Optimal sensor/actuator placement and switching schemes for control of flexible structures

The vibration control problem for flexible structures is examined within the context of overall controller performance and power reduction. First, the issue of optimal sensor and actuator placement is considered along with its associated control robustness aspects. Then the option of alternately activating subsets of the available devices is investigated. Such option is considered in order to better address the effects of spatiotemporally varying disturbances acting on a flexible structure while reducing the overall energy consumption. Towards the solution to the problem of optimal device placement, three different approaches are proposed. First, a computationally efficient scheme for the simultaneous placement of multiple devices is presented. The second approach proposes a strategy for the optimal placement of sensors and collocated sensor/actuator pairs, taking into account the influence of the spatial distribution of disturbances. The third approach provides a solution to the actuator location problem by incorporating considerations with respect to preferred spatial regions within the flexible structure. Then the second problem named above is considered. Activating a subset of the available and optimally placed actuators and sensors in a flexible structure provides enhanced performance with reduced energy consumption. Such approach of switching on and off different actuating devices, depending on their local-in-time authority, results in a hybrid system. Therefore the proposed work draws on existing results on hybrid systems and includes an additional degree of freedom, whereby both the actuating devices and the control signals allocated to them are switched in and out. To enable this switching an activation strategy, which insures also that stability-under-switching is guaranteed, is required. Three different strategies are considered for such actuators allocation: first a cost-to-go index is considered, then a cost function based on the mechanical energy of the flexible structure and finally a performance index based on the maximum deviation of the transverse displacement. A flexible aluminum plate was chosen to validate and test the proposed approaches. The set up utilized four pairs of collocated piezoceramic patches that serve to provide sensing and actuating capabilities. Extensive numerical simulations were performed for both the placement strategies and the switching policies proposed, in order to predict the behavior of the flexible plate and provide the optimal actuator and sensor locations that were to be affixed on the flexible structure. Finally, to complete the validation process a sequence of experimental tests were performed. The objective of these tests was to compare the performance of the proposed hybrid control system to traditional non switched control schemes. In order to provide a repeatable perturbation, four of the piezoceramic patches were allocated to simulate a spatiotemporally varying disturbance, while the remaining four patches were used as sensors and controlling actuators. The experimental results showed a significant performance improvement for the switched controller over the traditional controller. Moreover the switched controller exhibited improved robustness towards spatiotemporally varying disturbances while the traditional controller showed a significant loss of controller performance. The improvement achieved in vibration control problems could be extended to a wider range of applications. In particular, although this study was concentrated on a rectangular thin plate, the proposed strategies can be applied to emph{any} structure and more generally to any plant whose dynamics can be represented by a second order linear system. For example, by removing the restriction of spatially fixed actuators and sensors, the proposed theory can be applied to the problem of unmanned vehicles control

Port-based modeling and optimal control for a new very versatile energy efficient actuator

In this paper, we analyze in depth the innovative very versatile and energy efficient (V2E2) actuator proposed in Stramigioli et al. (2008). The V2E2 actuator is intended to be used in all kind of robotics and powered prosthetic applications in which energy consumption is a critical issue. In particular, this work focuses on the development of a port-based Hamiltonian model of the V2E2 and presents an optimal control architecture which exploits the intrinsic hybrid characteristics of the actuator design. The optimal control guarantees the minimization of dissipative power losses during torque tracking transients

Hybrid Cfd-Nnarx Modelling Of Single Mrf Valve For Visual Servoing.

Magnetorheological fluid (MRF) actuator emerged in the last decade as a potential system to replace electro-hydraulic servo system in precision applications. A complete closed-loop control system is necessary to support the accuracy of the system. Modelling of the valve is a crucial task in developing an optimal control system for the valve, but the knowledge of fluid behaviour inside the valve channel remains scarce. This research aims to develop a plant model of MRF actuator using the system identification approach, where the Computational Fluid Dynamics (CFD) result is used as an input. The plant model is then used to design a closed-loop control system for the MRF actuator. To achieve this objective, a 3D CFD model was developed, and a steady state analysis was run to study fluid behaviours in the channel. Transient analysis with dynamic input was further performed to study the correlation between the current input and the volume flow rate as an output. Neural network nonlinear autoregressive network with exogenous inputs (NNARX) used data from the CFD to identify the plant model of an MRF valve. The result acquired from the CFD simulation and plant model gave good agreement with the experimental result with an error of less than 3%. The velocity in the MRF valve reduced 85% when the current varied from 0 to 0.8A. The hybrid CFD-NNARX model shows a small deviation from the experimental result with an average error of 4%. As a conclusion, the hybrid CFDNNARX has been proven useful in modelling the MRF actuator. The main contribution of this work is the plant model of an MRF actuator, which can be utilised as an input in controller design process of MRF actuator

Design an intelligent controller for full vehicle nonlinear active suspension systems

The main objective of designed the controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which arises from road roughness and to increase the ride handling associated with the pitching and rolling movements. This necessitates a very fast and accurate controller to meet as much control objectives, as possible. Therefore, this paper deals with an artificial intelligence Neuro-Fuzzy (NF) technique to design a robust controller to meet the control objectives. The advantage of this controller is that it can handle the nonlinearities faster than other conventional controllers. The approach of the proposed controller is to minimize the vibrations on each corner of vehicle by supplying control forces to suspension system when travelling on rough road. The other purpose for using the NF controller for vehicle model is to reduce the body inclinations that are made during intensive manoeuvres including braking and cornering. A full vehicle nonlinear active suspension system is introduced and tested. The robustness of the proposed controller is being assessed by comparing with an optimal Fractional Order (FOPID) controller. The results show that the intelligent NF controller has improved the dynamic response measured by decreasing the cost function