932 research outputs found

    H∞ control for networked systems with random communication delays

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    Copyright [2006] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This note is concerned with a new controller design problem for networked systems with random communication delays. Two kinds of random delays are simultaneously considered: i) from the controller to the plant, and ii) from the sensor to the controller, via a limited bandwidth communication channel. The random delays are modeled as a linear function of the stochastic variable satisfying Bernoulli random binary distribution. The observer-based controller is designed to exponentially stabilize the networked system in the sense of mean square, and also achieve the prescribed H∞ disturbance attenuation level. The addressed controller design problem is transformed to an auxiliary convex optimization problem, which can be solved by a linear matrix inequality (LMI) approach. An illustrative example is provided to show the applicability of the proposed method

    Control of an IPMC soft actuator using adaptive full-order recursive terminal sliding mode

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    The ionic polymer metal composite (IPMC) actuator is a kind of soft actuator that can work for underwater applications. However, IPMC actuator control suffers from high nonlinearity due to the existence of inherent creep and hysteresis phenomena. Furthermore, for underwater applications, they are highly exposed to parametric uncertainties and external disturbances due to the inherent characteristics and working environment. Those factors significantly affect the positioning accuracy and reliability of IPMC actuators. Hence, feedback control techniques are vital in the control of IPMC actuators for suppressing the system uncertainty and external disturbance. In this paper, for the first time an adaptive full-order recursive terminal sliding-mode (AFORTSM) controller is proposed for the IPMC actuator to enhance the positioning accuracy and robustness against parametric uncertainties and external disturbances. The proposed controller incorporates an adaptive algorithm with terminal sliding mode method to release the need for any prerequisite bound of the disturbance. In addition, stability analysis proves that it can guarantee the tracking error to converge to zero in finite time in the presence of uncertainty and disturbance. Experiments are carried out on the IPMC actuator to verify the practical effectiveness of the AFORTSM controller in comparison with a conventional nonsingular terminal sliding mode (NTSM) controller in terms of smaller tracking error and faster disturbance rejection

    Dynamics and Control of Fiber-Elastomer Composites embedded with Shape Memory Alloys

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    Soft robots have been used in a wide range of applications from robotic and mechanical engineering to medicine and biomededical field. The growing interest in soft robots comes from their good performance in environments which is not best suited for conventional rigid bodies. Soft robots utilize the compliance, adaptability and flexibility of soft materials and actuation methods to develop highly adaptive structures. Among the soft materials, elastomers are specially popular due to their wide range of elasticity and viscoelasticity. Along with elastomers, textile fabrics are also of high interest for soft robotic applications due to their bendable, flexible, and often stretchable nature. The reinforcement of elastomers with textile fibers results in so-called integrated fiber-elastomer composites (IFEC) which offer a wide variety of properties such as flexibility, strength, fracture toughness and damage resistance. The elastic properties of textile reinforced composites require smart actuators which possess adaptability and deformability. Among existing smart actuators, shape memory alloys (SMA) have been frequently adopted in flexible structures including soft robots. SMAs have sensing and actuation capabilities and are characterized by flexibility and lightness which facilitates their integration into these structures. In this dissertation, the modeling and control of soft prototypes made of IFEC are presented. Shape memory alloys are embedded in the composites for the system actuation. First, the mechanical design and production of three IFEC prototypes are described. For each prototype, a test bench including power and control electronics set-up is designed. Next, mathematical models are developed to analyze the dynamic behavior of the prototypes. The IFEC systems exhibit highly nonlinear behaviour due to SMA hysteresis. For modeling, two different approaches, namely physical modelling and system identification are adopted. In physical modeling, the SMA constitutive and heat transfer equations are incorporated with the composite deflection model. To fully develop the equations, thermal and mechanical parameters of SMA wires are identified experimentally. In the second approach, the mathematical model of the systems is derived from experimental identification and unstructured uncertainty models. Two different control techniques are proposed to compensate the nonlinear behavior of the systems and ensure a robust, fast and precise position tracking. In the first control technique, a proportional integral (PI) controller is designed through robust stability analysis. The second controller is a multivariable PI control which is designed for the prototypes that can move in more than one direction. The performance of the controllers are examined experimentally

    Nonlinear, Adaptive and Fault-tolerant Control for Electro-hydraulic Servo Systems

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    Retrospective-Cost Adaptive Control of Uncertain Hammerstein-Wiener Systems with Memoryless and Hysteretic Nonlinearities

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97108/1/AIAA2012-4449.pd

    Model reference control for ultra-high precision positioning systems

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    Due to the increasing demands of high-density semiconductors, molecular biology, optoelectronics, and MEMS/NEMS in the past decades, control of ultra-high precision positioning using piezoelectricity has become an important area because of its high displacement resolution, wide bandwidth, low power consumption, and potential low cost. However, the relatively small displacement range limits its application. This work proposed a practical ultra-high precision piezoelectric positioning system with a complementary high displacement range actuation technology. Solenoids are low cost, high speed electromagnetic actuators which are commonly used in on-off mode only because of the inherent high nonlinear force-stroke characteristics and unipolar forces (push/pull) generated by the magnetic fields. In this work, an integrated positioning system based on a monolithic piezoelectric positioner and a set of push-pull dual solenoid actuators is designed for high speed and high precision positioning applications. The overall resolution can be sub-nanometer while the moving range is in millimeters, a three order of magnitude increase from using piezoelectric positioner alone. The dynamic models of the dual solenoid actuator and piezoelectric nanopositioner are derived. The main challenge of designing such positioning systems is to maintain the accuracy and stability in the presence of un-modeled dynamics, plant variations, and parasitic nonlinearities, specifically in this work, the friction and forcestroke nonlinearities of the dual solenoid actuator, and the friction, hysteresis and coupling effects of piezoelectric actuator, which are impossible to be modeled accurately and even time-varying. A model reference design approach is presented to attenuate linear as well as nonlinear uncertainties, with a fixed order controller augmenting a reference model that embeds the nominal dynamics of the plant. To improve transient characteristics, a Variable Model Reference Zero Vibration (VMRZV) control is also proposed to stabilize the system and attenuate the adverse effect of parasitic nonlinearities of micro-/nano- positioning actuators and command-induced vibrations. The speed of the ultra-high precision system with VMRZV control can also be quantitatively adjusted by systematically varying the reference model. This novel control method improves the robustness and performance significantly. Preliminary experimental data on dual solenoid system confirm the feasibility of the proposed method

    Modeling and Control of Piezoelectric Actuators

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    Piezoelectric actuators (PEAs) utilize the inverse piezoelectric effect to generate fine displacement with a resolution down to sub-nanometers and as such, they have been widely used in various micro- and nanopositioning applications. However, the modeling and control of PEAs have proven to be challenging tasks. The main difficulties lie in the existence of various nonlinear or difficult-to-model effects in PEAs, such as hysteresis, creep, and distributive vibration dynamics. Such effects can seriously degrade the PEA tracking control performances or even lead to instability. This raises a great need to model and control PEAs for improved performance. This research is aimed at developing novel models for PEAs and on this basis, developing model-based control schemes for the PEA tracking control taking into account the aforementioned nonlinear effects. In the first part of this research, a model of a PEA for the effects of hysteresis, creep, and vibration dynamics was developed. Notably, the widely-used Preisach hysteresis model cannot represent the one-sided hysteresis of PEAs. To overcome this shortcoming, a rate-independent hysteresis model based on a novel hysteresis operator modified from the Preisach hysteresis operator was developed, which was then integrated with the models of creep and vibration dynamics to form a comprehensive model for PEAs. For its validation, experiments were carried out on a commercially-available PEA and the results obtained agreed with those from model simulations. By taking into account the linear dynamics and hysteretic behavior of the PEA as well as the presliding friction between the moveable platform and the end-effector, a model of the piezoelectric-driven stick-slip (PDSS) actuator was also developed in the first part of the research. The effectiveness of the developed model was illustrated by the experiments on the PDSS actuator prototyped in the author's lab. In the second part of the research, control schemes were developed based on the aforementioned PEA models for tracking control of PEAs. Firstly, a novel PID-based sliding mode (PIDSM) controller was developed. The rational behind the use of a sliding mode (SM) control is that the SM control can effectively suppress the effects of matched uncertainties, while the PEA hysteresis, creep, and external load can be represented by a lumped matched uncertainty based on the developed model. To solve the chattering and steady-state problems, associated with the ideal SM control and the SM control with boundary layer (SMCBL), the novel PIDSM control developed in the present study replaces the switching control term in the ideal SM control schemes with a PID regulator. Experiments were carried out on a commercially-available PEA and the results obtained illustrate the effectiveness of the PIDSM controller, and its superiorities over other schemes of PID control, ideal SM control, and the SMCBL in terms of steady state error elimination, chattering suppression, and tracking error suppression. Secondly, a PIDSM observer was also developed based on the model of PEAs to provide the PIDSM controller with state estimates of the PEA. And the PIDSM controller and the PIDSM observer were combined to form an integrated control scheme (PIDSM observer-controller or PIDSMOC) for PEAs. The effectiveness of the PIDSM observer and the PIDSMOC were also validated experimentally. The superiority of the PIDSMOC over the PIDSM controller with σ-β filter control scheme was also analyzed and demonstrated experimentally. The significance of this research lies in the development of novel models for PEAs and PDSS actuators, which can be of great help in the design and control of such actuators. Also, the development of the PIDSM controller, the PIDSM observer, and their integrated form, i.e., PIDSMOC, enables the improved performance of tracking control of PEAs with the presence of various nonlinear or difficult-to-model effects

    Direct Adaptive Control of Systems with Actuator Failures: State of the Art and Continuing Challenges

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    In this paper, the problem of controlling systems with failures and faults is introduced, and an overview of recent work on direct adaptive control for compensation of uncertain actuator failures is presented. Actuator failures may be characterized by some unknown system inputs being stuck at some unknown (fixed or varying) values at unknown time instants, that cannot be influenced by the control signals. The key task of adaptive compensation is to design the control signals in such a manner that the remaining actuators can automatically and seamlessly take over for the failed ones, and achieve desired stability and asymptotic tracking. A certain degree of redundancy is necessary to accomplish failure compensation. The objective of adaptive control design is to effectively use the available actuation redundancy to handle failures without the knowledge of the failure patterns, parameters, and time of occurrence. This is a challenging problem because failures introduce large uncertainties in the dynamic structure of the system, in addition to parametric uncertainties and unknown disturbances. The paper addresses some theoretical issues in adaptive actuator failure compensation: actuator failure modeling, redundant actuation requirements, plant-model matching, error system dynamics, adaptation laws, and stability, tracking, and performance analysis. Adaptive control designs can be shown to effectively handle uncertain actuator failures without explicit failure detection. Some open technical challenges and research problems in this important research area are discussed
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