Communication-induced dynamic control strategies under packet collisions and SNR variations

Dynamic control behavior in networked control systems is closely associated with the information available to the controller. In practical environments, the availability of such information is uncertain and may cause the implemented control protocol to evolve. This paper investigates dynamic control behavior induced by communication uncertainty from a control perspective. A key coefficient in a general distributed controller is modeled as a random variable to capture information availability among agents. Its probability distribution is derived by jointly considering packet collisions and transmission errors, both of which depend on the signal-to-noise ratio. The resulting information availability determines whether inter-agent coupling terms participate in each control decision, thereby linking packet-level communication conditions to the implemented control strategy. Through this formulation, communication uncertainty is embedded into the control coefficient, resulting in a time-varying control system with different strategies. A Lyapunov-based analysis establishes uniform exponential stability of the time-varying control system, with the sufficient condition verified using the controller gains. A formation control case study involving three unmanned surface vehicles is then conducted to evaluate how the communication-induced strategy variations affect control performance and strategy evolution. The results show that increasing signal-to-noise ratio from 10 to 20 dB reduces the bit error rate from approximately 1 0 − 1 to 1 0 − 5 and markedly improves formation performance. At collision probability is equal to 0.15, , the control strategy changes at approximately 17–20 dB, and severe collisions limit the benefits of high signal-to-noise ratio. Overall, communication uncertainty can reshape both formation performance and the evolution of control strategies, demonstrating a coherent propagation from packet-level communication conditions to information availability, dynamic control behavior, and control performance.