Dynamic optimization of double-sided cooking of meat patties

Abstract

Optimal operating procedures for double-sided cooking of frozen hamburger patties were computed using dynamic optimization techniques. The mathematical statement was to find the optimal control (e.g., heating surface temperature) over cooking time to minimize (or maximize) the performance index J, for example minimize cooking loss, and to ensure the required lethality and safe cooking temperature. The control vector parameterization framework was applied, and stochastic algorithm was used to locate the global optimum with reasonable computation effort (Integrated Controlled Random Search for Dynamic Systems). The performance index improved when the heating temperature profile was considered as control variable and when two control elements of variable size were used (compared with the constant-temperature process or nominal case, ΔJ<3%). When the lower bound was relaxed and two control elements were used, the performance index improved significantly (ΔJ<7%). However, when the top and bottom plate temperatures were considered as two different controls, the plate temperature profiles obtained did not significantly improve the results compared with the nominal cases. When the temperature of the top and bottom plates and gap thickness were considered as control variables, and when two control elements of variable size for gap thickness were used, the performance index improved for long periods of cooking time (ΔJ<2.5%).