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This paper presents an improved secondary voltage control (SVC) methodology incorporating compressive sensing (CS) for a multi-area power system. SVC minimizes the voltage deviation of the load buses while CS deals with the problem of the limited bandwidth capacity of the communication channel by reducing the size of massive data output from phasor measurement unit (PMU) based monitoring system. The proposed strategy further incorporates the application of a Morphological Median Filter (MMF) to reduce noise from the output of the PMUs. To keep the control area secure and protected locally, Mathematical Singular Entropy (MSE) based fault identification approach is utilized for fast discovery of faults in the control area. Simulation results with 27-bus and 486-bus power systems show that CS can reduce the data size up to 1/10 th while the MSE based fault identification technique can accurately distinguish between fault and steady state conditions. N communication channel, and communication channel cost.CS is regarded as a promising joint data acquisition and reconstruction method to deal with the problem of limited bandwidth and data congestion. The data retrieved from the PMUs can be compressed before sending through the communication channel and can be recovered at the end of communication channel. Plenty of research has been performed to recover the signal at the end of communication channel [13], [14]. A CS based control strategy is developed for load frequency control in a multi-area power system network [15]. This strategy helps reduce the transmission data loss and increase the reliability of the communication network.Performance of CS may be affected by the noise in the signal, which may induce error in the signal processing and degrade the system's dynamic performance [16]. In order to deal with such problems, several noise filtering techniques have been developed in the recent literature [17], [18]. Based on the theory of Mathematical Morphology (MM), a mathematical morphological filter (MMF) is proposed in [21],