Dissipative stability theory for linear repetitive processes with application in iterative learning control

This paper develops a new set of necessary and sufficient conditionsfor the stability of linear repetitiveprocesses, based on a dissipative setting for analysis. Theseconditions reduce the problem of determining whether a linearrepetitive process is stable or not to that of checking for theexistence of a solution to a set of linear matrixinequalities (LMIs). Testing the resulting conditions only requirescomputations with matrices whose entries are constant in comparison toalternatives where frequency response computations are required

A proposal for a global task planning architecture using the RoboEarth cloud based framework

As robotic systems become more and more capable of assisting in human domains, methods are sought to compose robot executable plans from abstract human instructions. To cope with the semantically rich and highly expressive nature of human instructions, Hierarchical Task Network planning is often being employed along with domain knowledge to solve planning problems in a pragmatic way. Commonly, the domain knowledge is specific to the planning problem at hand, impeding re-use. Therefore this paper conceptualizes a global planning architecture, based on the worldwide accessible RoboEarth cloud framework. This architecture allows environmental state inference and plan monitoring on a global level. To enable plan re-use for future requests, the RoboEarth action language has been adapted to allow semantic matching of robot capabilities with previously composed plans

Dissipative stability theory for linear repetitive processes with application in iterative learning control

Abstract-This paper develops a new set of necessary and sufficient conditions for the stability of linear repetitive processes, based on a dissipative setting for analysis. These conditions reduce the problem of determining whether a linear repetitive process is stable or not to that of checking for the existence of a solution to a set of linear matrix inequalities (LMIs). Testing the resulting conditions only requires computations with matrices whose entries are constant in comparison to alternatives where frequency response computations are required

Stability analysis of networked control systems using a switched linear systems approach.

Abstract. In this paper, we study the stability of Networked Control Systems (NCSs) that are subject to time-varying transmission intervals and communication constraints in the sense that, per transmission, only one node can access the network and send its information. The order in which nodes send their information is dictated by a network protocol, such as the well-known Round Robin (RR) or Try-Once-Discard (TOD) protocol. Focussing on linear plants and linear continuous-time or discrete-time controllers, we model the NCS with time-varying transmission intervals as a discrete-time switched linear uncertain system. We obtain bounds for the allowable range of transmission intervals in terms of both minimal and maximal allowable transmission intervals. Hereto, a new convex overapproximation of the uncertain switched system is proposed, using a polytopic system with norm-bounded uncertainty, and new stability results for this class of hybrid systems are developed. On the benchmark example of a batch reactor, we explicitly exploit the linearity of the system, leading to a significant reduction in conservatism with respect to the existing approaches

Linear Control of Time-Domain Constrained Systems

Abstract-Recent results on the control of linear systems subject to time-domain constraints could only handle the case of closed-loop poles that are situated on the real axis. As most closed-loop systems in practice contain also complex poles, there is a strong need for a general framework encompassing all cases. In this paper such a framework is presented based on sumsof-squares techniques and we show indeed that time-domain constraints on closed-loop signals of linear systems can be incorporated as linear matrix inequalities, even when complex conjugate poles are assigned. The effectiveness of this complete design method is evaluated by means of a simulation example

Control of the tokamak safety factor profile with time-varying constraints using MPC

A controller is designed for the tokamak safety factor profile that takes real-time-varying operational and physics limits into account. This so-called model predictive controller (MPC) employs a prediction model in order to compute optimal control inputs that satisfy the given limits. The use of linearized models around a reference trajectory results in a quadratic programming problem that can easily be solved online. The performance of the controller is analysed in a set of ITER L-mode scenarios simulated with the non-linear plasma transport code RAPTOR. It is shown that the controller can reduce the tracking error due to an overestimation or underestimation of the modelled transport, while making a trade-off between residual error and amount of controller action. It is also shown that the controller can account for a sudden decrease in the available actuator power, while providing warnings ahead of time about expected violations of operational and physics limits. This controller can be extended and implemented in existing tokamaks in the near future.</p