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Despite significant effort in modelling and simulating flotation circuits, comprehensive model based control and optimisation implementations on industrial circuits remain scarce. In this paper, the factors preventing more widespread implementation of model-based control and optimisation applications are investigated by focussing on three aspects. Firstly, the critical variables required in a simplified flotation model are identified. Models that are currently used in control, optimisation and supervisory applications are thereafter analysed to determine to what extent the required variables are modelled. Finally, online instrumentation available to support these models are investigated, also including instrumentation that is still under development and not commonly available in commercial applications. Although models used in control applications tend to focus on subsections of the flotation process, there seem to be a good agreement between the required and modelled variables. Model fitting however often relies on extensive sampling campaigns that will need to be repeated regularly to maintain model accuracy. A number of online measurements of sufficient accuracy are still not available to support these models, compromising the long term reliable use of models in online applications. The fact that flotation processes are in many instances not extensively instrumented, constrains online maintenance and adaption of model based solutions further.

This paper considers synchronization as a control problem. In particular, a (robust) controller for achieving synchronization in pairs of second order nonlinear systems is designed. The design is inspired by the classical experiment on synchronization of pendulum clocks, as described by Christiaan Huygens. In the proposed control scheme, the systems do not interact directly but through an exogenous system. Ultimately, it is demonstrated that Huygens' controller, can be used to perform in-phase and anti-phase synchronized tasks, with the advantage that 'small' control gains are required. The stability of the closed-loop system is analyzed using perturbation theory and the proposed controller is experimentally validated on a pair of Cartesian robots.

In this paper, we consider the asymptotic stabilization of a class of one dimensional boundary controlled port Hamiltonian systems by an immersion/reduction approach and the use of Casimir invariants. We first extend existing results on asymptotic stability of linear infinite dimensional systems controlled at their boundary to the case of stable Port Hamiltonian controllers including some physical constraints as clamping. Then the relation between structural invariants, namely Casimir functions, and the controller structure is computed. The Casimirs are employed in the selection of the controllers Hamiltonian to shape the total energy function of the closed loop system and introduce a minimum in the desired equilibrium configuration. The approach is illustrated on the model of a micro manipulation process with partial-actuation on one side of the spatial domain.

This paper discusses a method for introducing frequency-domain robustness constraints in a data-driven control design. The method is based on adaptive weighting filters used in a time-domain cost function to be minimized. In an iterative way, violation of the frequency-domain robustness constraints is checked by model prediction and accounted for by adapting the weighting filters. The method is applied to the stage synchronization problem in wafer scanners, which involves synchronization of the outputs of two motion systems, and will be discussed in view of both simulation results and experimental results.

This paper describes development of autonomous robot to clean dust in the International Space Station. Clean robot having an autonomous flight control and navigation in Japanese Experiment Module named "KIBO". And, it has function to collect dust which can't be recovered by ISS air conditioning. In this study, the authors chose to fish shapes for cleaning robot. Elastic oscillation fin was realized to have high controllability and soft behavior of creatures. Robotic fish takes evasive action by detecting the astronauts, walls, and obstacles. Then, cleaning work continues safe in cabin. The purpose of robotic fish is to reduce the cleaning workload of astronauts. And, the basic technology contributes to establish autonomous flight control and navigation in zero gravity., 9th IFAC Conference on Control Applications in Marine Systems, CAMS 2013; Osaka; Japan; 17 September 2013 through 20 September 2013, IFAC Proceedings Volumes, 9(1), pp.386-391; 2013

The objective of this paper is, on the base of existing results, to provide a general framework for synthesizing min-max MPC schemes with an a priori robust stability guarantee for nonlinear constrained systems. Using regional input-to-state stability, it is proven that the standard min-max approach can only guarantee practical stability. This is due to the choice of the stage cost. In order to avoid this problem, two different solutions have been considered: the first one is based on a particular design of the stage cost of the performance index, while the second one is based on a dual-mode strategy. It is shown that under fairly mild assumptions both controllers guarantee input-to-state stability.

Inspired by learning feed–forward control structures, this paper considers the adaptation of the parameters of a model–reference based learning feed–forward controller that realizes an inverse model of the process. The actual process response is determined by a setpoint generator. For linear systems it can be proved that the controlled system is asymptotically stable in the sense of Liapunov. Compared with more standard model reference configurations this system has a superior performance. It is fast, robust and relatively insensitive for noisy measurements. Simulations with an arbitrary second–order process and with a model of a typical fourth–ordermechatronics process demonstrate this.

This paper presents an experimental implementation of an observer-based controller design strategy on a piecewise linear beam system comprising a flexible steel beam with a one-sided support. The observer-based controller design strategy guarantees a unique globally asymptotically stable steady-state solution of the closed-loop system, which allows for unique performance evaluation in terms of disturbance attenuation. Experimental and simulation results are presented to demonstrate the effectiveness of the strategy.

This paper presents an experimental implementation of an observer-based controller design strategy on a piecewise linear beam system comprising a flexible steel beam with a one-sided support. The observer-based controller design strategy guarantees a unique globally asymptotically stable steady-state solution of the closed-loop system, which allows for unique performance evaluation in terms of disturbance attenuation. Experimental and simulation results are presented to demonstrate the effectiveness of the strategy.

In this paper we prescntan experimental study in the identification of an industrial hybrid system. Piecewise ARX models, that consist of a number of ARX models, together with the partition of the regressor space into regions where each of the models is valid, were identified. Effects of dry friction, and mechanical constraints in the experimental setup are demonstrated, and their influence on the identification procedure is discussed. Comparison of the simulated responses of the identified models with the responses of the real system shows mat the obtained models are able to describe relevant aspects of the dynamics of the experimental setup. Ways to improve die identification procedure are proposed.

In this paper we prescntan experimental study in the identification of an industrial hybrid system. Piecewise ARX models, that consist of a number of ARX models, together with the partition of the regressor space into regions where each of the models is valid, were identified. Effects of dry friction, and mechanical constraints in the experimental setup are demonstrated, and their influence on the identification procedure is discussed. Comparison of the simulated responses of the identified models with the responses of the real system shows mat the obtained models are able to describe relevant aspects of the dynamics of the experimental setup. Ways to improve die identification procedure are proposed.

A controller is presented for point stabilization of the extended chained form system. The extended chained form system can not be stabilized by means of continuous pure-state feedback. Moreover, it can not be exponentially stabilized by smooth feedback, since the linearization around equilibrium points is uncontrollable. In this paper, a controller is given that ρ-exponentially stabilizes the system. The controller is derived by using a combined averaging technique for homogeneous systems and a backstepping approach. The controller is illustrated in a benchmark example by application to the V/STOL aircraft without gravity.

The paper deals with the problem of destabilization of diffusively coupled identical systems. It is shown that the globally asymptotically stable systems being diffusively coupled may exhibit an oscillatory behavior. It is shown that if the diffusive medium consists of hyperbolically nonminimum phase systems and the diffusive factors exceed some threshold value the origin of the overall system undergoes a Poincare-Andronov-Hopfbifurcation resulting in oscillatory behavior.

In this paper we deal with the state-feedback tracking control problem for a class of nonholonomic dynamic systems in chained form. By means of the recursive technique proposed in our recent work, we first show that the semiglobal exponential tracking can be easily obtained for systems in chained form. Then, we show that, whenever the control inputs are subject to saturation constraints, a semiglobal asymptotic tracking controller can be found on the basis of Lyapunov redesign and backstepping techniques.

The design of a control system is not finished with the derivation of the necessary control algorithms. The system designer has to schedule all control and calculation tasks within the sampling interval of the system. Higher sampling frequencies often improve the system performance. On the other hand, more sophisticated control algorithms require more computing time thus reducing the obtainable sampling frequencies. In this paper a systematic approach to obtain a design optimum is given. The design method is illustrated with the control of a flexible robot arm.