A robust model matching control of immune response is proposed for therapeutic enhancement to match a prescribed immune response under uncertain initial states and environmental disturbances, including continuous intrusion of exogenous pathogens. The worst-case effect of all possible environmental disturbances and uncertain initial states on the matching for a desired immune response is minimiz...

This paper considers the adaptive fuzzy robust control problem for a class of single-input and single-output (SISO) stochastic nonlinear systems in strict-feedback form. The systems under study possess unstructured uncertainties, unknown dead-zone, uncertain dynamics and unknown gain functions. In the controller design, fuzzy logic systems are adopted to approximate the unknown functions, and t...

The present paper presents the rst steps towards a theory to build Robust Nonlinear Predictive Control based on Fuzzy Models. The main idea behind this theory is to write the Predictive Control Problem as a Robust Optimization problem and apply Semideenite Programming to solve in a eecient way the optimization. The information about the plant behavior and its uncertainties will be provided by t...

Neural network has good nonlinear function approximation ability. It can be widely used to identify the model of controlled plant. In this chapter, the theories of modeling uncertain plant by using two kinds of neural networks: feed-forward neural network and recurrent neural network are introduced. And two adaptive control strategies for robotic tracking control are developed. One is recurrent...

The interval type-2 fuzzy, combined with sliding mode control, is proposed in this paper to design a novel nonlinear robust controller for a hypersonic aircraft. In this method, sliding mode reaching law is designed to keep the system stable. In order to overcome the uncertain parameters and external disturbances which exist in aerospace, we utilize an interval type-2 fuzzy approach represented...

This paper deals with resilient robust H∞ fuzzy control problem for a class of nonlinear time-delayed systems with norm-bounded and time-varying uncertainties in the matrices of state, delayed state and control gain via state feedback controllers. Firstly, the nonlinear system is represented by Takagi-Sugeno (TS) fuzzy model. Sufficient conditions are derived for the existence of resilient robu...

On the basis of inverse dynamics controller as a nominal control portion, two types of novel robust adaptive inverse dynamics control schemes are proposed for the trajectory tracking control of robot manipulator with uncertain dynamics. They are composed of an adaptive fuzzy control algorithm and a nonlinear H∞ tracking control model. The adaptive fuzzy control algorithm is employed to approxim...

Abstrae1-Most fuzzy controllers (FCs) for nonlinear second order systems are designed with a two-dimensional phase plane in mind. We show that the performance and the robustness of this kind of FC stems from their property of driving the system into the sliding mode (SM), in which the controlled system is invariant to parameter fluctuations and disturbances. Additionally, the continuous distrib...

In this paper, a robust adaptive fuzzy control algorithm based on the generalized fuzzy hyperbolic model (GFHM) for nonlinear system with uncertainties is proposed. The proposed control is a smooth control with no chattering phenomena, which consists of two control terms. One is the certainty equivalent control and the other is the compensated control, which is obtained by bounded estimation in...

An approach for the design of fuzzy control laws for tracking control of a large class of mechanical systems is proposed. The approach employs the framework of Lyapunov’s stability theory to formulate a class of control laws that guarantee convergence of the tracking errors to within speci3cation limits in presence of bounded parameter uncertainties and input disturbances. The proposed control ...