2,477 research outputs found
On the control of complementary-slackness juggling mechanical systems
International audienceThis paper studies the feedback control of a class of complementary-slackness hybrid mechanical systems. Roughly, the systems we study are composed of an uncontrollable part (the "object") and a controlled one (the "robot"), linked by a unilateral constraint and an impact rule. A systematic and general control design method for this class of systems is proposed. The approach is a nontrivial extension of the one degree-of-freedom (DOF) juggler control design. In addition to the robot control, it is also useful to study some intermediate controllability properties of the object's impact Poincaré mapping, which generally takes the form of a non-linear discrete-time system. The force input mainly consists of a family of dead-beat feedback control laws, introduced via a recur-sive procedure, and exploiting the underlying discrete-time structure of the system. The main goal of this paper is to highlight the role of various physical and control properties characteristic of the system on its stabilizability properties and to propose solutions in certain cases
Quantum Internal Model Principle: Decoherence Control
In this article, we study the problem of designing a Decoherence Control for
quantum systems with the help of a scalable ancillary quantum control and
techniques from geometric control theory, in order to successfully and
completely decouple an open quantum system from its environment. We
re-formulate the problem of decoherence control as a disturbance rejection
scheme which also leads us to the idea of Internal Model Principle for quantum
control systems which is first of its kind in the literature.
It is shown that decoupling a quantum disturbance from an open quantum
system, is possible only with the help of a quantum controller which takes into
account the model of the environmental interaction. This is demonstrated for a
simple 2-qubit system wherein the effects of decoherence are completely
eliminated. The theory provides conditions to be imposed on the controller to
ensure perfect decoupling. Hence the problem of decoherence control naturally
gives rise to the quantum internal model principle which relates the
disturbance rejecting control to the model of the environmental interaction.
Classical internal model principle and disturbance decoupling focus on
different aspects viz. perfect output tracking and complete decoupling of
output from external disturbances respectively. However for quantum systems,
the two problems come together and merge in order to produce an effective
platform for decoherence control. In this article we introduce a seminal
connection between disturbance decoupling and the corresponding analog for
internal model principle for quantum systems.Comment: Submitted to IEEE Transactions on Automatic Control, Mar 15 2010. A
basic introduction appeared in 46th IEEE CDC 2007. Acknowledgements: The
authors would like to thank the Center for Quantum Information Science and
Technology at Tsinghua University, R.-B. Wu, J. Zhang, J.-W. Wu, M. Jiang,
C.-W. Li and G.-L. Long for their valuable comments and suggestion
Information flow and cooperative control of vehicle formations
We consider the problem of cooperation among a collection of vehicles performing a shared task using intervehicle communication to coordinate their actions. Tools from algebraic graph theory prove useful in modeling the communication network and relating its topology to formation stability. We prove a Nyquist criterion that uses the eigenvalues of the graph Laplacian matrix to determine the effect of the communication topology on formation stability. We also propose a method for decentralized information exchange between vehicles. This approach realizes a dynamical system that supplies each vehicle with a common reference to be used for cooperative motion. We prove a separation principle that decomposes formation stability into two components: Stability of this is achieved information flow for the given graph and stability of an individual vehicle for the given controller. The information flow can thus be rendered highly robust to changes in the graph, enabling tight formation control despite limitations in intervehicle communication capability
An Approach to Simultaneous Control of Trajectory and Interaction Forces in Dual-Arm Configurations
Multiple arm systems, multifingered grippers, and walking vehicles all have two common features. In each case, more than one actively coordinated articulation interacts with a passive object, thus forming one or more closed chains. For example, when two arms grasp an object simultaneously, the arms together with the object and the ground (base) form a closed chain. This induces kinematic and dynamic constraints and the resulting equations of motion are extremely nonlinear and coupled. Furthermore, the number of actuators exceeds the kinematic mobility of the chain in a typical case, which results in an underdetermined system of equations. An approach to control such constrained dynamic systems is described in this short paper. The basic philosophy is to utilize a minimal set of inputs to control the trajectory and the surplus inputs to control the constraint or interaction forces and moments in the closed chain. A dynamic control model is derived for the closed chain that is suitable for designing a controller, in which the trajectory as well as the interaction forces and moments are explicitly controlled. Nonlinear feedback techniques derived from differential geometry are then applied to linearize and decouple the nonlinear model. In this paper, these ideas are illustrated through a planar example in which two arms are used for cooperative manipulation. Results from a simulation are used to illustrate the efficacy of the method
Intelligent flight control systems
The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms
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