1.1 Robot manipulators Robot manipulators are well-known as nonlinear systems including strong coupling between their dynamics (Craig, 1996). These characteristics, in company with: 1) structured uncertainties caused by model imprecision of link parameters, payload variation, etc., and 2) unstructured uncertainties produced by un-modeled dynamics –such as nonlinear friction and external disturb...

This paper describes a hybrid approach to the problem of controlling flexible link manipulators for both structured and unstructured uncertainties conditions. First, a neural network controller based on the robot’s dynamic equation of motion is elaborated. It aims to produce a fast and stable control of the joint position and velocity, and to damp the vibration of each arm. Then, an adaptive ne...

A novel approach to neural network based tracking-control of robot manipulator including actuator dynamics is proposed by using of backstepping method. A simple two-step backstepping is considered for an nlink robotic system, and a feedforward neural controller is designed at second step where structured and unstructured uncertainties in robot dynamics and actuator model are approximated by thi...

This paper studies the consequences of alternative ways of representing uncertainty about a law of motion in a version of a classic macroeconomic targetting problem of Milton Friedman (1953). We study both “unstructured uncertainty” – ignorance of the conditional distribution of the target next period as a function of states and controls – and more “structured uncertainty” – ignorance of the pr...

This paper presents new adaptive robust control schemes for a class of nonlinear uncertain descriptor systems. Taking both the structured and unstructured uncertainties into consideration, the first control scheme achieves asymptotic stability of the closed-loop descriptor system. To avoid any potential problems such as parameter drift by unmodeled dynamics, in the second control scheme the ada...

A sum radial-basis-function neural-network (NN) compensator with computed-torque control and novel weight-tuning algorithms is proposed to improve tracking performance and to account for structured/unstructured uncertainties of robot manipulators. The proposed weight-tuning algorithms do not require the initial NN weights to be small. The bounds of NN weights are guaranteed to be convergent in ...

This paper presents a model on the leverage of …nancial intermediaries, where debt are held by risk averse agents and equity by the risk neutral. The paper shows that in an unregulated competitive market, …nancial intermediaries choose to be leveraged over the social best level. This is because the leverage of one intermediary imposes a negative externality upon others by reducing their pro…t m...

To overcome the disadvantages of conventional computed‐torque control and fuzzy control, and to exploit their attractive features, this paper proposes two types of adaptive control scheme combining conventional computed‐torque control and different fuzzy compensators for the robust tracking control of robotic manipulators with structured and unstructured unce...

In this paper, we introduce an adaptive type-2 fuzzy logic controller (FLC) for flexible-joint manipulators with structured and unstructured dynamical uncertainties. Simplified interval fuzzy sets are used for real-time efficiency, and internal stability is enhanced by adopting a trade-off strategy between the manipulator’s and the actuators’ velocities. Furthermore, the control scheme is indep...