A computer-implemented method comprising: detecting, during a first period of time, an output of a system; determining, based on the output detected during the first period of time, a first performance metric for the system; operating a first hybrid controller, based on the first performance metric, to generate a first hybrid controller output, wherein the first hybrid controller comprises a first constraint, a first dynamic system, and a first learned system model, wherein operating the first hybrid controller to generate the first hybrid controller output comprises: determining a first difference between the first performance metric and the first constraint; applying the determined first difference to the first dynamic system to generate a first dynamic system output; and applying the generated first dynamic system output to the first learned system model to generate the first hybrid controller output; controlling the system, during a second period of time, according to the generated first hybrid controller output; detecting, during a third period of time, the output of the system; determining, based on the output detected during the third period of time, a second performance metric for the system; operating a second hybrid controller, based on the first performance metric and the second performance metric, to generate an updated constraint value; updating the first constraint according to the updated constraint value; subsequent to updating the first constraint, operating the first hybrid controller, based on the second performance metric, to generate a second output of the first hybrid controller; and controlling the system, during a fourth period of time, according to the generated second output of the first hybrid controller; wherein the second hybrid controller comprises a second constraint, a second dynamic system, and a second learned system model, wherein operating the second hybrid controller, based on the first performance metric and the second performance metric, to generate an updated constraint value comprises: applying the first performance metric and the second performance metric to the second dynamic system to generate a second dynamic system output; and applying the generated second dynamic system output to the second learned system model to generate the updated constraint value. detecting, during a first period of time, an output of a system; determining, based on the output detected during the first period of time, a first performance metric for the system; operating a first hybrid controller, based on the first performance metric, to generate a first hybrid controller output, wherein the first hybrid controller comprises a first constraint, a first dynamic system, and a first learned system model, wherein operating the first hybrid controller to generate the first hybrid controller output comprises: determining a first difference between the first performance metric and the first constraint; applying the determined first difference to the first dynamic system to generate a first dynamic system output; and applying the generated first dynamic system output to the first learned system model to generate the first hybrid controller output; determining a first difference between the first performance metric and the first constraint; applying the determined first difference to the first dynamic system to generate a first dynamic system output; and applying the generated first dynamic system output to the first learned system model to generate the first hybrid controller output; controlling the system, during a second period of time, according to the generated first hybrid controller output; detecting, during a third period of time, the output of the system; determining, based on the output detected during the third period of time, a second performance metric for the system; operating a second hybrid controller, based on the first performance metric and the second performance metric, to generate an updated constraint value; updating the first constraint according to the updated constraint value; subsequent to updating the first constraint, operating the first hybrid controller, based on the second performance metric, to generate a second output of the first hybrid controller; and controlling the system, during a fourth period of time, according to the generated second output of the first hybrid controller; wherein the second hybrid controller comprises a second constraint, a second dynamic system, and a second learned system model, wherein operating the second hybrid controller, based on the first performance metric and the second performance metric, to generate an updated constraint value comprises: applying the first performance metric and the second performance metric to the second dynamic system to generate a second dynamic system output; and applying the generated second dynamic system output to the second learned system model to generate the updated constraint value. applying the first performance metric and the second performance metric to the second dynamic system to generate a second dynamic system output; and applying the generated second dynamic system output to the second learned system model to generate the updated constraint value.