This paper deals with the simultaneous application of thyristor controlled series capacitor based damping controller and power system stabilizer for stability improvement of dynamic power system. The adaptive neuro-fuzzy inference system and Levenberg–Marquardt artificial neural network algorithm are used to develop the control strategy for thyristor controlled series capacitor based damping controller and power system stabilizer. The power system stabilizer generates appropriate supplementary control signal to an excitation system of synchronous generator to damp the frequency oscillations and improves the performance of the power system dynamic. The performance of power system affected due to the system configuration and load variation. In order to achieve the appreciable damping, the series capacitor is suggested in addition to the power system stabilizer. Nonlinear simulations of single machine infinite bus system are carried out using the individual application of power system stabilizer and simultaneous application of power system stabilizer and thyristor controlled series capacitor. The comparison analysis between conventional and smart control strategies based controllers is demonstrated. Single machine infinite bus system is tested under various operating conditions and disturbances to show the effectiveness of proposed control schemes. rotor angle in radian rotor base speed, rad/s generator slip, p.u. initial operating slip, p.u. inertia constant damping coefficient mechanical power input, p.u. electrical power output, p.u. open circuit d-axis time constant, s open circuit q-axis time constant, s q-axis transient voltage d-axis transient voltage d-axis synchronous reactance, p.u. d-axis transient reactance, p.u. q-axis synchronous reactance, p.u. q-axis transient reactance, p.u. d-axis current q-axis current generator terminal voltage infinite bus voltage 
Smart control techniques for design of TCSC and PSS for stability enhancement of dynamical power system