KEYWORDS: Control systems, Data modeling, Telecommunications, Systems modeling, Quantization, Matrices, Data transmission, Data communications, Algorithms, Adaptive control
For the nonlinear discrete-time Multi-agent system of unknown dynamic models, there are cooperation and competition between agents, and the problem of data quantification in communication, a model-free adaptive iterative control (MFAILC) algorithm is proposed. First, the method of compact form dynamic linearization (CFDL) is used to transform the agent system into a model with time-varying parameters, and the quantizer is applied to quantize the data in the process of processing, and the cooperation-competition relationship between multi-agents is considered in algebraic graph theory, on this basis, the MFAILC control algorithm is designed and the convergence of the proposed algorithm is proved. Finally, the simulation results verify the effectiveness of the proposed algorithm.
Traditional fractional-order controller (FOPID) parameter tuning methods are mainly based on amplitude margin and phase angle margin in the frequency domain, and there are problems such as low parameter tuning efficiency and low accuracy. This paper proposes a parameter optimization method based on the multi-objective particle swarm optimization algorithm MOPSO. By rotating the Hankel matrix to approximate the fractional-order operator, the system fractional-order differential equation satisfied by the fractional-order controller parameters is transformed into an algebraic differential equation Using MOPSO to optimize controller parameters. Experimental results show that the design method improves the dynamic performance of the system and makes the system have good robustness.
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