A configurable controller for controlling a physical plant having associated therewith a plurality of actuators for controlling operation of the physical plant and a plurality of sensors (116, 266) for observing a plurality of characteristics of the physical plant operations, the configurable controller comprising: a state observer configured to capture a current state of the physical plant by communication with the plurality of sensors; and an optimizer configured to optimize behavior of the physical plant using at least the actuators; wherein the optimizer is operable using a model predictive control cost function including a first term representing a traditional model predictive control cost function based on the current state of the physical plant, multiplied by a first weighting factor, and wherein the model predictive control cost function further comprises at least one second term representing a health indicator, the at least one second term being one of: a) a second term indicating degradation of one or more components of the physical plant that results from steps that occur in time horizon of the optimization calculation, multiplied by a second weighting factor, wherein the first term and second term are summed by the optimizer; or b) a second term which decreases as health of one or more components of the physical plant degrades, multiplied by a second weighting factor, wherein the second term is subtracted from the first term by the optimizer; or c) a second term representing a slack variable calculated as difference between health impacts within the time horizon and a maximum allowed health degradation factor, multiplied by a second weighting factor, wherein the first and second terms are summed by the optimizer; and wherein the optimizer operates to direct use of parameters in the actuators to minimize the sum of the first and second terms in the event the second term is either (a) or (c) or the difference of the first and second terms in the event the second term is (b). a state observer configured to capture a current state of the physical plant by communication with the plurality of sensors; and an optimizer configured to optimize behavior of the physical plant using at least the actuators; wherein the optimizer is operable using a model predictive control cost function including a first term representing a traditional model predictive control cost function based on the current state of the physical plant, multiplied by a first weighting factor, and wherein the model predictive control cost function further comprises at least one second term representing a health indicator, the at least one second term being one of: a) a second term indicating degradation of one or more components of the physical plant that results from steps that occur in time horizon of the optimization calculation, multiplied by a second weighting factor, wherein the first term and second term are summed by the optimizer; or b) a second term which decreases as health of one or more components of the physical plant degrades, multiplied by a second weighting factor, wherein the second term is subtracted from the first term by the optimizer; or c) a second term representing a slack variable calculated as difference between health impacts within the time horizon and a maximum allowed health degradation factor, multiplied by a second weighting factor, wherein the first and second terms are summed by the optimizer; and a) a second term indicating degradation of one or more components of the physical plant that results from steps that occur in time horizon of the optimization calculation, multiplied by a second weighting factor, wherein the first term and second term are summed by the optimizer; or b) a second term which decreases as health of one or more components of the physical plant degrades, multiplied by a second weighting factor, wherein the second term is subtracted from the first term by the optimizer; or c) a second term representing a slack variable calculated as difference between health impacts within the time horizon and a maximum allowed health degradation factor, multiplied by a second weighting factor, wherein the first and second terms are summed by the optimizer; and wherein the optimizer operates to direct use of parameters in the actuators to minimize the sum of the first and second terms in the event the second term is either (a) or (c) or the difference of the first and second terms in the event the second term is (b).