Most researches so far on robot control have assumed that the exact kinematics and Jacobian matrix of the manipulator from joint space to Cartesian space are known. Unfortunately, no physical parameters could be derived exactly. In addition, the robot is required to interact with its environment and hence the overall parameters would change according to different tasks. In this paper, simple fe...

This paper treats the practical and challenging control problem of tracking a prescribed continuous trajectory for an autonomous vehicle in the presence of gravity, buoyancy, fluid dynamic and other forces and moments that are uncertain. These uncertain forces and moments are bounded and may be difficult to model accurately, but they act persistently or over long periods of time. The trajectory...

This paper presents a novel approach to the problem of output feedback stabilization with L2 disturbance attenuation for nonlinear uncertain systems. A new method of state-dependent scaling is introduced into the output feedback design, which unifies treatment of nonlinear and linear gains. The effect of disturbance on the controlled output, which is allowed to be any function of measurement ou...

Abstract: This paper presents a fuzzy robust controller for the nonlinear systems with uncertain dynamics. The main idea of this method is that Type-2 fuzzy system estimates nonlinear and uncertain functions exist in the system equations and then the parameters of type-2 fuzzy system are tuned online by adaptive rules obtained from Lyapunov theory and finally, stability and convergence analysis...

We develop an adaptive control architecture to achieve stabilization and command following of uncertain dynamical systems with improved transient performance. Our framework consists of a new reference system and an adaptive controller. The proposed reference system captures a desired closed-loop dynamical system behavior modified by a mismatch term representing the high-frequency content betwee...

Verification of probabilistic systems is usually based on variants of Markov processes. For systems with continuous dynamics, Markov processes are generated using discrete approximation methods. These methods assume an exact model of the dynamic behavior. However, realistic systems operate in the presence of uncertainty and variability and they are described by uncertain models. In this paper, ...

A robust hybrid control strategy for a broad class of hybrid nonlinear processes with actuator constraints and uncertain dynamics is proposed. These ®ariable-structure processes comprise a finite family of constrained uncertain continuous nonlinear dynamical subsystems, together with discrete e®ents that trigger the transition between the continuous subsystems. The proposed control strategy is ...

Risk aversion is prevalent behaviors of decision makers when the external environment is uncertain. In this paper, the dynamic output game strategies in two-tier supply chains under uncertain demand and competitive environment are discussed, where the supply chains include a risk-averse manufacturer and customers respectively. Two game models with a mean-variance framework are developed under d...

Some robust control methods have been developed in the past in order to increase tracking performance in the presence of parametric uncertainties. In the presence of parametric uncertainty, unmodelled dynamics and other sources of uncertainties, robust control laws are used. Corless-Leitmann [1] approach is a popular approach used for designing robust controllers for robot manipulators. In earl...