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This paper tackles the distributed leader–follower cooperative control problem for networked heterogeneous unmanned aerial vehicle–unmanned ground vehicle (UAV‐UGV) systems in unknown environments requiring formation keeping, obstacle avoidance, inter‐robot collision avoidance, and reliable robot communications. To adopt various formations, we design a novel negative imaginary (NI) switching formation protocol with a directed dynamic topology. To prevent an inter‐mobile robot collision, a new method to formulate the virtual propulsive force between robots is employed. To avoid unexpected obstacles, a new obstacle avoidance technique that allows the UGVs' formation to change its shape and the UGVs' roles is developed. To determine each UGV robot's order in obstacle avoidance formation, a quadrotor UAV, controlled by a strictly negative imaginary controller involving good wind resistance characteristics, tracks the center of formation shape to guarantee the maintaining visibility for multi‐robot systems on the ground. The proposed control system's efficacy is investigated through a rigorously comparative study with other control techniques, namely, the performance of artificial potential field and an NI obstacle avoidance strategy using the switching formation control method without switching topology. Finally, we also conduct a stability analysis of the closed‐loop control system using the NI‐systems theory. [ABSTRACT FROM AUTHOR]

The acquisition of a high‐quality imaging performance by an atomic force microscope is significantly influenced by the motion coupling effect of its key scanning unit, i.e. its piezoelectric tube scanner. In this Letter, to improve its performance, a MIMO model predictive control scheme for reducing this effect is proposed. The proposed controller achieves this by greatly overcoming the problem of tilted characters in the atomic force microscopy (AFM) scanned images. The experimental results are demonstrating the effectiveness of the proposed control technique. [ABSTRACT FROM AUTHOR]

Abstract: In most nanotechnology applications, speed and precision are important requirements for obtaining good topographical maps of material surfaces using atomic force microscopes (AFMs), many of which use piezoelectric tube scanners (PTSs) for scanning and positioning at nanometric resolutions. For control engineers, the PTS is particularly interesting since its ability to enable the AFM to undertake 3D imaging is entirely dependent upon the use of a feedback loop. However, it suffers from various intrinsic problems that degrade its positioning performance, such as: (i) lightly damped low‐frequency resonant modes due to its mechanical structure; (ii) nonlinear behavior due to hysteresis and creep; (iii) the cross‐coupling effect between its axes (in 3D positioning systems such as AFMs); and (iv) effect of thermal drift. This article presents a survey of the literature on the PTS, an overview of a few existing innovative solutions for its nanopositioning and future research directions. This article will help the reader to walk around the present development of the PTS aimed at meeting the requirements for high‐speed AFM imaging. [ABSTRACT FROM AUTHOR]

This paper presents a systematic approach to the design of a nonlinear robust dynamic state feedback controller for nonlinear uncertain systems using copies of the plant nonlinearities. The technique is based on the use of integral quadratic constraints and minimax linear quadratic regulator control, and uses a structured uncertainty representation. The approach combines a linear state feedback guaranteed cost controller and copies of the plant nonlinearities to form a robust nonlinear controller with a novel control architecture. A nonlinear state feedback controller is designed for a synchronous machine using the proposed method. The design provides improved stability and transient response in the presence of uncertainty and nonlinearity in the system and also provides a guaranteed bound on the cost function. An automatic voltage regulator to track reference terminal voltage is also provided by a state feedback equivalent robust nonlinear proportional integral controller. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a finite horizon H ∞ control problem is solved for a class of linear quantum systems using a dynamic game approach for the case of sampled-data measurements. The methodology adopted involves an equivalence between the quantum problem and two auxiliary classical problems. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We consider classical estimators for a class of physically realizable linear quantum systems. Optimal estimation using a complex Kalman filter for this problem has been previously explored. Here, we study robust H ∞ estimation for uncertain linear quantum systems. The estimation problem is solved by converting it to a suitably scaled H ∞ control problem. The solution is obtained in the form of two algebraic Riccati equations. Relevant examples involving dynamic squeezers are presented to illustrate the efficacy of our method. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The negative imaginary (NI) property occurs in many important applications. For instance, flexible structure systems with collocated force actuators and position sensors can be modelled as negative imaginary systems. In this study, a data‐driven controller synthesis methodology for NI systems is presented. In this approach, measured frequency response data of the plant is used to construct the controller frequency response at every frequency by minimising a cost function. Then, this controller response is used to identify the controller transfer function using system identification methods. [ABSTRACT FROM AUTHOR]

This paper presents a scheme for the design of a robust fixed-lag smoother for a class of nonlinear uncertain systems. The proposed approach combines a nonlinear robust estimator with a stable fixed-lag smoother, to improve the estimation error covariance. The robust fixed-lag smoother is based on the use of integral quadratic constraints and minimax linear quadratic regulator estimation and control theory. The state estimator uses a copy of the system nonlinearity in the estimator and combines an approximate model of the delayed states to produce a smoother signal. Also in this work, a characterization of the delay approximation error is presented, and the corresponding integral quadratic constraint is included in the design, which gives a guaranteed bound on the performance cost function. In order to see the effectiveness of the method, it is applied to a quantum optical phase estimation problem. Results show a significant improvement in the error covariance of the estimator when compared with a robust nonlinear filter. [ABSTRACT FROM AUTHOR]

Nanotechnology is an area of modern science which deals with the control of matter at dimensions of 100 nm or less. In recent years, of all the available microscopy techniques, atomic force microscopy (AFM) has proven to be extremely versatile as an investigative tool in this field. However the performance of AFM is significantly limited by the effects of hysteresis, creep, cross-coupling, and vibration in its scanning unit, the piezoelectric tube scanner (PTS). This article presents the design and experimental implementation of a single-input single-output (SISO) model predictive control (MPC) scheme with a vibration compensator which is based on an identified model of the PTS. The proposed controller provides an AFM with the capability to achieve improved tracking and results in compensation of the nonlinear effects. The experimental results, which compare the tracking performances of the proposed controller for different reference signals, highlight the usefulness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

ABSTRACT A systematic approach to design a nonlinear controller using minimax linear quadratic Gaussian regulator ( LQG) control is proposed for a class of multi-input multi-output nonlinear uncertain systems. In this approach, a robust feedback linearization method and a notion of uncertain diffeomorphism are used to obtain an uncertain linearized model for the corresponding uncertain nonlinear system. A robust minimax LQG controller is then proposed for reference command tracking and stabilization of the nonlinear system in the presence of uncertain parameters. The uncertainties are assumed to satisfy a certain integral quadratic constraint condition. In this method, conventional feedback linearization is used to cancel nominal nonlinear terms and the uncertain nonlinear terms are linearized in a robust way. To demonstrate the effectiveness of the proposed approach, a minimax LQG-based robust controller is designed for a nonlinear uncertain model of an air-breathing hypersonic flight vehicle ( AHFV) with flexibility and input coupling. Here, the problem of constructing a guaranteed cost controller which minimizes a guaranteed cost bound has been considered and the tracking of velocity and altitude is achieved under inertial and aerodynamic uncertainties. [ABSTRACT FROM AUTHOR]

There is a need, in the wide ranging scientific community, to perform fast scans using an atomic force microscope (AFM) with nanoscale accuracy. The performance of an AFM at high scanning speeds is limited because of some serious limitations of its scanning unit; that is, the piezoelectric tube scanner (PTS). To increase the imaging speed of an AFM, a multi-input-multi-output (MIMO) model predictive control scheme is applied in the axes of the PTS to reduce its vibration and cross-coupling effect. The design of this controller is based on an identified MIMO model of the AFM PTS. Moreover, a damping compensator is designed and included in the feedback loop with the plant to suppress the vibration of the PTS at the resonant frequency. Consequently, the proposed controller achieves a higher closed-loop bandwidth, significant damping of the resonant mode of the AFM PTS and results in compensation of the above effects. To evaluate the performance improvement using the proposed control scheme, an experimental comparison of its results with those of the AFM in-built proportional-integral controller is performed. This comparison shows the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

SUMMARY This paper presents a new method to synthesize a decentralized state feedback robust H ∞ controller for a class of large-scale linear uncertain systems satisfying integral quadratic constraints. The decentralized controller is constructed by taking only block-diagonal elements of a nondecentralized state feedback controller and treating neglected off-diagonal blocks as uncertainties. A solution to this controller synthesis problem is given in terms of a stabilizing solution to a parametrized algebraic Riccati equation where the parameters are obtained using a differential evolution algorithm.Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This paper presents a new method to construct a decentralized nonlinear robust H ∞ controller for a class of large-scale nonlinear uncertain systems. The admissible uncertainties and nonlinearities in the system satisfy integral quadratic constraints and global Lipschitz conditions, respectively. The decentralized controller, which is required to be stable, is capable of exploiting known nonlinearities and interconnections between subsystems without treating them as uncertainties. Instead, additional uncertainties are introduced because of the discrepancies between nondecentralized and decentralized nonlinear output feedback controllers. The H ∞ control objective is to achieve an absolutely stable closed-loop system with a specified disturbance attenuation level. A solution to this control problem involves stabilizing solutions to algebraic Riccati equations parametrized by scaling constants corresponding to the uncertainties and nonlinearities. This formulation is nonconvex; hence, an evolutionary optimization method is applied to solve the control problem considered. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This paper presents an approach to discrete-time robust H∞ control for a class of nonlinear uncertain systems on the basis of the use of Sum Quadratic Constraints. The approach involves controllers, which include copies of the system nonlinearities in the controller. The nonlinearities being considered are those that satisfy a certain global Lipschitz condition. The linear part of the controller is synthesized using linear robust H∞ control theory, and this leads to a nonlinear controller, which gives an upper bound on the attainable disturbance attenuation level. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper develops a robust H∞ method for fast tracking position control problems arising in an atomic force microscope ( AFM). A commercial type NT- MDT AFM is used to generate 3D images of scanned material surfaces at high speeds and accuracies. A major component of this AFM is a piezoelectric tube actuator used for position control in three directions. Due to the nature of the piezoelectric actuator, there is nonlinear hysteresis present which affects the AFM scanning qualities. The original commercial AFM uses traditional proportional-integral-derivative position control and can only obtain good quality images for scanning rates under about 20 Hz in both the x and y directions. In this paper, a robust H∞ controller is designed based on a physical model of the AFM piezoelectric tube positioner in the x and y directions. On the electrical side of the positioning system, external capacitors are connected in series with the x and y contacts of the piezoelectric tube to provide measured voltages which are proportional to the charge on the actuator. The parameters for a nonlinear model are obtained from measurements of the system frequency response and time domain response. This model also takes into account the time delay resulting from the sensor electronics. This nonlinear model is represented as a linear uncertain system model with norm bounded uncertainty. The uncertain system model is used to design a robust H∞ tracking controller for the AFM scanning system. Experimental results show that the robust H∞ controller can improve the AFM scanning quality and increase the scanning speed significantly. The controller performs well in tracking a given reference scanning signal with frequencies up to 125 Hz. [ABSTRACT FROM AUTHOR]

This paper proposes a backup attitude estimation scheme for small fixed-wing unmanned aerial vehicles ( UAVs) in the event of gyroscopic failure. The attitude is propagated in terms of 3 degrees-of-freedom ( DoF) aircraft dynamics. The errors in attitude propagation are updated using indirect attitude information obtained from accelerations as sensed by onboard accelerometers and a global positioning system ( GPS) receiver. In the event of gyroscopic failure, large uncertainties are introduced into the attitude propagation model. Such uncertainties in states and parameters are modeled as norm-bound uncertainties and a discrete-time robust extended Kalman filter ( REKF) is implemented to estimate the attitude of the UAV. [ABSTRACT FROM AUTHOR]

For a class of multi-input and multi-output nonlinear uncertainty systems, a novel approach to design a nonlinear controller using minimax linear quadratic regulator (LQR) control is proposed. The proposed method combines a feedback linearization method with the robust minimax LQR approach in the presence of time-varying uncertain parameters. The uncertainties, which are assumed to satisfy a certain integral quadratic constraint condition, do not necessarily satisfy a generalized matching condition. The procedure consists of feedback linearization of the nominal model and linearization of the remaining nonlinear uncertain terms with respect to each individual uncertainty at a local operating point. This two-stage linearization process, followed by a robust minimax LQR control design, provides a robustly stable closed loop system. To demonstrate the effectiveness of the proposed approach, an application study is provided for a flight control problem of an air-breathing hypersonic flight vehicle (AHFV), where the outputs to be controlled are the longitudinal velocity and altitude, and the control variables are the throttle setting and elevator deflection. The proposed method is used to derive a linearized uncertainty model for the longitudinal motion dynamics of the AHFV first, and then a robust minimax LQR controller is designed, which is based on this uncertainty model. The controller is synthesized considering seven uncertain aerodynamic and inertial parameters. The stability and performance of the synthesized controller is evaluated numerically via single scenario simulations for particular cruise conditions as well as a Monte-Carlo type simulation based on numerous cases. It is observed that the control scheme proposed in this paper performs better, especially from the aspect of robustness to large ranges of uncertainties, than some controller design schemes previously published in the literature. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [ABSTRACT FROM AUTHOR]

The design of a multi-input-multi-output (MIMO) model predictive control (MPC) framework for reducing errors in images scanned by an atomic force microscope (AFM) is presented. To improve the damping capability of the proposed control framework, it is augmented with a damping compensator. The MIMO form of this control framework compensates the tilted natures of the scanned images by compensating the cross-coupling effect while its augmented damping compensator reduces the vibration effect by improving damping in the resonant mode of the AFM's piezoelectric tube scanner. Experimental results using the existing AFM proportional-integral controller and single-input-singleoutput MPC are also presented to show the effectiveness of the MIMO MPC controller. This Letter is an extension of an authors' earlier published work. [ABSTRACT FROM AUTHOR]