This paper investigates the potential of fluid antenna systems (FAS) to shift the trade-off between integrated sensing and communication (ISAC) performance. As an emerging antenna technology, FAS enhances spatial diversity by allowing active antennas to shift among available ports, thereby improving both sensing and communication performance. The authors propose a model for FAS-enabled ISAC and jointly optimize transmit beamforming and port selection to minimize transmit power while satisfying communication and sensing requirements. An efficient iterative algorithm based on sparse optimization, convex approximation, and penalty methods is developed. Simulation results show that the proposed scheme can achieve a 33% reduction in transmit power while maintaining sensing and communication performance, demonstrating the potential of FAS to provide a flexible trade-off between sensing and communication in ISAC systems. The system model considers a multicast ISAC base station (BS) with an N-antenna FAS, where M ports are uniformly distributed along a linear space. The BS transmits a common signal to users and uses echo signals for target sensing. Each user has a fixed-position antenna, while the BS uses the FAS to enhance ISAC performance by shifting active ports. The communication performance is evaluated based on signal-to-noise ratio (SNR) requirements, and the sensing performance is based on the SNR of the received echo signal. The authors propose a joint port selection and dual-functional beamforming optimization approach to minimize transmit power under constraints of minimum SNR requirements and available ports. The problem is formulated as a non-convex optimization problem, which is solved using an iterative algorithm based on sparse optimization and convex approximation. The algorithm involves a penalty method to transform the non-convex problem into a sequence of convex optimization problems, followed by successive convex approximation to solve them iteratively. Simulation results show that the proposed method significantly reduces transmit power compared to conventional antenna systems, demonstrating the potential of FAS in improving the flexibility of balancing sensing and communication performance in ISAC systems. The results also show that increasing the number of activated ports leads to a significant reduction in transmit power, indicating the potential of FAS in power saving. The trade-off between sensing and communication performance is further analyzed, showing that FAS can achieve a better balance between the two functions, leading to a lower transmit power under the same constraints. The results confirm the effectiveness of FAS in enhancing ISAC performance and demonstrate its potential in future wireless communication systems.This paper investigates the potential of fluid antenna systems (FAS) to shift the trade-off between integrated sensing and communication (ISAC) performance. As an emerging antenna technology, FAS enhances spatial diversity by allowing active antennas to shift among available ports, thereby improving both sensing and communication performance. The authors propose a model for FAS-enabled ISAC and jointly optimize transmit beamforming and port selection to minimize transmit power while satisfying communication and sensing requirements. An efficient iterative algorithm based on sparse optimization, convex approximation, and penalty methods is developed. Simulation results show that the proposed scheme can achieve a 33% reduction in transmit power while maintaining sensing and communication performance, demonstrating the potential of FAS to provide a flexible trade-off between sensing and communication in ISAC systems. The system model considers a multicast ISAC base station (BS) with an N-antenna FAS, where M ports are uniformly distributed along a linear space. The BS transmits a common signal to users and uses echo signals for target sensing. Each user has a fixed-position antenna, while the BS uses the FAS to enhance ISAC performance by shifting active ports. The communication performance is evaluated based on signal-to-noise ratio (SNR) requirements, and the sensing performance is based on the SNR of the received echo signal. The authors propose a joint port selection and dual-functional beamforming optimization approach to minimize transmit power under constraints of minimum SNR requirements and available ports. The problem is formulated as a non-convex optimization problem, which is solved using an iterative algorithm based on sparse optimization and convex approximation. The algorithm involves a penalty method to transform the non-convex problem into a sequence of convex optimization problems, followed by successive convex approximation to solve them iteratively. Simulation results show that the proposed method significantly reduces transmit power compared to conventional antenna systems, demonstrating the potential of FAS in improving the flexibility of balancing sensing and communication performance in ISAC systems. The results also show that increasing the number of activated ports leads to a significant reduction in transmit power, indicating the potential of FAS in power saving. The trade-off between sensing and communication performance is further analyzed, showing that FAS can achieve a better balance between the two functions, leading to a lower transmit power under the same constraints. The results confirm the effectiveness of FAS in enhancing ISAC performance and demonstrate its potential in future wireless communication systems.