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Showing papers in "Asian Journal of Control in 2008"


Journal ArticleDOI
TL;DR: The main result is that if the adjacent topology of the graph is frequently connected then the consensus is achievable via local-information-based decentralized controls, provided that the linear dynamic mode is completely controllable.
Abstract: In this paper the consensus problem is considered for multi-agent systems, in which all agents have an identical linear dynamic mode that can be of any order. The main result is that if the adjacent topology of the graph is frequently connected then the consensus is achievable via local-information-based decentralized controls, provided that the linear dynamic mode is completely controllable. Consequently, many existing results become particular cases of this general result. In this paper, the case of fixed connected topology is discussed first. Then the case of switching connected topology is considered. Finally, the general case is studied where the graph topology is switching and only connected often enough. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

268 citations


Journal ArticleDOI
TL;DR: In this paper, the authors present new tuning rules for PI control of processes with essentially monotone step response that are typically encountered in process control, based on characterization of process dynamics by three parameters that can be obtained from a step response experiment.
Abstract: This paper presents new tuning rules for PIcontrol of processes with essentially monotone step response that aretypically encountered in process control. The rules are based oncharacterization of process dynamics by three parameters that can beobtained from a step response experiment. The rules are obtained bymaximizing integral gain subject to a constraint on themaximum sensitivity. They are almost as simple as theZiegler-Nichols tuning rules but they give substantially betterperformance.

264 citations


Journal ArticleDOI
TL;DR: In this article, the authors focus on a Lyapunov function (CLF) variation of Sontag's formula, which also results from a special choice of parameters in the so-called pointwise min-norm formulation.
Abstract: Two well known approaches to nonlinear control involve the use of control Lyapunov functions (CLFs) and receding horizon control (RHC), also known as model predictive control (MPC). The on-line Euler-Lagrange computation of receding horizon control is naturally viewed in terms of optimal control, whereas researchers in CLF methods have emphasized such notions as inverse optimality. We focus on a CLF variation of Sontag's formula, which also results from a special choice of parameters in the so-called pointwise min- norm formulation. Viewed this way, CLF methods have direct connections with the Hamilton-Jacobi-Bellman formulation of optimal control. A single example is used to illustrate the various limitations of each approach. Finally, we contrast the CLF and receding horizon points of view, arguing that their strengths are complementary and suggestive of new ideas and opportunities for control design. The presentation is tutorial, emphasizing concepts and connec- tions over details and technicalities.

254 citations


Journal ArticleDOI
TL;DR: This paper uses computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad and presents a new estimation scheme for solving the differential case, linear, numerically robust, and computationally inexpensive hence suitable for real‐time implementation.
Abstract: In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.

254 citations


Journal ArticleDOI
TL;DR: In this article, a method of smooth sliding mode control design is presented to provide for an asymptotic second-order sliding mode on the selected sliding surface in the presence of unknown disturbances and discrete-time control update.
Abstract: Presented is a method of smooth sliding mode control design to provide for an asymptotic second-order sliding mode on the selected sliding surface. The control law is a nonlinear dynamic feedback that in absence of unknown disturbances provides for an asymptotic second-order sliding mode. Application of the second-order disturbance observer in a combination with the proposed continuous control law practically gives the second-order sliding accuracy in presence of unknown disturbances and discrete-time control update. The piecewise constant control feedback is “smooth” in the sense that its derivative numerically taken at sampling rate does not contain high frequency components. A numerical example is presented.

246 citations


Journal ArticleDOI
TL;DR: The literature of the last two decades contains many important advances in the control of flexible joint robots as mentioned in this paper, and a survey of these advances and an assessment for future developments is provided.
Abstract: The robotics literature of the last two decades contains many important advances in the control of flexible joint robots. This is a survey of these advances and an assessment for future developments, concentrated mostly on the control issues of flexible joint robots.

150 citations


Journal ArticleDOI
TL;DR: A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems, and extensions are discussed to force control, backstepping control, and output feedback control, where dynamic nonlinear nets are required.
Abstract: A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems. These structures possess a universal approximation property that allows them to be used in feedback control of unknown systems without requirements for linearity in the system parameters or finding a regression matrix. Nonlinear nets can be linear or nonlinear in the tunable weight parameters. In the latter case weight tuning algorithms are not straightforward to obtain. Feedback control topologies and weight tuning algorithms are given here that guarantee closed-loop stability and bounded weights. Extensions are discussed to force control, backstepping control, and output feedback control, where dynamic nonlinear nets are required.

140 citations


Journal ArticleDOI
TL;DR: In this paper, the geometric structure of receding horizon control (RHC) of linear, discrete-time systems, subject to a quadratic performance index and linear constraints, is investigated.
Abstract: This paper characterises the geometric structure of receding horizon control (RHC) of linear, discrete-time systems, subject to a quadratic performance index and linear constraints. The geometric insights so obtained are exploited to derive a closed-form solution for the case where the total number of constraints is less than or equal to the number of degrees of freedom, represented by the number of control moves. The solution is shown to be a partition of the state space into regions for which an analytic expression is given for the corresponding control law. Both the regions and the control law are characterised in terms of the parameters of the open-loop optimal control problem that underlies RHC and can be computed off line. The solution for the case where the total number of constraints is greater than the number of degrees of freedom is addressed via an algorithm that iteratively uses the off-line solution and avoids on-line optimisation.

136 citations


Journal ArticleDOI
TL;DR: In this article, the authors investigate the problem of controlling a group of mobile autonomous agents to track multiple virtual leaders with varying velocities in the sense that agents with the same virtual leader attain the same velocity and track the corresponding leader.
Abstract: Many tracking problems in flocking are related to a single (virtual) leader with a constant velocity. In this paper, we investigate the problem of controlling a group of mobile autonomous agents to track multiple virtual leaders with varying velocities in the sense that agents with the same virtual leader attain the same velocity and track the corresponding leader. We propose a provably-stable flocking algorithm. Moreover, we show that the position and velocity of the center of the mass of all agents will exponentially converge to weighted average position and velocity of the virtual leaders. Numerical simulations are worked out to illustrate theoretical results. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

124 citations


Journal ArticleDOI
TL;DR: This paper addresses stabilization of switched linear control systems with unstabilizable individual switching models via a controllable switching strategy and stabilization by both controls and switching laws is investigated.
Abstract: This paper addresses stabilization of switched linear control systems with unstabilizable individual switching models. First we consider the stabilization of switched systems via a controllable switching strategy. Then stabilization by both controls and switching laws is investigated. Certain sufficent conditions are obtained. ABSTRACT

112 citations


Journal ArticleDOI
TL;DR: An inversion-based feedback/feedforward control approach is applied to overcome positioning problems that limit the operating speed of current AFM systems, and the efficacy of the method is experimentally evaluated by applying it to image collagen samples.
Abstract: This article considers the precision positioning problem associated with high-speed operation of the Atomic Force Microscope (AFM), and presents an inversion-based control approach to achieve precision positioning. Although AFMs have high (nanoscale) spatial resolution, a problem with current AFM systems is that they have low temporal resolution, i.e., AFM imaging is slow. In particular, current AFM imaging cannot be used to provide three-dimensional, time-lapse images of fast processes when imaging relatively-large, soft samples. For instance, current AFM imaging of living cells takes 1-2 minutes (per image frame) - such imaging speeds are too slow to study rapid biological processes that occur in seconds, e.g., to investigate the rapid movement of cells or the fast dehydration and denaturation of collagen. This inability, to rapidly image fast biological processes, motivates our current research to increase the operating speed of the AFM. We apply an inversion-based feedback/feedforward control approach to overcome positioning problems that limit the operating speed of current AFM systems. The efficacy of the method, to achieve high-speed AFM operation, is experimentally evaluated by applying it to image collagen samples.

Journal ArticleDOI
TL;DR: Through the study, iterative learning control is shown to be the one best suited for learning unknown time functions of known period and it is shown for the first time that an iterativeLearning control is directly applicable to systems described by nonlinear partial differential equation.
Abstract: Model-based learning control of nonlinear systems is studied. Two types of learning algorithms, described by differential equations and/or difference equations to learn unknown time functions, are designed and compared using the Lyapunov’s direct method. The time functions to be learned are classified into several classes according to their properties such as continuity, periodicity, and value at the origin of the state space. Conditions are found for iterative learning controls to achieve asymptotic stability and asymptotic learning convergence. For a comparative study, learning capability of a control is defined and, using the criterion, other model-based controls with learning capability such as adaptive controls and robust controls are investigated. Through the study, iterative learning control is shown to be the one best suited for learning unknown time functions of known period. Finally, it is shown for the first time that an iterative learning control is directly applicable to systems described by nonlinear partial differential equation.

Journal ArticleDOI
TL;DR: In this paper, the stability properties of linear switched systems consisting of both Hurwitz stable and unstable subsystems are investigated by using piecewise Lyapunov functions incorporated with an average dwell time approach.
Abstract: The stability properties of linear switched systems consisting of both Hurwitz stable and unstable subsystems are investigated by using piecewise Lyapunov functions incorporated with an average dwell time approach. It is shown that if the average dwell time is chosen sufficiently large and the total activation time ratio between Hurwitz stable and unstable subsystems is not smaller than a specified constant, then exponential stability of a desired degree is guaranteed. The above result is also extended to the case where nonlinear norm-bounded perturbations exist.

Journal ArticleDOI
TL;DR: In this article, the stability conditions of linear uncertain systems with time-varying delay are derived based on a generalized discretized Lyapunov functional approach, and the kernel of the functional, which is a function of two variables, is chosen as piecewise linear.
Abstract: This paper investigates the stability of linear uncertain systems with time-varying delay. Stability criteria are derived based on a generalized discretized Lyapunov functional approach. The kernel of the functional, which is a function of two variables, is chosen as piecewise linear. The stability conditions are written in the form of linear matrix inequalities. Numerical examples indicate significant improvements over the existing results.

Journal ArticleDOI
TL;DR: In this paper, the problem of stability and robust control for both certain and uncertain continuous-time singular systems with state delay is considered, and robust delay-dependent stability criteria and linear memoryless state feedback controllers based on linear matrix inequality are obtained.
Abstract: This paper deals with the problem of stability and robust control for both certain and uncertain continuous-time singular systems with state delay. Systems with norm-bounded parameter uncertainties are considered. Robust delay-dependent stability criteria and linear memoryless state feedback controllers based on linear matrix inequality are obtained. By choosing some Lyapunov-Krasovskii functionals, neither model transformation nor bounding for cross terms is required in the derivation of our delay-dependent results. Finally, numerical example is provided to illustrate the effectiveness of the proposed method.

Journal ArticleDOI
TL;DR: This paper is concerned with control applications over lossy data networks, and the discrete‐time linear quadratic Gaussian (LQG) optimal control problem is considered.
Abstract: This paper is concerned with control applications over lossy data networks. Sensor data is transmitted to an estimation-control unit over a network, and control commands are issued to subsystems over the same network. Sensor and control packets may be randomly lost according to a Bernoulli process. In this context, the discrete-time linear quadratic Gaussian (LQG) optimal control problem is considered. It is known that in the scenario described above, and for protocols for which there is no acknowledgment of successful delivery of control packets (e.g. UDP-like protocols), the LQG optimal controller is in general nonlinear. However, the simplicity of a linear sub-optimal solution is attractive for a variety of applications. Accordingly, this paper characterizes the optimal linear static controller and compares its performance to the case when there is acknowledgment of delivery of packets (e.g. TCP-like protocols). Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

Journal ArticleDOI
TL;DR: In this article, the authors present an analysis of the Ziegler-Nichols frequency response method for tuning PI controllers, showing that this method has severe limitations and can be overcome by a simple modification for processes where the time delay is not too short.
Abstract: This paper presents an analysis of the Ziegler-Nichols frequency response method for tuning PI controllers, showing that this method has severe limitations. The limitations can be overcome by a simple modification for processes where the time delay is not too short. By a major modification it is possible to obtain new tuning rules that also cover processes that are lag dominated.

Journal ArticleDOI
TL;DR: In this paper, a survey of recent and historical publications on automotive powertrain control is presented, and a comprehensive list of references is provided, as well as a comprehensive review of the most relevant technologies.
Abstract: This paper surveys recent and historical publications on automotive powertrain control. Control-oriented models of gasoline and diesel engines and their aftertreatment systems are reviewed, and challenging control problems for conventional engines, hybrid vehicles and fuel cell powertrains are discussed. Fundamentals are revisited and advancements are highlighted. A comprehensive list of references is provided.

Journal ArticleDOI
TL;DR: In this paper, the fault detection observer design problem in finite frequency domain for linear time-invariant continuous-time systems with bounded disturbances is considered and two finite frequency performance indexes are introduced to measure the fault sensitivity and the disturbance robustness.
Abstract: This paper deals with the fault detection observer design problem in finite frequency domain for linear time-invariant continuous-time systems with bounded disturbances. Two finite frequency performance indexes are introduced to measure the fault sensitivity and the disturbance robustness. Faults are considered in the low frequency domain while disturbances are considered in certain finite frequency domain. With the aid of the Generalized Kalman-Yakubovich-Popov lemma, the design methods are presented in terms of solutions to a set of linear matrix inequalities. An example of the VTOL aircraft is studied to illustrate the effectiveness of the proposed method.

Journal ArticleDOI
TL;DR: In this paper, an improved delay-dependent condition guaranteeing that a stochastic delay system will be exponentially stable in the mean square is proposed, which is less conservative than existing ones in the literature.
Abstract: This paper studies robust stability for a class of uncertain nonlinear stochastic time-delay systems. In terms of a linear matrix inequality, an improved delay-dependent condition guaranteeing that a stochastic delay system will be exponentially stable in the mean square is proposed. This condition is less conservative than existing ones in the literature and is demonstrated by means of an example.

Journal ArticleDOI
TL;DR: In this paper, the infinite horizon linear quadratic optimal control for discrete-time stochastic systems with both state and controldependent noise is studied under assumption of stabilization and exact observability.
Abstract: This paper is concerned with the infinite horizon linear quadratic optimal control for discrete-time stochastic systems with both state and controldependent noise. Under assumptions of stabilization and exact observability, it is shown that the optimal control law and optimal value exist, and the properties of the associated discrete generalized algebraic Riccati equation (GARE) are also discussed.

Journal ArticleDOI
TL;DR: In this article, an adaptive version of the controller is presented to compensate the parameter perturbation when the perturbed parameters satisfy a suitable matching condition, and the proposed method is applied to the excitation control problem for power systems.
Abstract: This paper deals with the problem of L2 disturbance attenuation for Hamiltonian systems. We first show that the L2 gain from the disturbance to a penalty signal may be reduced to any given level if the penalty signal is defined properly. Then, an adaptive version of the controller will be presented to compensate the parameter perturbation. When the perturbed parameters satisfy a suitable matching condition, it is easy to introduce the adaptive mechanism to the controller. Another contribution of this paper is to apply the proposed method to the excitation control problem for power systems. An adaptive L2 controller for the power system is designed using the proposed method and a simulation result with the proposed controller is given.

Journal ArticleDOI
TL;DR: A variant of k Bipartite Neighbors, called k‐BN2, is introduced, which combines local linear models and the global nonlinear model to predict the value of the novel instance of the bipartite neighborhood.
Abstract: This paper introduces a variant of k Bipartite Neighbors (k-BN), called k-BN2, for use in function prediction. Like k-BN, k-BN2 selects k instances surrounding the query, i.e., the novel instance, and keeps them bipartitely. However, in order to improve the prediction precision, based on the bipartite neighborhood, k-BN2 combines local linear models and the global nonlinear model to predict the value of the novel instance. Applied to two real measured datasets, k-BN2 outperforms the typical k-BN and those methods in which kBN or a related approximate physical model alone is exploited.

Journal ArticleDOI
TL;DR: A robust controller design method is first formulated to deal with both performance and robust stability specifications for multivariable processes and a PID approximation method is proposed to reduce a high‐order controller.
Abstract: In this paper, a robust controller design method is first formulated to deal with both performance and robust stability specifications for multivariable processes. The optimum problem is then dealt with using a loop-shaping H∞ approach, which gives a sub-optimal solution. Then a PID approximation method is proposed to reduce a high-order controller. The whole procedure involves selecting several parameters and the computation is simple, so it serves as a PID tuning method for multivariable processes. Examples show that the method is easy to use and the resulting PID settings have good time-domain performance and robustness.

Journal ArticleDOI
TL;DR: In this article, the authors investigated iterative learning control for non-minimum phase systems from a novel viewpoint and showed that ILC using an adjoint system achieves the desired input defined by stable inversion.
Abstract: In this paper, we investigate iterative learning control (ILC) for non-minimum phase systems from a novel viewpoint. For non-minimum phase systems, the magnitude of a desiredinput obtained by ILC using forward-time updating and Silverman's inversion are too large because of the influence of the unstable zeros. On the other hand, stable inversion constructs a bounded desired input by using non-causal inverse for non-minimum phase systems. In this paper, we first clarify that ILC using an adjoint system achieves the desired input defined by stable inversion. Hence, ILC using an adjoint system is an effective method for the control of non-minimum phase systems with uncertainty. However, a useful convergence condition of ILC using an adjoint system was not achieved. Next, we develop a simple convergence condition in the frequency domain.

Journal ArticleDOI
TL;DR: The authors use a neural computing technique, based on a mathematical model of amygdala and the limbic system, for emotional control of the washing machine, and the obtained results indicate the applicability of the proposed techniques in this important business sector.
Abstract: Intelligent control of home appliances has, in recent years, attracted much theoretical attention, as well as becoming a major factor for industrial and economic success and rapid market penetration. Washing Machines represent an important market. Intelligent control techniques are capable of providing useful means for both easier use and energy and water conservation. In this paper, the authors use two techniques that have successfully been used in other intelligent modeling and control applications. Firstly, the authors use a neuro-fuzzy locally linear model tree system for data driven modeling of the machine. Secondly, the authors use a neural computing technique, based on a mathematical model of amygdala and the limbic system, for emotional control of the washing machine. The obtained results indicate the applicability of the proposed techniques in this important business sector.

Journal ArticleDOI
TL;DR: In this article, the authors pre-sent the design and implementation of a two-degree-of-freedom (2DOF)-controller to accomplish topography measurements at high scan-rates with reduced measurement error.
Abstract: The performance of an atomic force microscope (AFM) is improved substantially by utilizing modern model-based control methods in compari-son to a standard proportional-integral (PI) controlled AFM system. We pre-sent the design and implementation of a two-degree-of-freedom (2DOF)- controller to accomplish topography measurements at high scan-rates with reduced measurement error. An H∞–controller operates the AFM system in a closed loop while a model-based feedforward controller tracks the scanner to the last recorded scan-line. Experimental results compare the actual per-formance of the standard PI-controlled AFM and the 2DOF controlled system. The new controller reduces the control error considerably and enables imag-ing at higher speeds and at weaker tip-sample interaction forces. KeyWords: Nanotechnology, fast scanning, AFM, robust control, scanning probe. I. INTRODUCTION The topography of a nano-scale specimen can be imaged using an atomic force microscope (AFM) by tracing the surface with a probing tip supported on a mi-cro-mechanical cantilever [1]. The spatially resolved topography is measured by laterally scanning of the sample under the probing tip. A piezoelectric tube scan-ner (piezo scanner), capable of moving in all three spa-tial directions, is used as actuator [2]. The deflection of the cantilever due to the sample topography can be monitored by an optical lever (e.g. [3]) and a segmented photo diode (Fig. 1). For a detailed description of the function of the AFM and its components we refer to [1] and [4]. In the constant force mode, also referred to as “contact mode”, the tip-sample interaction force is held constant in a closed loop-operation (e.g. [1,5]). The can-tilever deflection depends on the tip-sample interaction force and is tracked to a predetermined setpoint value by varying the position of the sample along the Z-direction,

Journal ArticleDOI
TL;DR: In this article, the authors proposed improved delay-dependent conditions for the robust stability and robust stabilization of discrete time-delay systems with norm-bounded parameter uncertainties, and theoretically established that the proposed conditions are less conservative than those discussed in the literature.
Abstract: This paper provides improved delay-dependent conditions for the robust stability and robust stabilization of discrete time-delay systems with norm-bounded parameter uncertainties. It is theoretically established that the proposed conditions are less conservative than those discussed in the literature. The new approach proposed in this paper in a derivation of delay-dependent conditions and involves the use of neither model transformation nor bounding techniques for some cross terms. A numerical example is provided to demonstrate the reduced conservatism of the proposed conditions.

Journal ArticleDOI
TL;DR: In this paper, the authors considered the problem of robust stability and robust stabilization for uncertain continuous singular systems with multiple time-varying delays, where the parametric uncertainty is assumed to be norm bounded.
Abstract: This paper deals with the problem of robust stability and robust stabilization for uncertain continuous singular systems with multiple time-varying delays. The parametric uncertainty is assumed to be norm bounded. The purpose of the robust stability problem is to give conditions such that the uncertain singular system is regular, impulse free, and stable for all admissible uncertainties. The purpose of the robust stabilization problem is to design a feedback control law such that the resulting closed-loop system is robustly stable. This problem is solved via generalized quadratic stability approach. A strict linear matrix inequality (LMI) design approach is developed. Finally, a numerical example is provided to demonstrate the application of the proposed method.

Journal ArticleDOI
TL;DR: In this article, the authors consider a gradient climbing problem where the objective is to steer a group of vehicles to the extrema of an unknown scalar field distribution while keeping a prescribed formation, where the leader vehicle performs extremum seeking for the minima or maxima of the field, and other vehicles follow according to passivity-based coordination rules.
Abstract: We consider a gradient climbing problem where the objective is to steer a group of vehicles to the extrema of an unknown scalar field distribution while keeping a prescribed formation. We address this problem by developing a scheme in which the leader performs extremum seeking for the minima or maxima of the field, and other vehicles follow according to passivity-based coordination rules. The extremum-seeking approach generates approximate gradients of the field locally by “dithering” sensor positions. We show that if there is sufficient time-scale separation between the fast dither and slow gradient motions of the leader vehicle, the followers only respond to the gradient motion, and filter out the dither component. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society