Online Convex Programming (OCP) is a recently developed model of sequential decision-making in the presence of time-varying uncertainty. In this framework, a decisionmaker selects ...
We present a discrete-time adaptive control law that is effective for systems that are MIMO and either minimum phase or nonminimum phase. The adaptive control algorithm provides gu...
Mario A. Santillo, Matthew S. Holzel, Jesse B. Hoa...
Abstract. In this paper, we propose a novel approach for adaptive control of robotic manipulators. Our approach uses a representation of inverse dynamics models learned from a vari...
An adaptive control scheme for mechanical manipulators is proposed. The control loop essentially consists of a network for learning the robot's inverse dynamics and on-line ge...
This paper deals with the adaptive control of a class of continuous-time nonlinear dynamic systems preceded by an unknown dead-zone. By using a new description of a dead-zone and ...
The certainty equivalence approach to adaptive control is commonly used with two types of identifiers: passivity-based identifiers and swapping identifiers. The “passive” (...
The performance of a Multiobjective Evolutionary Algorithm (MOEA) is crucially dependent on the parameter setting of the operators. The most desired control of such parameters pre...
— This paper proposes a strategy referred to as Stability Overlay (SO) for linear and nonlinear time-varying plants, that provides input/output stability guarantees for a wide se...
Paulo Andre Nobre Rosa, Jeff S. Shamma, Carlos Sil...
Due to the increasing complexity, the behavior of large-scale distributed systems becomes difficult to predict. The ability of on-line identification and autotuning of adaptive co...
— A decentralized, adaptive control law is presented to drive a network of mobile robots to a near-optimal sensing configuration. The control law is adaptive in that it integrat...
Mac Schwager, Jean-Jacques E. Slotine, Daniela Rus