A cyber-physical control system (CPS) typically consists of a set of physical subsystems, their remote terminal units, a central control center (if applicable), and local communication networks that interconnect all the components to achieve a common goal. Applications include energy systems, autonomous vehicles, and collaborative robots. Ensuring stability, performance, and resilience in CPS requires thorough analysis and control design, utilizing robust algorithms to handle delays, communication failures, and potential cyber-attacks. Time delays are a challenge in CPS, particularly in teleoperation systems, where human operators remotely control robotic systems. These delays cause chattering, oscillations, and instability, making it difficult to achieve smooth and stable remote robot control. Applications like remote surgery, space exploration, and hazardous environment operations are highly susceptible to these disruptions. To address this issue, a novel passivity-shortage framework is proposed, that enables systems to maintain stability and transparency despite time-varying communication delays and environmental disturbances. CPS are prone to attacks, particularly Denial-of-Service (DoS) attacks, which disrupt the normal functioning of a network by overwhelming it with excessive internet traffic, rendering the communication channels unavailable to legitimate users. These attacks threaten the stability and functionality of CPS. To enhance resilience in multi-agent systems, novel distributed algorithms are proposed. These graph theory-based algorithms mitigate network vulnerabilities by incorporating strategically placed additional communication channels, thereby increasing tolerance to attacks in large, dynamic networks. The effectiveness of these proposed approaches is validated through simulations, experiments, and numerical examples. The passivity-shortage teleoperation strategies are tested using Phantom Omni devices and they show reduced chattering and better steady-state error convergence. A case study demonstrates how the proposed distributed algorithms effectively achieve consensus, even when some agents are disconnected from the network due to DoS attacks.