Establishment of optimal control for systems, where constraints involve both control and state, is very difficult. In some problems the difficulty is reduced significantly by transforming the optimal control problem. For illustration, the optimal control of a nonisothermal fed-batch reactor with heat removal constraint is considered Although there are only two control variables, the feed rate and the temperature, the heat removal rate constraint makes the optimal control problem very difficult. To parametrize the optimal control problem, the time interval is divided into P time stages of variable length, and piecewise constant control is used at each time stage. Establishment of the optimal control policy is very challenging owing to the low sensitivity, the heat removal constraint, and the need for a large number of time stages for adequate approximation. However, by reformulating the optimal control problem where heat generation, rather than temperature, is used as a control variable, we are able to get greater accuracy with a smaller number of time stages. The optimal control policy is established with iterative dynamic programming and checked with LJ-optimization procedure