Self-Sensing Control for Soft-Material Actuators Based on Dielectric Elastomers

Due to their energy density and softness that are comparable to human muscles dielectric elastomer (DE) transducers are well-suited for soft-robotic applications. This kind of transducer combines actuator and sensor functionality within one transducer so that no external senors to measure the deformation or to detect collisions are required. Within this contribution we present a novel self-sensing control for a DE stack-transducer that allows to control several different quantities of the DE transducer with the same controller. This flexibility is advantageous e.g., for the development of human machine interfaces with soft-bodied robots. After introducing the DE stack-transducer that is driven by a bidirectional flyback converter, the development of the self-sensing state and disturbance estimator based on an extended Kalman-filter is explained. Compared to known estimators designed for DE transducers supplied by bulky high-voltage amplifiers this one does not require any superimposed excitation to enable the sensor capability so that it also can be used with economic and competitive power electronics like the flyback converter. Due to the behavior of this converter a sliding mode energy controller is designed afterwards. By introducing different feed-forward controls the voltage, force or deformation can be controlled. The validation proofs that both the developed self-sensing estimator as well as the self-sensing control yield comparable results as previously published sensor-based approaches.TU Berlin, Open-Access-Mittel - 201

Modeling and fault tolerant control of an electro-hydraulic actuator

In the modern industry, electro-hydraulic actuators (EHAs) have been applied to various applications for precise position pressure/ force control tasks. However, operating EHAs under sensor faults is one of the critical challenges for the control engineers. For its enormous nonlinear characteristics, sensor fault could lead the catastrophic failure to the overall system or even put human life in danger. Thus in this paper, a study on mathematical modeling and fault tolerant control (FTC) of a typical EHA for tracking control under sensor-fault conditions has been carried out. In the proposed FTC system, the extended Kalman-Bucy unknown input observer (EKBUIO) -based robust sensor fault detection and identification (FDI) module estimates the system states and the time domain fault information. Once a fault is detected, the controller feedback is switched from the faulty sensor to the estimated output from the EKBUIO owing to mask the sensor fault swiftly and retains the system stability. Additionally, considering the tracking accuracy of the EHA system, an efficient brain emotional learning based intelligent controller (BELBIC) is suggested as the main control unit. Effectiveness of the proposed FTC architecture has been investigated by experimenting on a test bed using an EHA in sensor failure conditions

Observer techniques applied to the control of piezoelectric Microactuators.

International audienceWe present here the use of sensors, observers and self-sensing techniques to control piezoelectric actuators, particularly piezocantielevers. First, the feedback control with full measurements (all variables are measured) is presented. Because of the lack of convenient sensors for the microworld, nonfull measurements combined with observer techniques is proposed. Finally, the self-sensing principle, where the actuator is at the same time sensor, is applied and used for the feedback

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

Design, Modeling and Control of a Thermal Management System for Hybrid Electric Vehicles

Hybrid electric vehicle (HEV) technology has evolved in the last two decades to become economically feasible for mass produced automobiles. With the integration of a lithium battery pack and electric motors, HEVs offer a significantly higher fuel efficiency than traditional vehicles that are driven solely by an internal combustion engine. However, the additional HEV components also introduce new challenges for the powertrain thermal management system design. In addition to the common internal combustion engine, the battery pack, the generator(s), as well as the electric motor(s) are now widely applied in the HEVs and have become new heat sources and they also require proper thermal management. Conventional cooling systems have been typically equipped with a belt driven water pump and radiator fan, as well as other mechanical actuators such as the thermostat valve. The operation of these components is generally determined by the engine speed. This open-loop cooling strategy has a low efficiency and suffers the risk of over-cooling the coolant and components within the system. In advanced thermal management systems, the mechanical elements are upgraded by computer controlled actuators including a servo-motor driven pump, variable speed fans, a smart thermostat, and an electric motor driven compressor. These electrified actuators offer the opportunity to improve temperature tracking and reduce parasitic losses. This dissertation investigates a HEV powertrain thermal management system featuring computer controlled cooling system actuators. A suite of mathematical models have been created to describe the thermal behaviour of the HEV powertrain components. Model based controllers were developed for the vehicle\u27s cooling systems including the battery pack, electric motors, and internal combustion engine. Optimal control theory has been applied to determine the ideal battery cooling air temperature and the desired heat removal rate on e-motor cooling surface. A model predictive controller(MPC) was developed to regulate the refrigerant compressor and track the battery cooling air temperature. A series of Lyapunov-based nonlinear controllers have been implemented to regulate the coolant pumps and radiator fans in the cooling systems for the engine and e-motors. Representative numerical results are presented and discussed. Overall, the proposed control strategies have demonstrated the effectiveness in improving both the temperature tracking performance and the cooling system power consumption reduction. The peak temperature error in the selected A123 battery core can be tracked within 0.25 C of the target; a 50% reduction of the vapor compression system energy consumption can be obtained by properly designing the cooling air flow structure. Similarly, the cooling system of HEV electric motors shows that the machine internal peak temperature can be tracked to the target value with a maximum error of 3.9 C and an average error of 0.13 C. A 70% to 81% cooling system energy consumption reduction can be achieved under different driving cycle comparing to classical controller applied to maintain a similar level of hotspot temperature stabilization. The proposed optimal nonlinear controller tracks the engine coolant temperature with an average error of 0.35 C and at least 13% reduction in engine cooling power. Further, a close analysis on the cooling system energy consumption reduction has been conducted with a heat exchanger simulation tool established for cooling system design optimization. This research has developed the basis for the holistic control of HEV powertrain thermal management systems by including a suite of model based nonlinear controllers to simultaneously regulate the cooling actuators for the battery pack, e-motors, and conventional internal combustion engine. Numerical studies has been conducted with a high fidelity HEV model under real driving cycles to demonstrate the advantages of introducing advanced control theory into multi-mode vehicle drive systems

Dynamics, control and sensor issues pertinent to robotic hands for the EVA retriever system

Basic dynamics, sensor, control, and related artificial intelligence issues pertinent to smart robotic hands for the Extra Vehicular Activity (EVA) Retriever system are summarized and discussed. These smart hands are to be used as end effectors on arms attached to manned maneuvering units (MMU). The Retriever robotic systems comprised of MMU, arm and smart hands, are being developed to aid crewmen in the performance of routine EVA tasks including tool and object retrieval. The ultimate goal is to enhance the effectiveness of EVA crewmen