in this research, first, kinematic and dynamic equations of a 4-dof 3-link robotic finger are derived using denavit-hartenberg convention and lagrange’s formulation. to model the muscles, several springs and dampers are placed between the finger links. then, two advanced controllers, namely adaptive-robust and adaptive-neural, which can control the robotic finger in presence of parametric uncer...

In this paper, we apply backstepping control method to derive new results for the adaptive controller and synchronizer design for the Arneodo chaotic system (1980), when the system parameters are unknown. First, we design an adaptive backstepping controller to stabilize the Arneodo system to its unstable equilibrium at the origin. Next, we design an adaptive backstepping controller to achieve g...

Power system stabilizers (PSSs) must be capable of providing appropriate stabilization signals over abroad range of operating conditions and disturbances. The main idea of this paper is changing aclassic PSS (CPSS) to an adaptive PSS using genetic algorithm. This new genetic algorithm based onadaptive PSS (GAPSS) improves power system damping, considerably. The controller design issue isformula...

In dealing with model predictive controllers (MPC), controller tuning is a key design step. Various tuning methods are proposed in the literature which can be categorized as heuristic, numerical and analytical methods. Among the available tuning methods, analytical approaches are more interesting and useful. This paper is based on a proposed analytical MPC tuning approach for plants can be appr...

An adaptive controller based upon the on-line minimization of a performance criteria is described. The adaptive controller is used to improve the performance of a one-legged mobile robot, removing prob lems experienced with previous controllers. The performance of several minimization algorithms is analyzed and, as a result, the Adaptive Step Size Random Search algorithm is selected. Finally, a...

Distillation is an essential separation process in the chemical and petrochemical industry. The distillation process is a highly nonlinear, complex, interactive and non -stationary, therefore its control is difficult. In the present work an adaptive neuro-fuzzy controller is designed to control a binary distillation process. A conventional PID controller is also designed for comparison purpose....

The objective of this study is to design a robust direct model reference adaptive controller (DMRAC) for a nonlinear cardiovascular model over a range of plant parameters representing a variety of physical conditions. The direct adaptive controllers used in thisd study require the plant to be almost strictly positive real (ASPR) that is, for a plant to be controlled there must exist a feedback ...

In this paper, we present an Adaptive Posicast Controller that deals with parametric uncertainties in linear systems with delays. It is assumed that the plant has no right half plane zeros and the delay is known. The adaptive controller is based on the Smith Predictor and Finite-Spectrum Assignment with time-varying parameters adjusted online. A novel Lyapunov-Krasovskii functional is used to s...

Recently, an adaptive posi-cast controller has been developed for dynamic systems with large time-delays. In this paper, we evaluate its performance in the context of a 4 MW combustor test-rig model that mimics many of the dynamic characteristics of an actual engine including a significant time-delay. Using closed loop input-output data and system identification, a model of the test-rig was der...