This paper addresses the problem of joint detection and estimation of cyberattacks and physical faults in smart-grid cyber-physical systems. In practical smart-grid environments

physical faults arising from equipment degradation may coexist with malicious cyber threats

leading to significant degradation in system reliability and operational security. To tackle these issues

a model-based resilient estimation and control framework is proposed

which integrates observer-based attack detection and fault estimation mechanisms. First

a set of distributed local estimators based on unknown input observers (UIOs) is developed to achieve robust state and fault estimation under disturbances and sparse sensor attacks. Subsequently

a resilient global fusion strategy is established to enhance tolerance against compromised measurements and to ensure bounded estimation errors even in the presence of sensor corruption. Based on the fused estimation results

a resilient fault-tolerant control scheme is formulated to guarantee closed-loop stability and desired performance. The proposed framework is applicable to both centralised and distributed smart-grid configurations. Simulation results on a nonlinear benchmark system demonstrate its effectiveness in detecting cyberattacks

estimating physical faults

and maintaining reliable system operation under adverse conditions.