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The article compares the dynamic performances of the pump-controlled, valve-controlled and prime-mover controlled hydromotor drive systems for a wide range of operating conditions. The control strategy adopted for each of them varies the supply flow to the hydromotor that gives the regulated drive speed. In this respect, the Simscape models are developed for the said systems that are validated experimentally. On the basis of response time, overshoot, and steady-state error obtained from the simulation and test results, it is found that the valve controlled hydromotor drive system is more sensitive than the others; whereas, the load-sensing pump control requires more time to settle but has less overshoot. • Three different control experiments are carried out to achieve a constant speed of a hydromotor under varying load. • The system parameters are estimated and validated by using optimization techniques. • It is established that the valve controlled hydromotor drive is more sensitive than others. • The load-sensing hydromotor drive is found to have a more sluggish response compared to the others. [ABSTRACT FROM AUTHOR]

A model of two area deregulated power system with automatic generation control (AGC) is developed. Two conventional control strategies, integral controller optimized by Genetic Algorithm (GA) and Proportional derivative integral (PID) controller tuned with Ziegler-Nichols (ZN), have been compared with proposed two step GA optimized fuzzy logic controller (FLC). In proposed controller, first step optimization is carried out for range optimization with uniform scaling of membership functions of input and output variables and in second step, scaling and gain parameters of FLC are optimized. The proposed control scheme shows the better dynamic response following a step load change with combination of PoolCo and bilateral contracts in deregulated environment. [ABSTRACT FROM AUTHOR]

An attempt is made for the effective application of Gravitational Search Algorithm (GSA) to optimize PI/PIDF controller parameters in Automatic Generation Control (AGC) of interconnected power systems. Initially, comparison of several conventional objective functions reveals that ITAE yields better system performance. Then, the parameters of GSA technique are properly tuned and the GSA control parameters are proposed. The superiority of the proposed approach is demonstrated by comparing the results of some recently published techniques such as Differential Evolution (DE), Bacteria Foraging Optimization Algorithm (BFOA) and Genetic Algorithm (GA). Additionally, sensitivity analysis is carried out that demonstrates the robustness of the optimized controller parameters to wide variations in operating loading condition and time constants of speed governor, turbine, tie-line power. Finally, the proposed approach is extended to a more realistic power system model by considering the physical constraints such as reheat turbine, Generation Rate Constraint (GRC) and Governor Dead Band nonlinearity. [ABSTRACT FROM AUTHOR]