Optimization of hysteretic chaotic neural network based on fuzzy sliding mode control

• A hysteretic chaotic neural network with the uncertain term is constructed.
• A novel control strategy based on fuzzy sliding mode is proposed.
• Fuzzy inference term can reduce the chattering on the sliding mode.
• Function optimization problem is resolved by the hysteretic chaotic neural network.

A hysteretic chaotic neural network with the uncertain term is constructed, and a novel control strategy based on fuzzy sliding mode is proposed to control its dynamic behaviors without changing its structure. The control law contains fuzzy inference term which can reduce the chattering on the sliding mode. The system stability is proved by the Lyapunov theory. The hysteretic chaotic neural network based on the fuzzy sliding mode control can be used to resolve the function optimization problem without destroying chaos generation mechanism and changing the structures of the neural network, which is different to the common annealing optimization strategy. Simulation results prove that the control strategy is a valid method to control the dynamic behaviors of the neural network and resolve the function optimization problem.