In this work, an adaptive controller for bioreactors, using the measurement of output gas flow rate to handle the uncertainty on biomass concentration and kinetic rate is developed. A mass–balance model based on a unique reaction pathway to represent the input–output behavior is considered....

A novel approach to adaptive direct neurocontrol is discussed in this paper. The objective is to construct an adaptive control scheme for unknown time-dependent nonlinear plants without using a model of the plant. The proposed approach is neural-network based and combines the self-tuning...

This paper proposes a direct adaptive fuzzy-model-based control algorithm. The controller is based on an inverse semi-linguistic fuzzy process model, identified and adapted via input-matching technique. For the adaptation of the fuzzy model a general learning rule has been developed employing...

This paper presents an adaptive control scheme for a hyper-redundant robot articulated nimble adaptable trunk (ANAT) subject to spatial constraints. An optimization scheme is applied to avoid obstacles in 3D space present in the robot's trajectory by using redundancy, and to prevent the robot...

This paper presents an indirect adaptive control scheme for nominally stabilizable, non-necessarily inversely stable, first-order continuous-time systems with unmodeled dynamics. The control objective is the adaptive stabilization of the closed-loop system with a bounded tracking error between...

Cascade control configurations offer interesting possibilities to improve the control of processes. However, the tuning of cascade controllers can be quite complex, which hampers a wider spread of applications. Using an on-line pattern recognition approach and fuzzy inferencing it is possible to...

In this paper, we study perturbed Chua’s system. First, we study the stability of equilibrium points of perturbed Chua’s system. Then, we control the chaotic behavior of perturbed Chua’s system to its equilibrium points using linear feedback control and adaptive control methods. Finally,...

We address the problem of control and synchronization of a class of uncertain chaotic systems. Our approach follows techniques of sliding mode control and adaptive estimation law. The adaptive algorithm is constructed based on the sliding mode control to ensure perfect tracking and...

A neural network-based robust adaptive control design scheme is developed for a class of nonlinear systems represented by input–output models with an unknown nonlinear function and unmodeled dynamics. By on-line approximating the unknown nonlinear functions and unmodeled dynamics by radial...

Using the Lyapunov stability theory an adaptive control is proposed for chaos synchronization between two Chua systems which have stochastically time varying unknown coefficients. The stochastic variations of the coefficients around their unknown mean values are modeled through Gaussian white...