For instance, in [21], data-driven Type-2 Takagi-Sugeno (T-S) fuzzy modeling and control for bilateral teleoperation with dynamic uncertainties and time-varying delays is developed. The Type-2 T-S fuzzy model describes the nonlinear teleoperation system by a weighted sum of a group of linear local models. Fuzzy model-based four-channel control laws are proposed to guarantee motion synchronization and to enhance the operator's force perception of the environment when time-varying delays and large dynamic uncertainties exist. In [22], a predictive control method for a bimanual teleoperation system without force/torque and acceleration sensors is proposed. By accurately estimating the local force, position predictors/observers are used to estimate the internal dynamics of the master and slave simultaneously, thereby avoiding the use of delayed transmitted information. An adaptive fuzzy control strategy based on linear matrix inequalities (LMIs) is proposed to evaluate and suppress system uncertainties. In [23], a combination of a force observer using Type-2 Fuzzy Neural Network (T2 FNN) and Moving Horizon Estimation (MHE) is proposed to estimate the external force/torque and simultaneously filter out disturbances in bilateral teleoperation systems. Applying the estimated forces, an external force-regulated Sliding Mode Control (SMC) strategy with the support of machine vision is proposed to enhance the adaptability of the slave robot and improve the perception of the operator about various scenarios by virtue of the detected location of the task object. In [24], a method based on a robust adaptive fuzzy control approach is developed for nonlinear teleoperation systems with time-varying delays. It has been proven that both position tracking and force feedback problems are solved. SMC techniques have also been applied in many works. For example, in [25; 26], sliding mode-based finite-time synchronization algorithms for bilateral teleoperation systems under unsymmetrical time-varying delays and uncertainties are presented. In [27], a position/force hybrid control strategy is proposed for a class of uncertain bilateral telerobotic systems under time-varying communication delays without using force sensors. The proposed Terminal Sliding Mode (TSM)-based force observer can estimate the human force and the environment force in a fixed time by applying a variable exponent coefficient, which effectively avoids the temporal problems of other existing force observers. In contrast with all previous works, most basic control techniques are scarcely used in the control of bilateral systems with time-varying delays. This fact is easy to understand in view of the complexity of the problem. Despite these advancements, the application of standard Proportional-Integral-Derivative (PID) controllers in bilateral teleoperation systems with time-varying delays remains underexplored. This study aims to fill this gap by providing a technical stability proof demonstrating that Standard Proportional-Integral-Derivative (PID) control can effectively regulate position in such systems, even in the presence of time-varying delays. Let us recall that for a single manipulator, it is very well-known that a simple Proportional-Derivative (PD) control law is enough to achieve exact regulation if gravity terms are cancelled out. In cases where the gravity term is unknown, exact regulation can be carried out by implementing a Standard Proportional-Integral-Derivative (PID) controller [28; 29; 30]. For the case of PD controllers, the extension for bilateral systems finds a first result in [5], where a PD control law plus gravity compensation is employed to show consensus for bilateral systems with constant and symmetric time delays. An extension for time-varying delays can also be found in [31], but still, gravity compensation is necessary. The obvious solution to avoid gravity compensation is to employ PID controllers; yet, no technical proof has been established in the literature to support its use on bilateral systems with time-varying delays.