[28] utilized an immeasurable premise variable for detecting the faults in T-S fuzzy systems. In order to tackle the uncertainties in a suitable manner, interval type-2 fuzzy sets were introduced. Moreover, a comparison between robust unknown input fault detection observers (UIFDO) and an existent reference is carried out to validate that the interval type-2 T-S fuzzy model is superior to type-1. In the work of [PERSON] et al. [29], it is demonstrated that the type-2 fuzzy PD/PID controller performed better than the classical fuzzy PD/PID controller in the control of vibration of the structure. An innovative concept involving type-1 and type-2 fuzzy logic systems are proposed for pitch angle controlled wind energy systems as an application for the performance investigation. The results show that the type-2 fuzzy logic system offers better performance in comparison to type-1 fuzzy logic systems [30]. A comparison between type-1 fuzzy and type-2 fuzzy logic controllers implemented in laser tracking systems was carried out by [PERSON] et al. [31]. The simulation results validated that the type-2 fuzzy controller outperformed the type-1 fuzzy controller. The exhaustive research reveals that type-2 fuzzy is superior to type-1 fuzzy. This fact initiate the research motivation of implementing type-2 fuzzy controllers for chatter attenuation. The numerical analysis validated that the results were improved by the incorporation of a type-2 fuzzy logic system. Sliding mode control (SMC) is a superior control mechanism for vibration attenuation in milling tools since SMC exhibits the same movement pattern as that of the tool vibration pattern. SMC is most suited for nonlinear systems due to its specific design criteria [32]. An SMC controller handles the external noises and fluctuations associated with the parameters with greater effectiveness. [PERSON] et al. [33] investigated the chatter phenomenon in the turning process and proposed SMC for chatter attenuation. A synergistic combination of proportional-integral (PI) control and fuzzy sliding mode control (FSMC) was proposed by [PERSON] et al. [34]. In their work, fuzzy logic is utilized to compensate the nonlinearities whereas the PI control is implemented for chatter control. [PERSON] et al. [35] developed an active sliding mode control strategy to mitigate the chatter in the turning process utilizing the concept of dynamic output feedback sliding surface combined with an adaptive law for noise approximation. A model based on an adaptive neuro-fuzzy inference system (ANFIS) and a novel fuzzy sliding mode controller (FSMC) was developed to control the vibration on vehicle the suspension system [36]. An efficient controller based on adaptive hybrid control of interval type-2 fuzzy controller in combination with a new modified sliding mode control is developed to control the vibration in magnetorheological mount [37]. Discrete time sliding mode control (DSMC) is an efficient controller for vibration attenuation due to its criteria of sampling period which is an important aspect in vibration control. Proportional-integral derivative (PID) control has been widely applied in industrial processes [38; 39]. It is an important control strategy because it demonstrates superior capabilities without the knowledge of the model and also due to its simplicity, as well as being incorporated with distinct physical meanings. [PERSON] et al. [15] implemented the concept of PID controller for chatter mitigation in the milling process. So in this paper, the PID controller is considered as a potential controller for the comparison with the developed controller. This work is carried out by implementing the third option \"active control of chatter\". In the first instance along \(x\) and \(y\) components, the mathematical modeling of the milling process is done. Then the nonlinearities are identified for efficient compensation. The actual outcomes of active vibration samper (AVD) was simulated using Matlab/Simulink for chatter suppression.