs an iterative step test on the APC system. The iterative step test modifies at least one test parameter of the operating process data and identifies changes to a set of remaining parameters of the operating process data resulting from modification of the test parameter. The APC management computer determines at least one process variable from the iterative step test and generates at least one process model based on the process variable. The APC management computer transmits the process model to the APC control computer.

The disclosure discloses a customized harmonic repetitive controller and a control method, and belongs to the field of repetitive controllers for industrial control. In the repetitive controller, a periodic signal generator formed by three time-delay modules and a positive feedforward gain module is taken as a whole to form a forward path, and an internal model of a periodic signal is constructed in the form of outputting positive feedback. Therefore, the structure of the repetitive controller conforms to a standard internal model construction method, the repetitive controller has an order expanding capability, the flexibility of the controller is greatly improved, the disturbance canceling speed of the controller is increased, and the repetitive controller is simple in structure and convenient to design. An h-order nk±m-order-harmonic repetitive controller (h≥2) obtained by further expansion covers various existing high-order repetitive controllers, and a unified form is provided to make the repetitive controller universal.

Various examples are provided that are related to boundary control in membrane distillation (MD) processes. In one example, a system includes a membrane distillation (MD) process comprising a feed side and a permeate side separated by a membrane boundary layer; and processing circuitry configured to control a water production rate of the MD process based at least in part upon a distributed heat transfer across the membrane boundary layer. In another example, a method includes determining a plurality of estimated temperature states of a membrane boundary layer separating a feed side and a permeate side of a membrane distillation (MD) process; and adjusting inlet flow rate or inlet temperature of at least one of the feed side or the permeate side to maintain a difference temperature along the membrane boundary layer about a defined reference temperature based at least in part upon the plurality of estimated temperature states.

A method for automated optimisation of a servo control system controlled by a setpoint, the servo control system including a corrector in a feedback loop, the method exhibiting satisfactory reliability and performance in terms of stability through an iterative procedure, the most effective corrector being determined from among correctors by developing a current value of the delay margin and by individually testing the correctors on the servo control system of the real mechatronic system and by injecting an excitation signal into the loop and by assessing two effective indicators based on at least one effective static margin and one effective dynamic margin, the two effective indicators being an effective static indicator and an effective dynamic indicator, the iterative procedure being stopped on a corrector, which is then the optimal corrector, when the two effective indicators become greater than respective thresholds determined for a current delay margin value.

A nonlinear disturbance rejection control apparatus and method for electronic throttle control systems are invented to control the electronic throttle system and to achieve a continuous finite-time disturbance rejection control goal. A control sub-apparatus and method are proposed with an observing sub-apparatus and method for controlling the opening angle of an electronic throttle valve. A mathematical model of the electronic throttle system is analyzed and a control-oriented model is presented with the formation of a lumped disturbance. With combination of the continuous terminal sliding mode control method and the output feedback control method, based on the finite-time high-order sliding mode observer, the preferred control performance is guaranteed, where both the dynamic and static performance of the system is effectively improved.