In this article, the problems of attack detection and secure tracking control for the power cyber-physical system are investigated. Considering the critical role of cyber networks in influencing decision-making for power grid optimization, a multiobjective optimization problem is introduced to determine the output power of generators. This optimization problem is solved based on the improved particle swarm optimization algorithm. The power system is modelled with dynamic characteristics taken into account. Furthermore, a resilient state-feedback tracking control strategy, that exploits a sliding mode observer, is introduced to ensure the reference value generated by the cyber network is tracked even under attacks. In addition, by using the reconstructed attack signals, an attack detection scheme is proposed. Some sufficient conditions are then obtained for the solvability of the tracking control problem. Finally, a simulation example and the experimental validation built into the StarSim hardware-in-the-loop simulation platform are introduced to illustrate the effectiveness of the proposed method.