Universal approximation using radial-basis-function networks
Neural Computation
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy logic control of dynamic balance and motion for wheeled inverted pendulums
Fuzzy Sets and Systems
Fuzzy adaptive observer backstepping control for MIMO nonlinear systems
Fuzzy Sets and Systems
A combined backstepping and small-gain approach to robust adaptive fuzzy output feedback control
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Neural Networks
IEEE Transactions on Fuzzy Systems
New passivity analysis for neural networks with discrete and distributed delays
IEEE Transactions on Neural Networks
Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints
Automatica (Journal of IFAC)
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Almost disturbance decoupling of MIMO nonlinear systems and application to chemical processes
Automatica (Journal of IFAC)
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Adaptive Output-Feedback Fuzzy Tracking Control for a Class of Nonlinear Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Data-driven monitoring for stochastic systems and its application on batch process
International Journal of Systems Science - Probability-constrained analysis, filtering and control
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An adaptive control scheme is studied for a class of continuous stirred tank reactors (CSTR) with unknown functions. Because the nonlinear property and the unknown functions are included in the considered reactor, it leads to a completed task for designing the controller. Based on the approximation property of the neural networks, several unknown functions are approximated. The main contribution of this paper is that a more general class of CSTR is controlled. A novel recursive design method is used to remove the interconnection term. It is proven that the proposed algorithm can guarantee that all the signals in the closed-loop system are bounded and the system output can converge to a neighborhood of zero based on the Lyapunov analysis method. A simulation example for continuous stirred tank reactor is illustrated to verify the validity of the algorithm.