The Automatic Voltage Regulation system is a fundamental component in electrical power systems, responsible for maintaining stable generator terminal voltage under varying load and operating conditions. Effective voltage regulation is essential for ensuring system stability, improving power quality, and enhancing the operational reliability of synchronous generators. This review paper presents a comprehensive analysis of recent advancements in Automatic Voltage Regulator (AVR) control strategies, with emphasis on classical, optimization-based, and intelligent control techniques. Conventional control approaches, including proportional-integral (PI) and proportional-integral-derivative (PID) controllers, are examined in terms of their performance limitations under nonlinear and dynamic operating environments. Furthermore, advanced optimization methods such as Particle Swarm Optimization, Genetic Algorithm, and intelligent techniques including Fuzzy Logic Control and Artificial Neural Network are critically reviewed for their capability to enhance dynamic response, reduce overshoot, and improve disturbance rejection. Comparative analysis indicates that hybrid and adaptive control methods offer superior performance compared to traditional controllers. The paper also discusses recent developments in digital AVR implementation and identifies current research gaps related to computational complexity and practical deployment. Finally, future research directions focusing on artificial intelligence-based adaptive voltage regulation for smart grid and renewable-integrated power systems are highlighted. The findings demonstrate that intelligent AVR strategies are essential for achieving reliable, efficient, and sustainable voltage regulation in modern power networks.