Camless reciprocating engine control system

A non-transitory machine-readable storage medium storing instructions executable by one or more processors of a computing device, wherein the instructions, when executed by the one or more processors, cause the computing device to:

• obtain training data comprising a plurality of training data input vectors and a plurality of reference data output vectors, wherein a training data input vector of the plurality of training data input vectors represents sensor data regarding an attribute of operation of a camless engine, and wherein a reference data output vector of the plurality of reference data output vectors represents actuator command data to be generated by a machine learning model from the training data input vector;
• cluster the training data into a plurality of clusters based on time proximity of cycles with which the plurality of training data input vectors are associated, wherein training data input vectors in a first cluster of the plurality of clusters are associated with a first set of cycles observed during a first period of time, and wherein training data input vectors in a second cluster of the plurality of clusters are associated with a second set of cycles observed during a second period of time subsequent to the first period of time;
• train the machine learning model using the training data and an objective function, wherein the objective function is associated with optimization of an engine function;
• and
• provide the machine learning model that has been trained to one or more camless engines.

A computer-implemented method comprising:

• as performed by a control system for a camless engine, the control system comprising one or more computer processors configured to execute specific instructions,
• receiving sensor data from an optical sensor in optical communication with an engine component associated with a cylinder of the camless engine, wherein the engine component is selected from a group consisting of:
• an intake valve, an exhaust valve, a spark plug, a fuel injector, and a variable compression mechanism;
• processing the sensor data using a neural network trained to generate actuator command data associated with a desired optimization of engine operation;
• initiating actuation of an actuator of the camless engine based at least partly on the actuator command data;
• receiving second sensor data from the optical sensor, wherein the second sensor data is generated by the optical sensor subsequent to the initiating actuation of the actuator based at least partly on the actuator command data;
• determining a reward value based on the second sensor data;
• and
• modifying a parameter of the neural network based on the reward value.