Intelligent systems may be viewed as a framework for solving the problems of nonlinear system control. The intelligence of the system in the nonlinear or changing environment is used to recognize in which environment the system currently resides and to service it appropriately. This paper presents a general methodology of adaptive control based on multiple models in fuzzy form to deal with plan...

Several multiple model adaptive control architectures have been proposed in the literature. Despite many advances in theory, the crucial question of how to synthesize the pairs model/controller in a structurally optimal way is to a large extent not addressed. In particular, it is not clear how to place the pairs model/controller is such a way that the properties of the switching algorithm (e.g....

Using multiple interacting drugs to control both the mean arterial pressure (MAP) and cardiac output (CO) of patients with different sensitivity to drugs is a challenging task which this paper attempts to address. A multivariable model reference adaptive control (MRAC) algorithm is developed using a two-input, two-output patient model. The control objective is to maintain the homodynamic variab...

Model predictive control (MPC) has become the leading form of advanced multivariable control in the chemical process industry. The objective of this work is to introduce a multiple model adaptive control strategy for multivariable dynamic matrix control (DMC). The novelty of the strategy lies in several subtle but significant details. One contribution is that the method combines the output of m...

Multiple contact interaction is common in many robotic applications. These include grasping, wheeled vehicles, and distributed manipulation. All of these applications are capable of experiencing stick/slip phenomena at the contact interfaces. In particular, when there are more kinematic constraints than there are degrees of freedom, some contact interfaces must slip. Moreover, this stick/slip b...

For a class of nonlinear systems with input saturation, a kind of adaptive fuzzy control law based on multiple-model structure is presented in this paper. First, a basic fuzzy controller is designed with adaptive weight parameters determined by multiplemodel switching performance indexes. Then a dynamic structure adaptive neural network is introduced for ensuring the system stable, while the co...

It is proved that the transient performance of nonlinear adaptive backstepping can be improved by resetting the parameter estimator, without loss of stability. The estimator resetting algorithm is based on multiple model adaptive control, where a number of models with xed parameter vectors are monitored online in order to detect parameter vectors that gives a negative jump in the control Lyapun...