This work presents the development of mathematical model of a mobile manipulator and its use to develop a controller based on backstepping nonlinear control and the computed torque control law. This MIMO nonlinear controller was implemented on the Robot Operating System (ROS) environment. The mobile robot is based on the Barrett WAM (Whole Arm Manipulator) and a custom build mobile platform. Th...

This paper describes the control of a batch pH reactor by a nonlinear predictive controller that improves performance by using data of past batches. The control strategy combines the feedback features of a nonlinear predictive controller with the learning capabilities of run-to-run control. The inclusion of real-time data collected during the on-going batch run in addition to those from the pas...

In this paper, we develop a thermodynamic framework for addressing consensus problems for nonlinear multiagent dynamical systems with fixed and switching topologies. Specifically, we present distributed nonlinear static and dynamic controller architectures for multiagent coordination. The proposed controller architectures are predicated on system thermodynamic notions resulting in controller ar...

A self-tuning neurofuzzy integrating controller is derived in this paper for offset eliminating purpose. CARIMA plant model is used and the control law produces integral control terms in a natural way. Neurofuzzy networks are chosen to implement the direct self-tuning nonlinear integrating controller. The performance of the self-tuning integrating neurofuzzy controller is illustrated by example...

This paper studies the design of a static output feedback controller for nonlinear systems described by continuous-time Takagi-Sugeno (T-S) models. Motivated by stability results developed for parallel distributed compensation (PDC) controller, an Output PDC (OPDC) controller that corresponds to a nonlinear static output feedback control law is proposed. Both stabilisation and poles placement a...

Alrstrmt This paper presents a switching control scheme for multivariable nonlinear systems. Based on a fuzzy plant model of the multivariable nonlinear system, a switching controller consisting of H number of simple subcontrollers i s proposed. The paramctern of thc switching controller can be obtained by solvitig some LMls. A switching algorithm is developed. To illustrate the merits and the ...

Model-reference adaptive control with neurofuzzy methodology is derived in this paper. Associate memory network(AMN) is investigated in detail to be the possible implementation as the direct self-tuning nonlinear controller. The essence of the neurofuzzy controller has been discussed and the local stability of the system is reached. The performance of the model-reference adaptive neurofuzzy con...

A neural network (NN) based adaptive output feedback controller is proposed for a class of nonlinear systems. In this control scheme, the adaptive output feedback NN controller is proposed by using an observer to estimate the states of the system. The weights of the neural network can be adjusted in terms of Lyapnuov’s stability criterion. The proposed controller can be applied to nonlinear sys...

This paper presents an adaptive nonlinear position controller with velocity constraint, capable of combining the input-output linearization technique and Lyapunov stability theory. Based on the Lyapunov stability theory, the adaptation law of the proposed controller is derived along with the verification of the overall system’s stability. Computer simulation results demonstrate that the propose...

In this study, a fuzzy rule-based optimal controller is designed for nonlinear dynamical systems. The direct second order method (or directdescend-curvature algorithm) with a modification called “modified descend controller (MDC)” is used for calculating the parameters of the fuzzy feedback controller. The optimal control problem defined here has dynamic constraints of nonlinear system states a...