At present, the agricultural industry is using more induction machines than previously in place of the traditional diesel engine. We identify useful parameters in the design of the control system of the induction machine. The conventional methods used to identify the parameters of the induction machine are a no-load test, a DC test, a locked rotor test, and a retardation test. This paper presents a new objective function for the identification of the parameters of the induction machine using hybrid particle swarm based gravitational search algorithm techniques (PSO-GSA). The integral of squared error (ISE) is used as the objective function of the hybrid particle swarm based gravitational search algorithm techniques. The conventional objective function for identifying the parameters only considers the stator current and rotor speed. The new objective function in the identification of parameters also includes consideration of the electromagnetic torque. A comparison is made between the results obtained by the new objective function and the old objective function. The simulated results show that the new objective function is more effective for this task than the old objective function at short iterations. © 2020 Greater Mekong Subregion Academic and Research Network, Asian Institute of Technology.