The paper presents the application of a modified adaptive Particle Swarm algorithm (PSO) to the design of finite impulse response (FIR) filters. Initially, the capabilities of the conventional version of the PSO algorithm were investigated, but it did not lead to optimal solutions in a wider range of the parameters of the FIR filters. For this reason, in the next stage, an adaptive PSO algorithm was introduced with the ability to modify key parameters during the optimization process. In the approaches that can be found in the state-of-the-art literature on adaptive PSO algorithms, for example, the value of the inertia coefficient was variable during the optimization process. In our solution, the possibility of changing the social and cognitive coefficients was additionally introduced. Thanks to this, it was possible to obtain correct solutions for longer impulse responses of the FIR filters. Verification of the proposed solution was carried out for different FIR-PSO configurations, for different FIR filter lengths, different cut-off frequencies, different numbers of particles in the swarm, etc.