A computer program product comprising a non-transitory computer readable medium having a computer readable program embodied therein, wherein the computer readable program, when executed on a computing device, causes the computing device to:
- implement an available solution during online trajectory optimization by communicating to relevant actuators present in a dynamical system, wherein the dynamical system includes an industrial system including a chemical, food or mineral processing plant, an oil refinery, a power plant, a hybrid electric vehicle, a continuous glucose monitoring sensor and an insulin pump;
- monitoring performance of the dynamical system, wherein in response to the performance of the dynamical system is off-track, actuation profiles that are the most appropriate of a set of manipulated variables are updated for a remaining time of the process;
- preprocess and integrate input data, wherein the input data comprises a plurality of data received from one or more sources;
- classify the preprocessed and integrated input data among one of a set of disturbance variables, a set of process variables, the set of manipulated variables, a set of material properties, and a set of design parameters, wherein the classification is stored in a variable information library;
- forecast an expected profile of each of the set of disturbance variables using respective models;
- fetch the most appropriate actuation profiles of the set of manipulated variables corresponding to a trajectory optimization model from a knowledgebase, based on a predefined condition for an applicable set of design parameters, the set of material properties, and expected profiles of the set of disturbance variables;
- implement the most appropriate actuation profiles of the set of manipulated variables by informing a set of actuators, wherein the set of actuators are part of the process;
- predict an expected profile for each of the set of process variables using their respective models;
- monitor the set of disturbance variables, the set of process variables, objectives, and constraints of the process in real time to observe one or more changes;
- adjust constituents of a trajectory optimization model in response to the one or more changes observed during the monitoring;
- estimate the most appropriate actuation profiles of the set of manipulated variables using the adjusted constituents, wherein the estimated most appropriate actuation profiles of the set of manipulated variables enables correcting a course of the process by transmitting the estimated most appropriate actuation profiles to the set of actuators;
- and
- implement the estimated most appropriate actuation profiles of the set of manipulated variables by the transmission of the estimated most appropriate actuation profiles to the set of actuators,
- wherein the real time trajectory optimization of the dynamical system includes operating the hybrid electrical vehicle to minimize fuel consumption, wherein the input data comprises i) design parameters comprising battery type, battery capacity, and drive-train of the hybrid electrical vehicle, and ii) operational data comprising road grade, speed, acceleration, gear number, engine torque, motor torque, State of Charge of battery (SOC), State of Health (SOH), wherein the set of process variables comprise the SOC, the engine torque, the motor torque and the fuel consumption, wherein the set of manipulated variables comprise a torque ratio, and wherein the set of disturbance variables comprise of a driver's velocity and traffic profile, wherein the actuation profiles of manipulated variables, optimized trajectory of process variables, constraints, objectives, and disturbance variable profile during movement along a route are determined using the trajectory optimization model, wherein during online implementation an expected velocity profile is predicted for the route and a profile of the torque ratio is fetched from the knowledgebase that minimizes the fuel consumption for a present and projected driving condition, wherein the set of process variables and the set of disturbance variables are monitored using vehicle sensors to detect drift from expected values and upon detection of the drift, a source of the drift is identified comprising at least one of inaccuracy of prediction model of process variable or disturbance variable, infeasibility to satisfy constraints, and wherein estimating, using the adjusted trajectory optimization model, a new actuation profile of the torque ratio for a remaining portion of the route and implementing the estimated actuation profile to meet the objective of minimization of the fuel consumption.