A control system to aid mobility is presented that is intended to assist living independently and that provides physical guidance. The system has two levels: a human machine interface and an adaptive shared controller.
Volkov, Vasily Y; Zhuravlev, Oleg N; Nukhaev, Marat T; Shchelushkin, Roman V
This article presents the idea and realization for the unique Adaptive Inflow Control System being a part of well completion, able to adjust to the changing in time production conditions. This system allows to limit the flow rate from each interval at a certain level, which solves the problem of water and gas breakthroughs. We present the results of laboratory tests and numerical calculations obtaining the characteristics of the experimental setup with dual-in-position valves as parts of adaptive inflow control system, depending on the operating conditions. The flow distribution in the system was also studied with the help of three-dimensional computer model. The control ranges dependences are determined, an influence of the individual elements on the entire system is revealed.
WANG Yi-jing; WANG Long
The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied. The switching law is determined by the output predictive errors of a finite number of subsystems. For the single subsystem and multiple subsystems cases, it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system. This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.
Frost, Susan A.; Balas, Mark J.
We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.
Akira Inoue; Ming-Cong Deng
This paper presents a framework of a combined adaptive and non-adaptive attitude control system for a helicopter experimental system. The design method is based on a combination of adaptive nonlinear control and non-adaptive nonlinear control. With regard to detailed attitude control system design, two schemes are shown for different application cases.
Lemos, João M; Igreja, José M
This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts
Optimal adaptive automatic control system for gas producing wells cluster is proposed intended for solving the problem of stabilization of the output gas pressure in the cluster at conditions of changing gas flow rate and changing parameters of the wells themselves, providing the maximum high resource of hardware elements of automation
Variations in systems dynamics and modeling uncertainty(due to unmodeled systems behavior and/or presence of disturbances),have posed significant challenges to the effective luminosity and orbit control in accelerators.Problems of similar nature occur in a wide variety of other applications from chemical processes to power plants to financial systems.Adaptive control has long been pursued as a possible solution,but difficulties with online model identification and robust implementation of the adaptive control algorithms has prevented their widespread application.In general developing and maintaining appropriate models is the key to the success of any deployed control solution.Meanwhile the performance of the control system is contingent on the responsiveness of the control algorithm to the inevitable deviations of the model from the actual system.This project uses neural networks to detect significant changes in system behavior,and develops an optimal model-predictive-based adaptive control algorithm that enables the robust implementation of an effective control strategy that is applicable in a wide range of applications.Simulation studies were conducted to clearly demonstrate the feasibility and benefits of implementing model predictive control technology in accelerator control problems.The requirements for an effective commercial product that can meet the challenge of optimal model-predictive-based adaptive control technology were developed.A prototype for the optimal model-predictive-based adaptive control algorithm was developed for a well-known nonlinear temperature control problem for gas-phase reactors that proved the feasibility of the proposed approach.This research enables a commercial party to leverage the knowledge gained through collaboration with a national laboratory to develop new system identification and optimal model-predictive-based adaptive control software to address current and future challenges in process industries,power systems
In light of the complex and highly uncertain nature of dynamical systems requiring controls, it is not surprising that reliable system models for many high performance engineering and life science applications are unavailable. In the face of such high levels of system uncertainty, robust controllers may unnecessarily sacrifice system performance whereas adaptive controllers are clearly appropriate since they can tolerate far greater system uncertainty levels to improve system performance. In this dissertation, we develop a Lyapunov-based direct adaptive and neural adaptive control framework that addresses parametric uncertainty, unstructured uncertainty, disturbance rejection, amplitude and rate saturation constraints, and digital implementation issues. Specifically, we consider the following research topics; direct adaptive control for nonlinear uncertain systems with exogenous disturbances; robust adaptive control for nonlinear uncertain systems; adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints; adaptive reduced-order dynamic compensation for nonlinear uncertain systems; direct adaptive control for nonlinear matrix second-order dynamical systems with state-dependent uncertainty; adaptive control for nonnegative and compartmental dynamical systems with applications to general anesthesia; direct adaptive control of nonnegative and compartmental dynamical systems with time delay; adaptive control for nonlinear nonnegative and compartmental dynamical systems with applications to clinical pharmacology; neural network adaptive control for nonlinear nonnegative dynamical systems; passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems; neural network adaptive dynamic output feedback control for nonlinear nonnegative systems using tapped delay memory units; Lyapunov-based adaptive control framework for discrete-time nonlinear systems with exogenous disturbances
Thor I. Fossen
Full Text Available The problem of controlling underwater mobile robots in 6 degrees of freedom (DOF is addressed. Uncertainties in the input matrix due to partly known nonlinear thruster characteristics are modeled as multiplicative input uncertainty. This paper proposes two methods to compensate for the model uncertainties: (1 an adaptive passivity-based control scheme and (2 deriving a hybrid (adaptive and sliding controller. The hybrid controller consists of a switching term which compensates for uncertainties in the input matrix and an on-line parameter estimation algorithm. Global stability is ensured by applying Barbalat's Lyapunovlike lemma. The hybrid controller is simulated for the horizontal motion of the Norwegian Experimental Remotely Operated Vehicle (NEROV.
Presents an adaptive controller for continuous systems with unknown deadzones and known linear part which consists of an adaptive deadzone inverse to cancel the effects of deadzone and a linear-like control law to track the system output. It concludes from simulation results that this control possesses good robustness and improves the tracking performance of the system.
Yudong Li; Tianyu Zhang; Yujun Zhang
This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.
Full Text Available This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.
Hidetoshi Oya; Daisuke Yamasaki; Shunya Nagai; Kojiro Hagino
We present a new adaptive gain robust controller for polytopic uncertain systems. The proposed adaptive gain robust controller consists of a state feedback law with a fixed gain and a compensation input with adaptive gains which are tuned by updating laws. In this paper, we show that sufficient conditions for the existence of the proposed adaptive gain robust controller are given in terms of LMIs. Finally, illustrative examples are presented to show the effectiv...
Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)
An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.
Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.
Jin J; Allison B.Z.; Sellers E.W.; Brunner & C.; Horki P.; Wang X; Neuper C.
An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e., 12 columns and 7 rows). The 9- and 14-flash A & B paradigms present all items of the 12 × 7 matrix three times using either nine or 14 flashes (instead of 19), decreasi...
SATOH, YASUYUKI; Nakamura, Hisakazu; Katayama, Hitoshi; Nishitani, Hirokazu
In this article, we proposed an adaptive inverse optimal controller for the magnetic levitation system. First, we designed an inverse optimal controller with a pre-feedback gravity compensator and applied it to the magnetic levitation system. However, this controller cannot guarantee any stability margin. We demonstrated that the controller did not work well (offset error remained) in the experiment. Hence, we proposed an improved controller via an adaptive control technique to guarantee the ...
Juntao Fei; Hongfei Ding
This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...
Dimino, I.; Concilio, A.; Schueller, M.; Gratias, A.
A key technology to enable morphing aircraft for enhanced aerodynamic performance is the design of an adaptive control system able to emulate target structural shapes. This paper presents an approach to control the shape of a morphing wing by employing internal, integrated actuators acting on the trailing edge. The adaptive-wing concept employs active ribs, driven by servo actuators, controlled in turn by a dedicated algorithm aimed at shaping the wing cross section, according to a pre-defined geometry. The morphing control platform is presented and a suitable control algorithm is implemented in a dedicated routine for real-time simulations. The work is organized as follows. A finite element model of the uncontrolled, non-actuated structure is used to obtain the plant model for actuator torque and displacement control. After having characterized and simulated pure rotary actuator behavior over the structure, selected target wing shapes corresponding to rigid trailing edge rotations are achieved through both open-loop and closed-loop control logics.
Mekel, R.; Nachmias, S.
A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.
Belda, Květoslav; Böhm, Josef
Roč. 5, č. 8 (2006), s. 1830-1837. ISSN 1109-2777 R&D Projects: GA ČR GP102/06/P275; GA ČR GA102/05/0271 Institutional research plan: CEZ:AV0Z10750506 Keywords : on-line identification * predictive control * input/output equations of predictions * real-time control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0040149.pdf
Belda, Květoslav; Böhm, Josef
Athens: WSEAS, 2006 - (Bardis, N.; Mladenov, V.), s. 307-312 ISBN 960-8457-47-5. [WSEAS International Conference on System. Athens (GR), 10.07.2006-12.07.2006] R&D Projects: GA ČR GP102/06/P275; GA ČR GA102/05/0271 Institutional research plan: CEZ:AV0Z10750506 Keywords : on-line identification * predictive control * input/output equations of predictions * real time control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0040145.pdf
Peng Song; Guo-kai Xu; Xiu-chun Zhao
Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules...
National Aeronautics and Space Administration — SSCI, in collaboration with Boeing Phantom Works, proposes to develop and test an efficient Integrated Damage Adaptive Control System (IDACS). The proposed system...
Chen Feng-Xiang; Wang Wei; Zhang Wei-Dong
The paper is concerned with adaptive tracking problem for a class of chaotic system with time-varying uncertainty,but bounded by norm polynomial. Based on adaptive technique, it proposes a novel controller to asymptotically track the arbitrary desired bounded trajectory. Simulation on the Rossler chaotic system is performed and the result verifies the effectiveness of the proposed method.
JIANG Rui; LUO Guiming
The least-squares(LS)algorithm has been used for system modeling for a long time. Without any excitation conditions, only the convergence rate of the common LS algorithm can be obtained. This paper analyzed the weighted least-squares(WLS)algorithm and described the good properties of the WLS algorithm. The WLS algorithm was then used for daptive control of linear stochastic systems to show that the linear closed-loop system was globally stable and that the system identification was consistent. Compared to the past optimal adaptive controller,this controller does not impose restricted conditions on the coefficients of the system, such as knowing the first coefficient before the controller. Without any persistent excitation conditions, the analysis shows that, with the regulation of the adaptive control, the closed-loop system was globally stable and the adaptive controller converged to the one-step-ahead optimal controller in some sense.
Farid, R.; Ibrahim, A.; Zalam, B., E-mail: firstname.lastname@example.org [Menofia University, Faculty of Electronic Engineering, Department of Industrial Electronics and Control, Menuf, Menofia (Egypt)
Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller.
Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller
Yizhong WANG; Huaguang ZHANG; Jun YANG
This paper focuses on the robust adaptive control problems for a class of interval time-delay systems and a class of large-scale interconnected systems. The nonlinear uncertainties of the systems under study are bounded by high-order polynomial functions with unknown gains. Firstly, the adaptive feedback controller which can guarantee the stability of the closed-loop system in the sense of uniform ultimate boundedness is proposed. Then the proposed adaptive idea is extended to robust stabilizing designing method for a class of large-scale interconnected systems. Here, another problem we address is to design a decentralized feedback adaptive controller such that the closed-loop system is stable in the sense of uniform ultimate boundedness for all admissible uncertainties and time-delay. Finally, an illustrative example is given to show the validity of the proposed approach.
National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...
Hansen, Poul Erik; Conrad, Finn
Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....
Hansen, Poul Erik; Conrad, Finn
Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....
Gunne J. Hegglid
Full Text Available This paper describes an adaptive multivariable control system for hydroelectric generating units. The system is based on a detailed mathematical model of the synchronous generator, the water turbine, the exiter system and turbine control servo. The models of the water penstock and the connected power system are static. These assumptions are not considered crucial. The system uses a Kalman filter for optimal estimation of the state variables and the parameters of the electric grid equivalent. The multivariable control law is computed from a Riccatti equation and is made adaptive to the generators running condition by means of a least square technique.
Sullivan, Gerald A.
Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up
Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...
LIU Yu-sheng; CHEN Jiang; LI Xing-yuan
Many physical systems such as biochemical processes and machines with friction are of nonlinearly parameterized systems with uncertainties.How to control such systems effectively is one of the most challenging problems.This paper presents a robust adaptive controller for a significant class of nonlinearly parameterized systems.The controller can be used in cases where there exist parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The design of the controller is based on the control Lyapunov function method.A dynamic signal is introduced and adaptive nonlinear damping terms are used to restrain the effects of unmodeled dynamics,nonlinear uncertainties and unknown bounded disturbances.The backstepping procedure is employed to overcome the complexity in the design.With the proposed method,the estimation of the unknown parameters of the system is not required and there is only one adaptive parameter no matter how high the order of the system is and how many unknown parameters.there are.It is proved theoretically that the proposed robust adaptive control scheme guarantees the stability of nonlinearly parameterized system.Furthermore,all the states approach the equilibrium in arbitrary precision by choosing some design constants appropriately.Simulation results illustrate the effectiveness of the proposed robust adaptive controller.
Mingjun ZHANG; Huaguang ZHANG
In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.
The variation of joint groove size during tungsten inert gas (TIG) welding will result in the non-uniform fill of deposited metal. To solve this problem, an adaptive fill control system was developed based on laser vision sensing. The system hardware consists of a modular development kit (MDK) as the real-time image capturing system, a computer as the controller, a D/A conversion card as the interface of controlled variable output, and a DC TIG welding system as the controlled device. The system software is developed and the developed feature extraction algorithm and control strategy are of good accuracy and robustness. Experimental results show that the system can implement adaptive fill of melting metal with high stability, reliability and accuracy. The groove is filled well and the quality of the weld formation satisfies the relevant industry criteria.
This work investigates adaptive control of a large class of uncertain me-delay chaotic systems (UTCSs) with unknown general perturbation terms bounded by a polynomial ( unknown gains). Associated with the different cases of known and unknown system matrices, two corresponding adaptive controllers are proposed to stabilize unstable fixed points of the systems by means of Lyapunov stability theory and linear matrix inequalities (LMI) which can be solved easily by convex optimization algorithms. Two examples are used for examining the effectiveness of the proposed methods.
Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza
For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.
LIU Yusheng; LI Xingyuan
The ideas of adaptive nonlinear damping and changing supply functions were used to counteract the effects of parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The high-gain observer was used to estimate the state of the system.A robust adaptive output feedback control scheme was proposed for nonlinearly parameterized systems represented by inputoutput models.The scheme does not need to estimate the unknown parameters nor add a dynamical signal to dominate the effects of unmodeled dynamics.It is proven that the proposed control scheme guarantees that all the variables in the closed-loop system are bounded and the mean-square tracking error can be made arbitrarily small by choosing some design parameters appropriately.Simulation results have illustrated the effectiveness of the proposed robust adaptive control scheme.
Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.
Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.
This paper describes an adaptive feed forward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF-field feedback control system can be eliminated with a feed forward system. Many RF-field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feed forward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feed forward system are presented. (Author) 3 figs., 2 refs
This paper describes an adaptive feedforward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF field feedback control system can be eliminated with a feedforward system. Many RF field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feedforward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feedforward system are presented
Wernicke, J.-Th. [Wind Force Engineering and Consulting GmbH, Bremerhaven (Germany)
The technology of Time Division Multiplexing (TDM) is compared with conventional strain gauge technologies in practical operation in a wind power system. Load cycles in the rotor blade were measured during plant life, and the data were used in plant control. The system is a tool in technical project management and financial management of a wind park. (orig.)
慕小武; 虞继敏; 毕卫萍; 程代展
Robust adaptive control of nonholonomic systems in chained form with linearly parameterized and strongly nonlinear disturbance and drift terms is dicussed.The novelty of the proposed method is a combined use of the state-scaling and the back-stepping procedure.
Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
In this paper, a learning control approach is applied to the generalized projective synchronisation (GPS) of different chaotic systems with unknown periodically time-varying parameters. Using the Lyapunov–Krasovskii functional stability theory, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to make the states of two different chaotic systems asymptotically synchronised. The scheme is successfully applied to the generalized projective synchronisation between the Lorenz system and Chen system. Moreover, numerical simulations results are used to verify the effectiveness of the proposed scheme. (general)
Volyanskyy, Kostyantyn Y.
Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance
Full Text Available There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting crosslayer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An eventdriven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN.
Yugang NIU; Xingyu WANG; Junwei LU
A dissipative-based adaptive neural control scheme was developed for a class of nonlinear uncertain systems with unknown nonlinearities that might not be linearly parameterized. The major advantage of the present work was to relax the requirement of matching condition, I.e., the unknown nonlinearities appear on the same equation as the control input in a state-space representation, which was required in most of the available neural network controllers. By synthesizing a state-feedback neural controller to nake the closed-loop system dissipative with respect to a quadratic supply rate, the developed control scheme guarantees that the L2-gain of controlled system was less than or equal to a prescribed level. And then, it is shown that the output tracking error is uniformly ultimate bounded. The design scheme is illustrated using a numerical simulation.
Basar, T. [Univ. of Illinois, Urbana, IL (United States)
We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.
Chen Yimei; Han Zhengzhi; Tang Houjun
The problem of adaptive stabilization of a class of multi-input nonlinear systems with unknown parameters both in the state vector-field and the input vector-field has been considered. By employing the control Lyapunov function method, a direct adaptive controller is designed to complete the global adaptive stability of the uncertain system. At the same time, the controller is also verified to possess the optimality. Example and simulations are provided to illustrate the effectiveness of the proposed method.
Nguyen, Nhan T.
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
Juan C. Tudón-Martínez
Full Text Available Several methods have been proposed to estimate the force of a semiactive damper, particularly of a magnetorheological damper because of its importance in automotive and civil engineering. Usually, all models have been proposed assuming experimental data in nominal operating conditions and some of them are estimated for control purposes. Because dampers are prone to fail, fault estimation is useful to design adaptive vibration controllers to accommodate the malfunction in the suspension system. This paper deals with the diagnosis and estimation of faults in an automotive magnetorheological damper. A robust LPV observer is proposed to estimate the lack of force caused by a damper leakage in a vehicle corner. Once the faulty damper is isolated in the vehicle and the fault is estimated, an Adaptive Vibration Control System is proposed to reduce the fault effect using compensation forces from the remaining healthy dampers. To fulfill the semiactive damper constraints in the fault adaptation, an LPV controller is designed for vehicle comfort and road holding. Simulation results show that the fault observer has good performance with robustness to noise and road disturbances and the proposed AVCS improves the comfort up to 24% with respect to a controlled suspension without fault tolerance features.
Partial pressure, system vibration and asymmetric system dynamic performance exit in asymmetric cylinder controller by symmetric valve hydraulic system. To solve this problem in the force control system, model reference adaptive controller is designed using equilibrium point stability theory and output error equation polynomial. The reference model is selected in such a way that it meets the system dynamic performance. Hardware configuration of asymmetric cylinder controlled by asymmetric valve hydraulic system is replaced by intelligent control algorithm, thus the cost is lowered and easy to application. Simulation results demonstrate that the proposed adaptive control sheme has good adaptive ability and well solves asymmetric dynamic performance problem. The designed adaptive controller is fairly robust to load disturbance and system parameter variation.
Chuanjing Hou; Lisheng Hu; Yingwei Zhang
An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.
Rasmussen, Henrik; Larsen, Lars F. S.
capacities ensures a high energy efficiency. The level of liquid filling is indirectly measured by the superheat. Introduction of variable speed compressors and electronic expansion valves enables the use of more sophisticated control algorithms, giving a higher degree of performance and just as important...... and used in a backstepping design of a nonlinear adaptive controller. The stability of the proposed method is validated theoretically by Lyapunov analysis and experimental results show the performance of the system for a wide range of operating points. The method is compared to a conventional method based...
Full Text Available This paper presents a robust adaptive fuzzy sliding mode control method for a class of uncertain nonlinear systems. The fractional order calculus is employed in the parameter updating stage. The underlying stability analysis as well as parameter update law design is carried out by Lyapunov based technique. In the simulation, two examples including a comparison with the traditional integer order counterpart are given to show the effectiveness of the proposed method. The main contribution of this paper consists in the control performance is better for the fractional order updating law than that of traditional integer order.
Wall, John H.; Orr, Jeb S.; VanZwieten, Tannen S.
Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to provide stable and high-performance flight. On its development path to Preliminary Design Review (PDR), the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an Adaptive Augmenting Control (AAC) algorithm has been shown to extend the envelope of failures and flight anomalies the SLS control system can accommodate while maintaining a direct link to flight control stability criteria such as classical gain and phase margin. In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the full SLS digital 3-axis autopilot, including existing load-relief elements, and the necessary steps for integration with the production flight software prototype have been implemented. Several updates which have been made to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are also shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.
Lefeber, AAJ Erjen; Nijmeijer, H Henk
We study an example of an adaptive (state) tracking control problem for a four-wheel mobile robot, as it is an illustrative example of the general adaptive state-feedback tracking control problem. It turns out that formulating the adaptive state-feedback tracking control problem is not straightforward, since specifying the reference state-trajectory can be in conflict with not knowing certain parameters. Our example illustrates this difficulty and we propose a problem formulation for the adap...
Mayer, D.; Pfeiffer, T.; Vrbata, J.; Melz, T.
Tuned vibration absorbers have become common for passive vibration reduction in many industrial applications. Lightly damped absorbers (also called neutralizers) can be used to suppress narrowband disturbances by tuning them to the excitation frequency. If the resonance is adapted in-operation, the performance of those devices can be significantly enhanced, or inertial mass can be decreased. However, the integration of actuators, sensors and control electronics into the system raises new design challenges. In this work, the development of adaptive-passive systems for vibration reduction at an industrial scale is presented. As an example, vibration reduction of a ship engine was studied in a full scale test. Simulations were used to study the feasibility and evaluate the system concept at an early stage. Several ways to adjust the resonance of the neutralizer were evaluated, including piezoelectric actuation and common mechatronic drives. Prototypes were implemented and tested. Since vibration absorbers suffer from high dynamic loads, reliability tests were used to assess the long-term behavior under operational conditions and to improve the components. It was proved that the adaptive systems are capable to withstand the mechanical loads in an industrial application. Also a control strategy had to be implemented in order to track the excitation frequency. The most mature concepts were integrated into the full scale test. An imbalance exciter was used to simulate the engine vibrations at a realistic level experimentally. The neutralizers were tested at varying excitation frequencies to evaluate the tracking capabilities of the control system. It was proved that a significant vibration reduction is possible.
The design and performance of a self-adaptive feedforward rf control system are reported. The system was built for the linac of the Accelerator Test Facility (ATF) at Brookhaven National Laboratory. Variables of time along the linac macropulse, such as field or phase are discretized and represented as vectors. Upon turn-on or after a large change in the operating-point, the control system acquires the response of the system to test signal vectors and generates a linearized system response matrix. During operation an error vector is generated by comparing the linac variable vectors and a target vector. The error vector is multiplied by the inverse of the system's matrix to generate a correction vector is added to an operating point vector. This control system can be used to control a klystron to produce flat rf amplitude and phase pulses, to control a rf cavity to reduce the rf field fluctuation, and to compensate the energy spread among bunches in a rf linac. Beam loading effects can be corrected and a programmed ramp can be produced. The performance of the control system has been evaluated on the control of a klystron's output as well as an rf cavity. Both amplitude and phase have been regulated simultaneously. In initial tests, the rf output from a klystron has been regulated to an amplitude fluctuation of less than ±0.3% and phase variation of less than ±0.6deg. The rf field of the ATF's photo-cathode microwave gun cavity has been regulated to ±5% in amplitude and simultaneously to ±1deg in phase. Regulating just the rf field amplitude in the rf gun cavity, we have achieved amplitude fluctuation of less than ±2%. (orig.)
V. M. Varatharaju; Badrilal Mathur; Udhayakumar
Problem statement: The tuning methodology for the parameters of adaptive speed controller causes a transient deviation of the response from the set reference following variation in load torque in a permanent-magnet brushless DC (BLDC) motor drive system. Approach: This study develops a mathematical model of the BLDC drive system, firstly. Secondly, discusses a design of the closed loop drive system employing the Adaptive-Network-based Fuzzy Interference System (ANFIS). The nonlinear simulatio...
Kim, Kilsoo (Inventor); Yucelen, Tansel (Inventor); Calise, Anthony J. (Inventor)
Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.
Zhang, Jianling; An, Jinwen; Wang, Mina
This paper describes the application and simulation of an adaptive fuzzy controller for a missile model. The fuzzy control system is tested using different values of fuzzy controller correctional factor on a nonlinear missile model. It is shown that the self-tuning fuzzy controller is well suited for controlling the pitch loop of the missile control system with air turbulence and parameter variety. The research shows that the Popov stability criterion could successfully guarantee the stability of the fuzzy system. It provides a good method for the design of missile control system. Simulation results suggest significant benefits from fuzzy logic in control task for missile pitch loop control.
van Nooijen, Ronald; Kolechkina, Alla; Mol, Bart
For small sewer systems that combine foul water and storm water sewer functions in flat terrain, central control of the sewer system may have problems during dry weather. These systems are a combination of local gravity flow networks connected by pumps. Under those conditions the level in the wet well (local storage at the pumping station) should be kept below the entrance pipe but above the top of the intake of the pump. The pumps are dimensioned to cope with the combined flow of foul water and precipitation run off so their capacity is relatively large when compared wityh the volume available in the wet well. Under local control this is not a major problem because the effective controller time step is very short. For central control the control time step can become a problem. Especially when there is uncertainty about the relation between level and volume in the wet well. In this paper we describe a way to dynamically adapt the level to volume relation based on dry weather behaviour. This is important because a better estimate of this volume will reduce the number of on/off cycles for the pumps. It will also allow detection and correction for changes in pump performance due to aging.
Ahn, Dae Ryong; Yang, Ji Hyun; Lee, Sang Hun [Kookmin University, Seoul (Korea, Republic of)
Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions.
Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions
Chunjie Zhou; Shuang Huang; Quan Yin; Duc Cuong Quach
In this paper, we present an improved Direct Adaptive Fuzzy (IDAF) controller applied to general control DC motor speed system. In particular, an IDAF algorithm is designed to control an uncertain DC motor speed to track a given reference signal. In fact, the quality of the control system depends significantly on the amount of fuzzy rules-fuzzy sets and the updating coefficient of the adaptive rule. This can be observed clearly by the system error when the reference input is constant and out ...
National Aeronautics and Space Administration — SSCI proposes to further develop, implement and test the damage-adaptive control algorithms developed in Phase I within the framework of an Integrated Damage...
Lu LU; Fagui LIU; Weixiang SHI
In this paper, a novel control law is presented, which uses neural-network techniques to approximate the affine class nonlinear system having unknown or uncertain dynamics and noise disturbances. It adopts an adaptive control law to adjust the network parameters online and adds another control component according to H-infinity control theory to attenuate the disturbance. This control law is applied to the position tracking control of pneumatic servo systems. Simulation and experimental results show that the tracking precision and convergence speed is obviously superior to the results by using the basic BP-network controller and self-tuning adaptive controller.
The synchronization of hyperchaotic Chen systems is considered. An adaptive synchronization approach and a cascade adaptive synchronization approach are presented to synchronize a drive system and a response system. By utilizing an adaptive controller based on the dynamic compensation mechanism, exact knowledge of the systems is not necessarily required, and the synchronous speed is controllable by tuning the controller parameters. Sufficient conditions for the asymptotic stability of the two synchronization schemes are derived. Numerical simulation results demonstrate that the adaptive synchronization scheme with four control inputs and the cascade adaptive synchronization scheme with only one control signal are effective and feasible in chaos synchronization of hyperchaotic systems. (general)
Virden, D.; Wagg, D.J.
A single degree of freedom mechanical spring-mass system was considered where the motion of the mass is constrained by an adjustable rigid impact stop. A model reference adaptive control algorithm combined with interspike interval techniques was used to consider the viability of identifying system parameters when impacts are present. The unmodified adaptive control algorithm destabilizes during vibro-impact motion, so three modified control algorithms were tested experimentally. The first, th...
Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)
Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.
Full Text Available Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS. This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to approximate the policy function of the Actor and the value function of the Critic simultaneously. These controllers are used to control a typical WECS in noiseless and noisy condition and results are compared with an adaptive Radial Basis Function (RBF PID control based on reinforcement learning and conventional PID control. Practical emulated results prove the capability and the robustness of the suggested controller versus the other PID controllers to control of the WECS. The ability of presented controller is tested by experimental setup.
V. M. Varatharaju
Full Text Available Problem statement: The tuning methodology for the parameters of adaptive speed controller causes a transient deviation of the response from the set reference following variation in load torque in a permanent-magnet brushless DC (BLDC motor drive system. Approach: This study develops a mathematical model of the BLDC drive system, firstly. Secondly, discusses a design of the closed loop drive system employing the Adaptive-Network-based Fuzzy Interference System (ANFIS. The nonlinear simulation model of the BLDC motors drive system with ANFIS control based is simulated in the MATLAB/SIMULINK platform. Results: The necessitated data for training the ANFIS control is generated by simulation of the system with conventional PI controller. Conclusion: The simulated electromagnetic torque and rotor speed signify the superiority of the proposed technique over the classical method.
The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller...... implementation. This is done using the code generation capabilities of Real Time Workshop in combination with C s-function blocks for adaptive control in Simulink. In the paper the design of each group of blocks normally found in adaptive controllers is outlined. The block types are, identification, controller...... design, controller and state variable filter.The use of the Adaptive Blockset is demonstrated using a simple laboratory setup. Both the use of the blockset for simulation and for rapid prototyping of a real-time controller are shown....
Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.
Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Isaac; Gregory, Irene M.; Cao, Chengyu
Certification of adaptive control technologies for both manned and unmanned aircraft represent a major challenge for current Verification and Validation techniques. A (missing) key step towards flight certification of adaptive flight control systems is the definition and development of analysis tools and methods to support Verification and Validation for nonlinear systems, similar to the procedures currently used for linear systems. In this paper, we describe and demonstrate the advantages of L(sub l) adaptive control architectures for closing some of the gaps in certification of adaptive flight control systems, which may facilitate the transition of adaptive control into military and commercial aerospace applications. As illustrative examples, we present the results of a piloted simulation evaluation on the NASA AirSTAR flight test vehicle, and results of an extensive flight test program conducted by the Naval Postgraduate School to demonstrate the advantages of L(sub l) adaptive control as a verifiable robust adaptive flight control system.
This Letter presents the adaptive control and synchronization problems for uncertain new chaotic dynamical system (Liu system). Based on Lyapunov stability theory, adaptive control law is derived such that the trajectory of Liu system with unknown parameters is globally stabilized to each unstable equilibrium point of the uncontrolled system. In addition, an adaptive control approach is proposed to make the states of two identical Liu systems with unknown parameters asymptotically synchronized. Numerical simulations are shown to verify the results
The Reactor TRIGA PUSPATI (RTP)-type TRIGA Mark II was installed in the year 1982. The Power Controller System (PCS) or Automated Power Controller System (APCS) is very important for reactor operation and safety reasons. It is a function of controlled reactivity and reactor power. The existing power controller system is under development and due to slow response, low accuracy and low stability on reactor power control affecting the reactor safety. The nuclear reactor is a nonlinear system in nature, and it is power increases continuously with time. The reactor parameters vary as a function of power, fuel burnup and control rod worth. The output power value given by the power control system is not exactly as real value of reactor power. Therefore, controller system design is very important, an adaptive controller seems to be inevitable. The method chooses is a linear controller by using feedback linearization, for example Model Reference Adaptive Control. The developed APCS for RTP will be design by using Model Reference Adaptive Control (MRAC). The structured of RTP model to produce the dynamic behaviour of RTP on entire operating power range from 0 to 1MWatt. The dynamic behavior of RTP model is produced by coupling of neutronic and thermal-hydraulics. It will be developed by using software MATLAB/Simulink and hardware module card to handle analog input signal. A new algorithm for APCS is developed to control the movement of control rods with uniformity and orderly for RTP. Before APCS test to real plant, simulation results shall be obtained from RTP model on reactor power, reactivity, period, control rod positions, fuel and coolant temperatures. Those data are comparable with the real data for validation. After completing the RTP model, APCS will be tested to real plant on power control system performance by using real signal from RTP including fail-safe operation, system reliable, fast response, stability and accuracy. The new algorithm shall be a satisfied
This paper investigates the issue of adaptive finite-time control for hyperchaotic Lorenz–Stenflo systems with parameter uncertainties. Based on finite-time Lyapunov theory, a class of non-smooth adaptive finite time controllers is given to guarantee the adaptive finite-time stability and make the states of the systems converge to the origins within a finite-time. Finally, illustrative examples are presented to verify the effectiveness of the proposed adaptive finite-time controller. (paper)
Xuan Phu Do
Full Text Available This paper presents a new direct adaptive fuzzy controller and its effectiveness is verified by investigating the damping force tracking control of magnetorheological (MR fluid based damper (MR damper in short system. In the formulation of the proposed controller, a model of interval type 2 fuzzy controller is combined with the direct adaptive control to achieve high performance in vibration control. In addition, H∞ (H infinity tracking technique is used in building a model of the direct adaptive fuzzy controller in which an enhanced iterative algorithm is combined with the fuzzy model. After establishing a closed-loop control structure to achieve high control performance, a cylindrical MR damper is adopted and damping force tracking results are obtained and discussed. In addition, in order to demonstrate the effectiveness of the proposed control strategy, two existing controllers are modified and tested for comparative work. It has been demonstrated from simulation and experiment that the proposed control scheme provides much better control performance in terms of damping force tracking error. This leads to excellent vibration control performance of the semiactive MR damper system associated with the proposed controller.
REZAZADEH, A.; SEDIGHIZADEH, M.
Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS). This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to appro...
Mizumoto, Ikuro; Takagi, Taro; Fukui, Sota; Shah, Sirish L.
This paper deals with a design problem of an adaptive output feedback control for discrete-time systems with a parallel feedforward compensator (PFC) which is designed for making the augmented controlled system ASPR. A PFC design scheme by a FRIT approach with only using an input/output experimental data set will be proposed for discrete-time systems in order to design an adaptive output feedback control system. Furthermore, the effectiveness of the proposed PFC design method will be confirmed through numerical simulations by designing adaptive control system with adaptive NN (Neural Network) for an uncertain discrete-time system.
Bieniawski, Stefan; Wolpert, David H.
Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.
Martín-Sánchez, Juan M
This book is a didactic explanation of the developments of predictive, adaptive predictive and optimized adaptive control, including the latest methodology of adaptive predictive expert (ADEX) control, and their practical applications. It is focused on the stability perspective, used in the introduction of these methodologies, and is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. ADEX Optimized Adaptive Controllers and Systems begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guarantee achievement of desired control performance. The second and third parts are centered on the design of the driver block and adaptive mechanism, which verify these stability conditions. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control m...
Nguyen, Nhan T.
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.
FENG Ling-ling; ZHANG Wei
This paper proposes an indirect adaptive neural control scheme for a class of nonlinear systems with time delays. Based on the backstepping technique and Lyapunov–Krasovskii functional method are combined to construct the indirect adaptive neural controller. The proposed indirect adaptive neural controller guarantees that the state variables converge to a small neighborhood of the origin and all the signals of the closed-loop system are bounded. Finally, an example is used to show the effectiveness of the proposed control strategy.
Full Text Available Attitude dynamic model of unmanned aerial vehicles (UAVs is multi-input multioutput (MIMO, strong coupling, and nonlinear. Model uncertainties and external gust disturbances should be considered during designing the attitude control system for UAVs. In this paper, feedback linearization and model reference adaptive control (MRAC are integrated to design the attitude control system for a fixed wing UAV. First of all, the complicated attitude dynamic model is decoupled into three single-input single-output (SISO channels by input-output feedback linearization. Secondly, the reference models are determined, respectively, according to the performance indexes of each channel. Subsequently, the adaptive control law is obtained using MRAC theory. In order to demonstrate the performance of attitude control system, the adaptive control law and the proportional-integral-derivative (PID control law are, respectively, used in the coupling nonlinear simulation model. Simulation results indicate that the system performance indexes including maximum overshoot, settling time (2% error range, and rise time obtained by MRAC are better than those by PID. Moreover, MRAC system has stronger robustness with respect to the model uncertainties and gust disturbance.
Full Text Available The main purpose of this paper is to develop an onboard adaptive and robust flight control system that improves control, stability, and survivability of a small unmanned aerial system in off-nominal or out-of-envelope conditions. The aerodynamics of aircraft associated with hazardous and adverse onboard conditions is inherently nonlinear and unsteady. The presented flight control system improves functionalities required to adapt the flight control in the presence of aircraft model uncertainties. The fault tolerant inner loop is enhanced by an adaptive real-time artificial neural network parameter identification to monitor important changes in the aircraft’s dynamics due to nonlinear and unsteady aerodynamics. The real-time artificial neural network parameter identification is done using the sliding mode learning concept and a modified version of the self-adaptive Levenberg algorithm. Numerically estimated stability and control derivatives are obtained by delta-based methods. New nonlinear guidance logic, stable in Lyapunov sense, is developed to guide the aircraft. The designed flight control system has better performance compared to a commercial off-the-shelf autopilot system in guiding and controlling an unmanned air system during a trajectory following.
Athans, M.; Willner, D.
A flight control system design is presented, that can be implemented by analog hardware, to be used to control an aircraft with uncertain parameters. The design is based upon the use of modern control theory. The ideas are illustrated by considering control of STOL longitudinal dynamics.
Full Text Available Fuzzy adaptive tracking controllers for a class of uncertain nonlinear dynamicalsystems are proposed and analyzed. The controller consists of adaptive and robustifyingcomponents whose role is to nullify the effect of uncertainties and achieve a desiredtracking performance. The interactions between the two components have beeninvestigated. We use the Takagi-Sugeno-Kang type of the fuzzy logic system to approximatethe controller. It is proved that the closed-loop system using this adaptive fuzzy controlleris globally stable in the sense that all signals involved are bounded. Finally, we apply themethod of direct adaptive fuzzy controllers to control an inverted pendulum and thesimulation results are included.
Engel, E.; Kovalev, I. V.; Kobezhicov, V.
This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.
XiaoJing Wang; ChangFu Xian; CaoLei Wan; JinBao Zhao; LiWei Xiu; AnCai Yu
In order to consider the influence of the continuous rotary motor electro-hydraulic servo system parameters change on its performance, the design method of backstepping adaptive controller is put forward. The mathematical model of electro-hydraulic servo system of continuous rotary motor is established, and the whole system is decomposed into several lower order subsystems, and the virtual control signal is designed for each subsystem from the final subsystem with motor angular displacement to the subsystem with system control input voltage. Based on Lyapunov method and the backstepping theory, an adaptive backstepping controller is designed with the changed parameters adaptive law. It is proved that the system reaches the global asymptotic stability, and the system tracking error asymptotically tends to zero. The simulation results show that the backstepping adaptive controller based on the adaptive law of the changed parameters can improve the performance of continuous rotary motor, and the proposed control strategy is feasible.
Ahmad A.M. Faudzi; Suzumori, K
Problem statement: Communication and control are two main components in any Mechatronics system. They can be designed either by centralized or decentralized approach. Both approaches can be chosen based on application designed and specific requirements of the designer. In this study, decentralized or normally called distributed approach was selected to solved communication and control of a human adaptive mechanical system namely Intelligent Chair Tools (ICT). The ICT seating system is powered...
This paper presents an improved observer-based indirect adaptive fuzzy control scheme for multiinput-multioutput (MIMO) nonlinear time-delay systems.The control scheme synthesizes adaptive fuzzy control with adaptive fuzzy identification.An observer is designed to observe the system state,and an identifier is developed to identify the unknown parts of the system.The update laws for parameters utilize two types of errors in the adaptive time-delay fuzzy logic systems,the observation error and the identificat...
A robust adaptive PID controller design motivated from the sliding mode control is proposed for a class of uncertain chaotic systems in this paper. Three PID control gains, K p, K i, and K d, are adjustable parameters and will be updated online with an adequate adaptation mechanism to minimize a previously designed sliding condition. By introducing a supervisory controller, the stability of the closed-loop PID control system under with the plant uncertainty and external disturbance can be guaranteed. Finally, a well-known Duffing-Holmes chaotic system is used as an illustrative to show the effectiveness of the proposed robust adaptive PID controller
National Aeronautics and Space Administration — M4 Engineering proposes the development of an adaptive structural mode control system. The adaptive control system will begin from a "baseline" dynamic model of the...
Goodwin, Graham C
Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o
Yao, Wei; Fang, Jiakun; Zhao, Ping;
In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have the...
Full Text Available This paper considers the containment control problem for uncertain nonlinear multiagent systems under directed graphs. The followers are governed by nonlinear systems with unknown dynamics while the multiple leaders are neighbors of a subset of the followers. Fuzzy logic systems (FLSs are used to identify the unknown dynamics and a distributed state feedback containment control protocol is proposed. This result is extended to the output feedback case, where observers are designed to estimate the unmeasurable states. Then, an output feedback containment control scheme is presented. The developed state feedback and output feedback containment controllers guarantee that the states of all followers converge to the convex hull spanned by the dynamic leaders. Based on Lyapunov stability theory, it is proved that the containment control errors are uniformly ultimately bounded (UUB. An example is provided to show the effectiveness of the proposed control method.
Hosseini, S.H.; Etemadi, A.H. [Department of Electrical Engineering, Sharif University of Technology, Tehran (Iran)
Fixed gain controllers for automatic generation control are designed at nominal operating conditions and fail to provide best control performance over a wide range of operating conditions. So, to keep system performance near its optimum, it is desirable to track the operating conditions and use updated parameters to compute control gains. A control scheme based on artificial neuro-fuzzy inference system (ANFIS), which is trained by the results of off-line studies obtained using particle swarm optimization, is proposed in this paper to optimize and update control gains in real-time according to load variations. Also, frequency relaxation is implemented using ANFIS. The efficiency of the proposed method is demonstrated via simulations. Compliance of the proposed method with NERC control performance standard is verified. (author)
Li Ning; Yuan Hui-Qun; Sun Hai-Yi; Zhang Qing-Ling
In this paper,the stabilization of a continuous time-delayed system is considered.To control the bifurcation and chaos in a time-delayed system,a parameter perturbation control and a hybrid control are proposed.Then,to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes,the adaptive control idea is introduced,i.e.,the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws,respectively.The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem.The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods.They have the advantages of increased stability,adaptability to the changes of the system parameters,control cost saving,and simplicity.Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods.A comparison of the two adaptive control methods is also made in an experimental study.
In this paper, the stabilization of a continuous time-delayed system is considered. To control the bifurcation and chaos in a time-delayed system, a parameter perturbation control and a hybrid control are proposed. Then, to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes, the adaptive control idea is introduced, i.e., the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws, respectively. The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem. The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods. They have the advantages of increased stability, adaptability to the changes of the system parameters, control cost saving, and simplicity. Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods. A comparison of the two adaptive control methods is also made in an experimental study
Andersen, Torben Ole; Pedersen, Henrik Clemmensen; Bech, Michael Møller;
This paper deals with high-performance position control of hydraulics servo systems in general. The hydraulic servo system used is a two link robotic manipulator actuated by two hydraulic servo cylinders. A non-linear model of the hydraulic system and a Newton-Euler based model of the mechanical...
R.R. Joshi; R.A. Gupta; A.K. Wadhwani
A systematic controller design and implementation for a matrix-converter-based induction motor drive system is proposed. A nonlinear adaptive backstepping controller is proposed to improve the speed and position responses of the induction motor system. By using the proposed adaptive backstepping controller, the system can track a time-varying speed command and a time-varying position command well. Moreover, the system has a good load disturbance rejection capability. The realization of the co...
Adaptive H∞ synchronization of chaotic systems via linear and nonlinear feedback control is investigated. The chaotic systems are redesigned by using the generalized Hamiltonian systems and observer approach. Based on Lyapunov's stability theory, linear and nonlinear feedback control of adaptive H∞ synchronization is established in order to not only guarantee stable synchronization of both master and slave systems but also reduce the effect of external disturbance on an H∞-norm constraint. Adaptive H∞ synchronization of chaotic systems via three kinds of control is investigated with applications to Lorenz and Chen systems. Numerical simulations are also given to identify the effectiveness of the theoretical analysis. (general)
We use the approach of "optimal" switching to design the adaptive control because the design among multiple models is intuitively more practically feasible than the traditional adaptive control in improving the performances. We prove that for a typical class of nonlinear systems disturbed by random noise, the multiple model adaptive switching control based on WLS(Weighted Least Squares) or projected-LS (Least Squares) is stable and convergent.
The paper concerns the development of a new adaptive PI controller for use in HVAC systems. The process of HVAC control can be described as a first order plus dead time model. A kind of arithmetic of recursive least squares (RLS) with exponential forgetting combined with model matching of a zero frequency method is adopted to estimate the model's parameters while the system remained in closed loop. Then, a simple tuning formula for a PI controller with robustness based on the estimated parameters was used to adjust the controller's parameters automatically while under closed loop. To evaluate the effectiveness of the adaptive PI controller, the proposed method was compared with a H ∞ adaptive PI controller. The simulation results show that the new adaptive PI controller has superior performance to that of the H ∞ adaptive PI controller
Cao, Chengyu (Inventor); Hovakimyan, Naira (Inventor); Xargay, Enric (Inventor)
Systems and methods of adaptive control for uncertain nonlinear multi-input multi-output systems in the presence of significant unmatched uncertainty with assured performance are provided. The need for gain-scheduling is eliminated through the use of bandwidth-limited (low-pass) filtering in the control channel, which appropriately attenuates the high frequencies typically appearing in fast adaptation situations and preserves the robustness margins in the presence of fast adaptation.
S. Lokesh; , T.Prahlad Reddy
By increasing of population the usage of vehicles have been increasing and controlling of traffic is one of the challenging works. The frequent traffic jams at major junctions call for an efficient traffic management system in place. The resulting wastage of time and increase in pollution levels can be eliminated on a city-wide scale by these systems. Previously the traffic control techniques used like magnetic loop detectors, induction loop detectors are buried on the road si...
Lequan Min; Jianyi Jing
Chaos synchronization has been applied in secure communication, chemical reaction, biological systems, and information processing. A new theorem to synchronization of unified chaotic systems via adaptive control is proposed. The consutructive theorem provides the design scheme for adaptive controller such that a respond system can synchronize with respect to an uncertain drive system. One example for discontinuous chaotic system is proposed to illustrate the effectiveness and feasibility.
Cai Guo-Liang; Zheng Song; Tian Li-Xin
This paper is involved with the adaptive control and synchronization problems for an uncertain new hyperchaotic Lorenz system. Based on the Lyapunov stability theory, the adaptive control law is derived such that the trajectory of hyperchaotic Lorenz system with unknown parameters can be globally stabilized to an unstable equilibrium point of the uncontrolled system. Furthermore, an adaptive control approach is presented to the synchronizations between two identical hyperchaotic systems, particularly between two different uncertain hyperchaotic systems. Numerical simulations show the effectiveness of the presented method.
This paper is involved with the adaptive control and synchronization problems for an uncertain new hyperchaotic Lorenz system. Based on the Lyapunov stability theory, the adaptive control law is derived such that the trajectory of hyperchaotic Lorenz system with unknown parameters can be globally stabilized to an unstable equilibrium point of the uncontrolled system. Furthermore, an adaptive control approach is presented to the synchronizations between two identical hyperchaotic systems, particularly between two different uncertain hyperchaotic systems. Numerical simulations show the effectiveness of the presented method. (general)
Active control is an effective method for synchronizing two identical chaotic systems. However, this method works only for a certain class of chaotic systems with known parameters. An improvement method was proposed in order to overcome this limitation in this paper. A classical example was used to demonstrate the method. Finally, numerical examples were given to validate the efficiency of the method.
Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon
This paper presents design and verification of an estimation and control system for a helicopter slung load system. The estimator provides position and velocity estimates of the slung load and is designed to augment existing navigation in autonomous helicopters. Sensor input is provided by a vision...
This paper describes a computer system for the setting and control of all the magnets and high voltage supplies of a many element spectrometer using an LSI11/23 running RT11 with CAMAC input/output. Magnetic field strengths are measured by an inexpensive and easily constructed system of Hall probes and temperature transducers. The software calculates the field strength in each magnet by applying a temperature correction and a quadratic calibration to the measured Hall voltage. Keyboard commands to the system provide many facilities for setting up and control of the separator. Communication with a remote processor via an X25 link is also described. (orig.)
Narendra, K. S.; Annaswamy, A. M.
Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.
Johnson, C. R., Jr.; Montgomery, R. C.
One attitude control device being studied for large spacecraft consists of two counter-rotating rings, each designated as an annular momentum control device (AMCD), that are attached to a spacecraft using several magnetic bearings distributed along the circumference of the rings. For large spacecraft large rings are desirable. Unfortunately, for large rings flexibility is appreciable and it becomes necessary to account for the distributed nature of the rings in the design of the magnetic bearing controllers. Also ring behavior is unpredictably sensitive to ring temperature, spin rate, manufacturing imperfections, and other variables. For that reason a distributed adaptive microcomputer-based control system is being sought for ring stabilization and maneuvering. An original adaptive-control methodology for distributed-parameter systems is detailed and application to spinning ring, i.e., AMCD, stabilization is used as an illustration. The proposed methodology, presented as a step-by-step procedure, combines a lumped-parameter expansion description of distributed parameter systems with a fundamental simultaneous identification and control strategy. Simulations are presented providing preliminary evidence of the capabilities of the proposed procedure.
This study addresses the adaptive synchronization of a modified Chua's circuit system with both unknown system parameters and the nonlinearity in the control input. An adaptive switching surface is newly adopted such that it becomes easy to ensure the stability of the error dynamics in the sliding mode. Based on this adaptive switching surface, an adaptive sliding mode controller (ASMC) is derived to guarantee the occurrence of the sliding motion, even when the system is undergoing input nonlinearity. This method can also be easily extended to a general class of Chua's circuits. An illustrative example is given to show the applicability of the proposed ASMC design
Full Text Available The main contribution of the paper is the development of an adaptive backstepping controller for a nonlinear hydraulic-mechanical system considering valve dynamics. The paper also compares the performance of two variants of an adaptive backstepping tracking controller with a simple PI controller. The results show that the backstepping controller considering valve dynamics achieves significantly better tracking performance than the PI controller, while handling uncertain parameters related to internal leakage, friction, the orifice equation and oil characteristics.
Tokmakova, I.; Yanchenko, N.
The article is devoted to research of approaches to introduction of the system of adaptive control on the enterprises of railway transport, the process of its integration in the existent system of management is considered in particular.
A robust adaptive sliding control scheme is developed in this study to achieve synchronization for two identical chaotic systems in the presence of uncertain system parameters, external disturbances and nonlinear control inputs. An adaptation algorithm is given based on the Lyapunov stability theory. Using this adaptation technique to estimate the upper-bounds of parameter variation and external disturbance uncertainties, an adaptive sliding mode controller is then constructed without requiring the bounds of parameter and disturbance uncertainties to be known in advance. It is proven that the proposed adaptive sliding mode controller can maintain the existence of sliding mode in finite time in uncertain chaotic systems. Finally, numerical simulations are presented to show the effectiveness of the proposed control scheme.
Full Text Available Adaptive assistive control for a haptic interface system is proposed in the present paper. The assistive control system consists of three subsystems: a servo controller to match the response of the controlled machine to the virtual model, an online identifier of the operator’s control characteristics, and a variable dynamics control using adaptive mechanism. The adaptive mechanism tunes an impedance of the virtual model for the haptic device according to the identified operator’s characteristics so as to enhance the operator’s control performance. The adaptive law is derived by utilizing a Lyapunov candidate function. Using a haptic interface device composed by a xy-stage, an effectiveness of the proposed control method was evaluated experimentally. As a result, it was confirmed that the operator’s characteristics can be estimated sufficiently and that performance of the operation was enhanced by the variable dynamics assistive control.
This paper attempts to study a optimal adaptive con tr ol problem using game theory, and proposes an important practical result that an adaptive processes is a set of sufficient conditions under which pure strategy is essentially complete, and thus the fact that yield a very useful desirable pu re optimal control rule.Optimal Adaptive Control of a Class of Stochastic Systems Using Game Theory
Li Huiguang; Zhang Xinying; Guan Xinping
The synchronization problem under two cases is considered. One is that the bound on the uncertainty existing in the controller is known, the other is that the bound is unknown. In the latter case, the simple adaptation laws for upper bound on the norm of the uncertainty is proposed. Using this adaptive upper bound, a variable structure control is designed. The proposed method does not guarantee the convergence of the adaptive upper bound to the real one but makes the system asymptotically stable.
Barkana, Itzhak, E-mail: email@example.com [BARKANA Consulting, Ramat Hasharon (Israel)
Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.
Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits
Rotariu, I; Steinbuch, M Maarten; Ellenbroek, RML Rogier
Iterative learning control (ILC) is a very effective technique to reduce systematic errors that occur in systems that repetitively perform the same motion or operation. However, several characteristics have prevented standard ILC from being widely used for high precision motion systems. Most importantly, the learned feedforward signal depends on the motion profile (setpoint trajectory) and if this is altered, the learning process has to be repeated. Secondly, ILC amplifies non-repetitive dist...
Horvat, Krunoslav; Šoić, Ines; Kuljača, Ognjen
The paper presents an analytical and simulation approach for the selection of activation functions for the class of neural network controllers for ship’s thermogenerator angular velocity stabilization system. Such systems can be found in many ships. A Lyapunov-like stability analysis is performed in order to obtain a weight update law. A number of simulations were performed to find the best activation function using integral error criteria and statistical T-tests.
Wei GUAN; Guanghong YANG
This paper studies the problem of designing adaptive fault-tolerant H-infinity controllers for linear timeinvariant systems with actuator saturation. The disturbance tolerance ability of the closed-loop system is measured by an optimal index. The notion of an adaptive H-infinity performance index is proposed to describe the disturbance attenuation performances of closed-loop systems. New methods for designing indirect adaptive fault-tolerant controllers via state feedback are presented for actuator fault compensations. Based on the on-line estimation of eventual faults, the adaptive fault-tolerant controller parameters are updated automatically to compensate for the fault effects on systems. The designs are developed in the framework of the linear matrix inequality (LMI) approach, which can guarantee the disturbance tolerance ability and adaptive H-infinity performances of closed-loop systems in the cases of actuator saturation and actuator failures. An example is given to illustrate the efficiency of the design method.
Chen, Ching-Huei; Chang, Shu-Wei
The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners' cognitive…
Patre, Parag; Joshi, Suresh M.
Decentralized adaptive control is considered for systems consisting of multiple interconnected subsystems. It is assumed that each subsystem s parameters are uncertain and the interconnection parameters are not known. In addition, mismatch can exist between each subsystem and its reference model. A strictly decentralized adaptive control scheme is developed, wherein each subsystem has access only to its own state but has the knowledge of all reference model states. The mismatch is estimated online for each subsystem and the mismatch estimates are used to adaptively modify the corresponding reference models. The adaptive control scheme is extended to the case with actuator failures in addition to mismatch.
Full Text Available By increasing of population the usage of vehicles have been increasing and controlling of traffic is one of the challenging works. The frequent traffic jams at major junctions call for an efficient traffic management system in place. The resulting wastage of time and increase in pollution levels can be eliminated on a city-wide scale by these systems. Previously the traffic control techniques used like magnetic loop detectors, induction loop detectors are buried on the road side provide the limited traffic information and require separate systems for traffic counting and for traffic surveillance. Here the project proposes to implement an artificial density traffic control system using image processing and Raspberrypi. The hardware here we are using is webcam, pc, Raspberry pi and the software used is OCCIDENTALIS and MATLAB. In this project the camera is get interfaced with a Raspberry pi. The image sequences from a camera are analyzed using thresholding method to find the density of vehicles. Subsequently, the number of vehicles at the intersection is evaluated and traffic is efficiently managed. In this project we implemented a real-time emergency vehicle detection system. In case an emergency vehicle is detected, the lane is given priority over all the others.
In this paper, a new adaptive control scheme is developed for a class of chaotic systems with unknown bounded uncertainties. Based on Lyapunov stability theory, an adaptive feedback controller is designed for tracking a smooth orbit that can be a limit cycle or a chaotic orbit of another system. Furthermore, it is worthy of note that the proposed adaptive control scheme does not involve any information about the bounds of uncertainties. A numerical example of the Duffing system is included to verify the validity of the proposed scheme. (author)
Dr. V. Sundarapandian
Full Text Available In this paper, we apply adaptive control method to derive new results for the global chaos synchronization of identical hyperchaotic Lorenz systems (2007, identical hyperchaotic Chen systems (2010 and non-identical hyperchaotic Lorenz and hyperchaotic Chen systems. In this paper, we shall assume that the parameters of both master and slave systems are unknown and we devise adaptive synchronizing schemes using the estimates of parameters for both master and slave systems. Our adaptive synchronization results derived in this paper are established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the adaptive control method is very effective and convenient to synchronize identical and non-identical hyperchaotic Lorenz and hyperchaotic Chensystems. Numerical simulations are shown to demonstrate the effectiveness of the proposed adaptive synchronization schemes for the hyperchaotic systems addressed in this paper.
Full Text Available This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC in the speed sensorless vector control of an induction motor (IM drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.
Installation and operation of a commercially available adaptive process control system in a gold processing plant in Nevada has proven technically and financially successful. Test results show that the system paid for itself through increased throughput within two weeks of commissioning. The control system uses an expert rule base written with both crisp and fuzzy logic rules integrated with continually adapting neural network models used by predictors, and optimizers. This allows the control system to provide optimum process performance under continually varying feed conditions. This paper describes the installation, rule and predictor configuration, and statistically verifiable testing of the control system in an operating plant. (author)
Full Text Available This communication develops an adaptive scheme for control and synchronization of Sprott J system with fully unknown parameters. The scheme provides an elegant strategy of designing estimators for identification of the unknown parameters of the underlying dynamical system. Adaptive control and update laws are proposed to globally stabilize the chaotic Sprott J system. A pair of identical Sprott J systems with un- known parameters are globally synchronized with the help of adaptive control and parameter update laws. The results are established using LaSalle invariance principle, which lays down weaker restrictions on the derivatives of the Lyapunov function, and producing more general results. All the results obtained in the paper are global in nature. Numerical simulations are performed to illustrate the validity and effectiveness of the proposed adaptive control and synchronization scheme in the context of the Sprott J system. The parameter identification capability of the scheme is also explored.
Wu, Zhizheng; Ben Amara, Foued
Modeling and Control of Magnetic Fluid Deformable Mirrors for Adaptive Optics Systems presents a novel design of wavefront correctors based on magnetic fluid deformable mirrors (MFDM) as well as corresponding control algorithms. The presented wavefront correctors are characterized by their linear, dynamic response. Various mirror surface shape control algorithms are presented along with experimental evaluations of the performance of the resulting adaptive optics systems. Adaptive optics (AO) systems are used in various fields of application to enhance the performance of optical systems, such as imaging, laser, free space optical communication systems, etc. This book is intended for undergraduate and graduate students, professors, engineers, scientists and researchers working on the design of adaptive optics systems and their various emerging fields of application. Zhizheng Wu is an associate professor at Shanghai University, China. Azhar Iqbal is a research associate at the University of Toronto, Canada. Foue...
Balas, Mark J.; Frost, Susan A.
This paper presents an introduction to Evolving Systems, which are autonomously controlled subsystems that self-assemble into a new Evolved System with a higher purpose. Evolving Systems of aerospace structures often require additional control when assembling to maintain stability during the entire evolution process. This is the concept of Adaptive Key Component Control which operates through one specific component to maintain stability during the evolution. In addition this control must overcome persistent disturbances that occur while the evolution is in progress. We present theoretical results for the successful operation of Nonlinear Adaptive Key Component control in the presence of such disturbances and an illustrative example.
Ronghu CHI; Zhongsheng HOU
In this paper,an optimal higher order learning adaptive control approach is developed for a class of SISO nonlinear systems.This design is model-free and depends directly on pseudo-partial-derivatives derived on-line from the input and output information of the system.A novel weighted one-step-ahead control criterion function is proposed for the control law.The convergence analysis shows that the proposed control law can guarantee the convergence under the assumption that the desired output is a set point.Simulation examples are provided for nonlinear systems to illustrate the better performance of the higher order learning adaptive control.
Mizumoto, Ikuro; Nakamura, Takuto; Kumon, Makoto; Takagi, Taro [Dept. of Mechanical Systems Engineering, Kumamoto University 2-39-1 Kurokami, Kumamoto, 860-8555 (Japan)
The paper deals with an adaptive control system design problem for a four rotor helicopter or quadrotor. A simple adaptive control design scheme with a parallel feedforward compensator (PFC) in the internal loop of the considered quadrotor will be proposed based on the backstepping strategy. As is well known, the backstepping control strategy is one of the advanced control strategy for nonlinear systems. However, the control algorithm will become complex if the system has higher order relative degrees. We will show that one can skip some design steps of the backstepping method by introducing a PFC in the inner loop of the considered quadrotor, so that the structure of the obtained controller will be simplified and a high gain based adaptive feedback control system will be designed. The effectiveness of the proposed method will be confirmed through numerical simulations.
The paper deals with an adaptive control system design problem for a four rotor helicopter or quadrotor. A simple adaptive control design scheme with a parallel feedforward compensator (PFC) in the internal loop of the considered quadrotor will be proposed based on the backstepping strategy. As is well known, the backstepping control strategy is one of the advanced control strategy for nonlinear systems. However, the control algorithm will become complex if the system has higher order relative degrees. We will show that one can skip some design steps of the backstepping method by introducing a PFC in the inner loop of the considered quadrotor, so that the structure of the obtained controller will be simplified and a high gain based adaptive feedback control system will be designed. The effectiveness of the proposed method will be confirmed through numerical simulations
Fiacchini, Mirko; Alamo, Teodoro; Albea-Sanchez, Carolina; Fernandez Camacho, Eduardo
International audience In this paper, an adaptive control scheme for the safe operation of a fuel cell system is presented. The aim of the control design is to guarantee that the oxygen ratio do not reach dangerous values. A first level of control is given by a feedforward control. An improved behavior is obtained using an adaptive predictive controller to determine the voltage to be applied to the air compressor. An admissible robust control invariant set for the PWA model of the system i...
Wei Du-Qu; Luo Xiao-Shu
With system parameters falling into a certain area, power system with excitation limits experiences complicated chaotic oscillations which threaten the secure and stable operation of power system. In this paper, to control these unwanted chaotic oscillations, a straightforward adaptive chaos controller based on Lyapunov asymptotical stability theory is designed. Since the presented controller does not need to change the controlled system structure and not to use any information of system except the system state variables, the designed controller is simple and desirable.Simulation results show that the proposed control law is very effective. This work is helpful to maintain the power system's security operation.
PU Xing-cheng; WANG Hai-ying
A parameter adaptive control approach was applied to a kind of financial chaotic systems. According to Lyapunov stability theorem, synchronization of two financial chaotic systems with different certain parameters or the same uncertain parameters were implemented through designing proper control functions and using parameters self-adaptive control principle. The sufficient synchronization conditions of the two financial systems were obtained. Under the situation of the same uncertain parameters, the synchronization system has simpler controller and better performance. Numerical simulations show the effectiveness of the method.
梅生伟; 金敏杰; 申铁龙
Generator excitation control plays an important role in improving the dynamic performance and stability of power systems. This paper is concerned with nonlinear decentralized adaptive excitation control for multi-machine power systems. Based on a recursive design method, an adaptive excitation control law with L2 disturbance attenuation is constructed. Furthermore, it is verified that the proposed control scheme possesses the property of decentralization and the robustness in the sense of L2-gain. As a consequence, transient stability of a multi-machine power system is guaranteed, regardless of system parameters variation and faults.
Full Text Available This paper analyzes the structure principle of the actuator simulated loading system with variable stiffness, and establishes the simplified model. What’s more, it also does a research on the application of the self-adaptive tuning of fuzzy PID(Proportion Integration Differentiation in actuator simulated loading system with variable stiffness. Because the loading system is connected with the steering system by a spring rod, there must be strong coupling. Besides, there are also the parametric variations accompanying with the variations of the stiffness. Based on compensation from the feed-forward control on the disturbance brought by the motion of steering engine, the system performance can be improved by using fuzzy adaptive adjusting PID control to make up the changes of system parameter caused by the changes of the stiffness. By combining the fuzzy control with traditional PID control, fuzzy adaptive PID control is able to choose the parameters more properly.
Mayosky, M A; Cancelo, I E
Grid connected wind energy conversion systems (WECS) present interesting control demands, due to the intrinsic nonlinear characteristics of windmills and electric generators. In this paper a direct adaptive control strategy for WECS control is proposed. It is based on the combination of two control actions: a radial basis zfunction network-based adaptive controller, which drives the tracking error to zero with user specified dynamics, and a supervisory controller, based on crude bounds of the system's nonlinearities. The supervisory controller fires when the finite neural-network approximation properties cannot be guaranteed. The form of the supervisor control and the adaptation law for the neural controller are derived from a Lyapunov analysis of stability. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution. PMID:18252585
Yang, Jung Hua
In this chapter, a nonlinear adaptive control law has been presented for the motion control of overhead crane. By utilizing a Lyapunov-based stability analysis, we can achieve asymptotic tracking of the crane position and stabilization of payload sway angle for an overhead crane system which is subject to both underactuation and parametric uncertainties. Comparative simulation studies have been performed to validate the proposed control algorithm. To practically validate the proposed adaptive...
The School of Electrical, Electronic and Computer Engineering at the North-West University in Potchefstroom has established an active magnetic bearing (AMB) research group called McTronX. This group provides extensive knowledge and experience in the theory and application of AMBs. By making use of the expertise contained within McTronX and the rest of the control engineering community, an adaptive controller for an AMB flywheel system is implemented. The adaptive controller is ...
Farouk Zouari; Kamel Ben Saad; Mohamed Benrejeb
This paper develops a robust adaptive control for a class of nonlinear systems using the backstepping method. The proposed robust adaptive control is a recursive method based on the Lyapunov synthesis approach. It ensures that, for any initial conditions, all the signals of the closed‐loop system are regularly bounded and the tracking errors converge to zero. The results are illustrated with simulation examples.
De Cataldo, G.; Franco, A.; Pastore, C.; Sgura, I.; Volpe, G.
The High Momentum Particle IDentification (HMPID) detector is a proximity focusing Ring Imaging Cherenkov (RICH) for charged hadron identification. The HMPID is based on liquid C 6F 14 as the radiator medium and on a 10 m 2 CsI coated, pad segmented photocathode of MWPCs for UV Cherenkov photon detection. To ensure full remote control, the HMPID is equipped with a detector control system (DCS) responding to industrial standards for robustness and reliability. It has been implemented using PVSS as Slow Control And Data Acquisition (SCADA) environment, Programmable Logic Controller as control devices and Finite State Machines for modular and automatic command execution. In the perspective of reducing human presence at the experiment site, this paper focuses on DCS evolution towards an expert and adaptive control system, providing, respectively, automatic error recovery and stable detector performance. HAL9000, the first prototype of the HMPID expert system, is then presented. Finally an analysis of the possible application of the adaptive features is provided.
Zhao, Xudong; Shi, Peng; Zheng, Xiaolong
In this paper, tracking control problems are investigated for a class of uncertain nonlinear systems in lower triangular form. First, a state-feedback controller is designed by using adaptive backstepping technique and the universal approximation ability of fuzzy logic systems. During the design procedure, a developed method with less computation is proposed by constructing one maximum adaptive parameter. Furthermore, adaptive controllers with nonsymmetric dead-zone are also designed for the systems. Then, a sampled-data control scheme is presented to discretize the obtained continuous-time controller by using the forward Euler method. It is shown that both proposed continuous and discrete controllers can ensure that the system output tracks the target signal with a small bounded error and the other closed-loop signals remain bounded. Two simulation examples are presented to verify the effectiveness and applicability of the proposed new design techniques. PMID:26208376
El Fadil, H.; Giri, F.; Guerrero, Josep M.
This paper deals with the problem of controlling energy generation systems including fuel cells (FCs) and interleaved boost power converters. The proposed nonlinear adaptive controller is designed using sliding mode control (SMC) technique based on the system nonlinear model. The latter accounts...... for the boost converter large-signal dynamics as well as for the fuel-cell nonlinear characteristics. The adaptive nonlinear controller involves online estimation of the DC bus impedance ‘seen’ by the converter. The control objective is threefold: (i) asymptotic stability of the closed loop system......, (ii) output voltage regulation under bus impedance uncertainties and (iii) equal current sharing between modules. It is formally shown, using theoretical analysis and simulations, that the developed adaptive controller actually meets its control objectives....
Zhang Tianping; Mei Jiandong
The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconnections is studied in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks, a design scheme of decentralized direct adaptive sliding mode controller is proposed. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the weights and sliding mode gains on-line for each subsystem using only local information. According to the Lyapunov method, the closed-loop adaptive control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed approach.
An adaptive fuzzy sliding mode strategy is developed for the generalized projective synchronization of a fractional-order chaotic system, where the slave system is not necessarily known in advance. Based on the designed adaptive update laws and the linear feedback method, the adaptive fuzzy sliding controllers are proposed via the fuzzy design, and the strength of the designed controllers can be adaptively adjusted according to the external disturbances. Based on the Lyapunov stability theorem, the stability and the robustness of the controlled system are proved theoretically. Numerical simulations further support the theoretical results of the paper and demonstrate the efficiency of the proposed method. Moreover, it is revealed that the proposed method allows us to manipulate arbitrarily the response dynamics of the slave system by adjusting the desired scaling factor λi and the desired translating factor ηi, which may be used in a channel-independent chaotic secure communication. (general)
Yan Ren; Zhenghua Liu; Le Chang; Nuan Wen
A structure mode of virtual compound-axis servo system is proposed to improve the tracking accuracy of the ordinary optoelectric tracking platform. It is based on the structure and principles of compound-axis servo system. A hybrid position control scheme combining the PD controller and feed-forward controller is used in subsystem to track the tracking error of the main system. This paper analyzes the influences of the equivalent disturbance in main system and proposes an adaptive sliding mod...
Chen Weisheng; Li Junmin
For a class of unknown nonlinear time-delay systems, an adaptive neural network (NN) control design approach is proposed. Backstepping, domination and adaptive bounding design technique are combined to construct a robust memoryless adaptive NN tracking controller. Unknown time-delay functions are approximated by NNs, such that the requirement on the nonlinear time-delay functions is relaxed. Based on Lyapunov-Krasoviskii functional, the sem-global uniformly ultimately boundedness (UUB) of all the signals in the closed-loop system is proved. The arbitrary output tracking accuracy is achieved by tuning the design parameters. The feasibility is investigated by an illustrative simulation example.
Full Text Available The trajectory tracking of underactuated nonlinear system with two degrees of freedom is tackled by an adaptive fuzzy hierarchical sliding mode controller. The proposed control law solves the problem of coupling using a hierarchical structure of the sliding surfaces and chattering by adopting different reaching laws. The unknown system functions are approximated by fuzzy logic systems and free parameters can be updated online by adaptive laws based on Lyapunov theory. Two comparative studies are made in this paper. The first comparison is between three different expressions of reaching laws to compare their abilities to reduce the chattering phenomenon. The second comparison is made between the proposed adaptive fuzzy hierarchical sliding mode controller and two other control laws which keep the coupling in the underactuated system. The tracking performances of each control law are evaluated. Simulation examples including different amplitudes of external disturbances are made.
A. H. Tahoun
Full Text Available The insertion of data network in the feedback adaptive control loops makes the analysis and design of networked control systems more complex than traditional control systems. This paper addresses the adaptive stabilization problem of linear time-invariant networked control systems when the measurements of the plant states are corrupted by bounded disturbances. The case of state feedback is treated in which only an upper bound on the norm of matrix A is needed. The problem is to find an upper bound on the transmission period h that guarantees the stability of the overall adaptive networked control system under an ideal transmission process, i.e. no transmission delay or packet dropout. Rigorous mathematical proofs are established, that relies heavily on Lyapunov's stability criterion and dead-zone Technique. Simulation results are given to illustrate the efficacy of our design approach.
Xia, Dunzhu; Hu, Yiwei; Ni, Peizhen
In this work we investigate the possibility of applying the adaptive control algorithm to Micro-Electro-Mechanical System (MEMS) gyroscopes. Through comparing the gyroscope working conditions with the reference model, the adaptive control method can provide online estimation of the key parameters and the proper control strategy for the system. The digital second-order oscillators in the reference model are substituted for two phase locked loops (PLLs) to achieve a more steady amplitude and frequency control. The adaptive law is modified to satisfy the condition of unequal coupling stiffness and coupling damping coefficient. The rotation mode of the gyroscope system is considered in our work and a rotation elimination section is added to the digitalized system. Before implementing the algorithm in the hardware platform, different simulations are conducted to ensure the algorithm can meet the requirement of the angular rate sensor, and some of the key adaptive law coefficients are optimized. The coupling components are detected and suppressed respectively and Lyapunov criterion is applied to prove the stability of the system. The modified adaptive control algorithm is verified in a set of digitalized gyroscope system, the control system is realized in digital domain, with the application of Field Programmable Gate Array (FPGA). Key structure parameters are measured and compared with the estimation results, which validated that the algorithm is feasible in the setup. Extra gyroscopes are used in repeated experiments to prove the commonality of the algorithm. PMID:26959019
Full Text Available The analitycal review of the possible usage on board any vehicle modern scanner-adapters which allows to get information for organize in the control system of the rolling stock technical state in conditions of the radical transformation of the existant control system of the automobile transport is offered.
We are engaged in solving two difficult problems in adaptive control of the large-scale time-variant aerospacesystem. One is parameter identification of time-variant continuous-time state-space model; the other is how to solvealgebraic Riccati equation(ARE) of large order efficiently. In our approach, two neural networks are employed toindependently solve both the system identification problem and the ARE associated with the optimal control problem.Thus the identification and the control computation are combined in closed-loop, adaptive, real-time control system . Theadvantage of this approach is that the neural networks converge to their solutions very quickly and simultaneously.
Pilipenko, A. V.; Pilipenko, A. P.; Kanatnikov, N. V.
In this paper, the authors highlight the problem of replacing an old heavy industrial equipment, and offer the replacement of obsolete control systems on the modern adaptive control system, which takes into account changes in the hydraulic system of the press and compensates them with a corrective action. The proposed system can reduce a water hammer and thereby increase the durability of the hydraulic system and tools.
Based on the Lorenz chaotic system, this paper constructs a new four-dimensional hyperchaotic Lorenz system, and studies the basic dynamic behaviours of the system. The Routh—Hurwitz theorem is applied to derive the stability conditions of the proposed system. Furthermore, based on Lyapunov stability theory, an adaptive controller is designed and the new four-dimensional hyperchaotic Lorenz system is controlled at equilibrium point. Numerical simulation results are presented to illustrate the effectiveness of this method. (general)
Hu, Yonghao; Song, Xueping; Li, Bangjun; Shi, Liping
For a class of nonlinear systems with dynamic uncertainties, adaptive stabilization problem is considered in the rate gyroscope of stable platform system. Since the uncertainties are inevitable in the practical model of systems, the robust property of the systems in the presence of parametric uncertainties is important to be considered, such as modeling error, external disturbances, etc. Due to the strong nonlinearity and coupling characteristic of systems, it is difficult to obtain the precise model, and the nonlinearity cannot be cancelled exactly so that the controller performs badly. Adaptive control (AC) can adapt to parameter variations, but it is not applicable to the transition phase. A way to optimize the overall disturbances rejection performance of the AC system in the presence of unknown external disturbances existing in the stable platform system is provided in this paper. According to the construction of stable platform system based on gyroscope stabilized platform, the coordinate systems related to stable platform system are defined, and its mathematical model of stabilized platform is build up. Using the SIMULINK of MATLAB, the model is applied to the computer simulation of the stable platform system with good results. The author designed the control law of velocity-loop respective with the method of continuous correcting net and the AC. The simulation results show that the designed adaptive control law can satisfy the required criterion, it proves that the design method is feasible. In order to compare the above two method efficiently, the author gives the seeker system step response, square wave response especially. Adaptive control law is confirmed to give better tracking performance compared with correcting net control, and a control precision comparable to seeker system and higher robustness to parameter change, despite the simple controller. The research results ensure a wider application of simple AC in real mechanical systems.
Full Text Available This paper proposes adaptive sliding mode control design for a class of fractional commensurate order chaotic systems. We firstly introduce a fractional integral sliding manifold for the nominal systems. Secondly we prove the stability of the corresponding fractional sliding dynamics. Then, by introducing a Lyapunov candidate function and using the Mittag-Leffler stability theory we derive the desired sliding control law. Furthermore, we prove that the proposed sliding manifold is also adapted for the fractional systems in the presence of uncertainties and external disturbances. At last, we design a fractional adaptation law for the perturbed fractional systems. To verify the viability and efficiency of the proposed fractional controllers, numerical simulations of fractional Lorenz’s system and Chen’s system are presented.
Chuntao LI; Yonghong TAN
An adaptive control scheme is presented for systems with unknown hysteresis. In order to handle the case where the hysteresis output is unmeasurale, a novel model is firstly developed to describe the characteristic of hysteresis. This model is motivated by Preisach model but implemented by using neural networks (NN). The main advantage is that it is easily used for controller design. Then, the adaptive controller based on the proposed model is presented for a class of SISO nonlinear systems preceded by unknown hysteresis, which is estimated by the proposed model. The laws for model updating and the control laws for the neural adaptive controller are derived from Lyapunov stability theorem, therefore the semi- global stability of the closed-loop system is guaranteed. At last, the simulation results are illustrated.
Long, Lijun; Zhao, Jun
This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed. PMID:25122844
An adaptive fuzzy method with terminal attractor based on input-output linearization for a class of uncertain chaos systems is presented. It controls the strong nonlinear chaos systems validly and rapidly for introducing the concept of terminal attractors that has the properties of stability and fast convergence. Global stability of the controller is established. Two kinds of chaos systems are controlled by using this approach. The results of simulation demonstrate the validity and rapidity of the method
C Narendra, Nanjangud
With increasing numbers of organizations automating their business processes by using workflow systems, security aspects of workflow systems has become a heavily researched area. Also, most workflow processes nowadays need to be adaptive, i.e., constantly changing, to meet changing business conditions. However, little attention has been paid to integrating Security and Adaptive Workflow. In this paper, we investigate this important research topic, with emphasis on Role Based Access Control (R...
In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment
An indirect adaptive fuzzy control scheme is developed for a class of nonlinear discrete-time systems. In this method, two fuzzy logic systems are used to approximate the unknown functions, and the parameters of membership functions in fuzzy logic systems are adjusted according to adaptive laws for the purpose of controlling the plant to track a reference trajectory. It is proved that the scheme can not only guarantee the boundedness of the input and output of the closed-loop system, but also make the tracking error converge to a small neighborhood of the origin. Simulation results indicate the effectiveness of this scheme.
Ahmad A.M. Faudzi
Full Text Available Problem statement: Communication and control are two main components in any Mechatronics system. They can be designed either by centralized or decentralized approach. Both approaches can be chosen based on application designed and specific requirements of the designer. In this study, decentralized or normally called distributed approach was selected to solved communication and control of a human adaptive mechanical system namely Intelligent Chair Tools (ICT. The ICT seating system is powered by thirty six intelligent pneumatic actuators to facilitate investigation of chair shapes from spring and damping effect of seating and backrest surface. Three studies are proposed from the sitting experiments namely chair shapes, chair spring and chair damping properties. Approach: PSoC microcontroller was selected based on its features of having configurable analog and digital blocks. Its flexible modules and programmable peripherals ease designer in designing the communication and control of ICT in improved and faster way. Three protocols of USB, SPI and I2C were used for the communication system of ICT using PSoC. Flow charts of each communication protocols algorithms were discussed. On the other hand, the control system used PSoCs ADC and counter modules to read inputs of pressure and encoder respectively. PWM module is used to control the valve and data communication was achieved using I2C module. Block diagram of unified control was discussed for further understandings of the control algorithms. Results: The PSoC specification, development design and experimental evaluation of ICT system are presented and discussed. Three studies of chair shapes, chair spring property and chair damping property from sitting experiment were shown. Conclusion/Recommendations: The PSoC microcontroller selection was discussed and application of its distributed communication and control was successfully applied to ICT. This distributed approach can be applied to other
Hu, Yunan; Jin, Yuqiang; Li, Jing
Based on fully tuned RBF neural networks and backstepping control techniques, a novel nonlinear adaptive control scheme is proposed for missile control systems with a general set of uncertainties. The effect of the uncertainties is synthesized one term in the design procedure. Then RBF neural networks are used to eliminate its effect. The nonlinear adaptive controller is designed using backstepping control techniques. The control problem is resolved while the control coefficient matrix is unknown. The adaptive tuning rules for updating all of the parameters of the fully tuned RBF neural networks are firstly derived by the Lyapunov stability theorem. Finally, nonlinear 6-DOF numerical simulation results for a BTT missile model are presented to demonstrate the effectiveness of the proposed method.
Large-scale power cuts in both North America and Europe emphasised the need to maintain an adequate supply of high-quality electricity. This book offers information on the relatively low-cost of doing so using self-regulating control mechanisms. It is of interest to the practising power/control engineer and to academics needing industrial inputs.
Mirkin, Boris; Gutman, Per-Olof
In this paper, we develop a model reference adaptive control scheme for a class of multi-input multi-output nonlinearly perturbed dynamic systems with unknown time-varying state delays which is also robust with respect to an external disturbance with unknown bounds. The output feedback adaptive control scheme uses feedback actions only, and thus does not require a direct measurement of the command or disturbance signals. A suitable Lyapunov-Krasovskii type functional is introduced to design the adaptation algorithms and to prove stability.
Nasirian, Vahidreza; Davoudi, Ali; Lewis, Frank;
the local perunit current of each converter with the neighbors’ on a communication graph and, accordingly, provides an impedance correction term. This term is then used to update the droop coefficient and synchronize per-unit currents or, equivalently, provide proportional load sharing. The proposed...... controller precisely accounts for the transmission/distribution line impedances. The controller on each converter exchanges data with only its neighbor converters on a sparse communication graph spanned across the Microgrid. Global dynamic model of the Microgrid is derived, with the proposed controller...
Jie Tian; Wei Feng; Yuzhen Wang
The main purpose of this paper is to apply stochastic adaptive controller design to mechanical system. Firstly, by a series of coordinate transformations, the mechanical system can be transformed to a class of special high-order stochastic nonlinear system, based on which, a more general mathematical model is considered, and the smooth state-feedback controller is designed. At last, the simulation for the mechanical system is given to show the effectiveness of the design scheme.
HU Tingliang; ZHU Jihong; SUN Zengqi
In this paper we present a robust adaptive control for a class of uncertain continuous time multiple input multiple output (MIMO) nonlinear systems. Multiple multi-layer neural networks are employed to approximate the uncertainty of the nonlinear functions,and robustifying control terms are used to compensate for approximation errors.All parameter adaptive laws and robustifying control terms are derived based on Lyapunov stability analysis so that, under appropriate assumptions, semiglobal stability of the closed - loop system is guaranteed, and the tracking error asymptotically converges to zero. Simulations performed on a two-link robot manipulator illustrate the approach and its performance.
WANG Wenqing; HAN Chongzhao
A new method for designing decentralized adaptive robust controllers was proposed which focuses on a class of more general uncertain complex systems,using the concept of the partition of unity in differential geometry to deal with system uncertainties.In this method the uncertainty of the system to be controlled was normalized firstly,and then the partition of unity that was subordinated to an open covering of state variables compact set was constructed.Subsequently the approximation was realized by using its property that can approximate nonlinear continuous function with arbitrary precision,and then the decentralized adaptive robust controller of complex systems and adaptive laws of approximate parameter estimation were designed.Compared to existing methods,the proposed algorithm requires simpler assumed conditions and no complicated computations.Simulation result shows that the method is valid.
A novel observer-base output feedback variable universe adaptive fuzzy controller is investigated in this paper. The contraction and expansion factor of variable universe fuzzy controller is on-line tuned and the accuracy of the system is improved. With the state-observer, a novel type of adaptive output feedback control is realized. A supervisory controller is used to force the states to be within the constraint sets. In order to attenuate the effect of both external disturbance and variable parameters on the tracking error and guarantee the states to be within the constraint sets, a robust controller is appended to the variable universe fuzzy controller. Thus, the robustness of system is improved. By Lyapunov method, the observer-controller system is shown to be stable. The overall adaptive control algorithm can guarantee the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded. In the paper, we apply the proposed control algorithms to control the Duffing chaotic system and Chua's chaotic circuit. Simulation results confirm that the control algorithm is feasible for practical application
Full Text Available This paper deals with the problems of “explosion of term,” uncertain parameter in static synchronous compensator (STATCOM system with nonlinear time-delay. An improved adaptive controller is proposed to enhance the transient stability of system states and reduce computational complexity of STATCOM control system. In contrast to backstepping control scheme in high order systems, the problem of “explosion of term” is avoided by designing dynamic surface controller. The low pass filter is included to allow a design where the model is not differentiated and thus has prevented the mathematical complexities effectively. In addition, unlike the traditional adaptive control schemes, the certainty equivalence principle is not required for estimating the uncertain parameter by system immersion and manifold invariant (I&I adaptive control. A smooth function is added to ensure that the estimation error converges to zero in finite time. The effectiveness of the proposed controller is verified by the simulations. Compared with adaptive backstepping and proportion integration differentiation (PID, the oscillation amplitudes of transient response are reduced by nearly half, and the time of reaching steady state is shortened by at least 11%.
Full Text Available In this study, a composite adaptive sliding mode control using Multiple Models (MM-CASMC is proposed for precision position control of an induction motor servo system with parametric uncertainties and external disturbance. The MM-CASMC is designed based on a classical sliding mode control frame. Robustness against parametric uncertainties and high-frequency extern disturbance are both obtained via online parameters estimation and switching control, respectively. A composite adaption law which combines direct and BGF-LS type indirect adaptive methods is developed to achieve both Globally Uniformly Ultimately Boundness (GUUB and approximately exponential convergence in large range under persistent excitation, the later implies clearer transient behaviour which is of great importance but not provided by standard direct adaptive method. Moreover, a multiple model adaptive control design is further incorporated to achieve improvement in transient response by utilizing model switching and parameters estimates resetting and an noval method by means of dual-channel filtering is proposed for regessor filtering and model switching. For the proposed strategy, the GUUB stability and improvments in transient behaviour and adaptability to sudden changes in the parameter values are all proved in Lyapunov sense. Simulation results verify that an induction motor servo system with the adoption of MM-CASMC can achieve favorable tracking performance and transient response in the presence of parameter variations and external load disturbance.
Ying-Chung Wang; Chiang-Ju Chien
An observer-based adaptive iterative learning control using a filtered fuzzy neural network is proposed for repetitive tracking control of robotic systems. A state tracking error observer is introduced to design the iterative learning controller using only the measurement of joint position. We first derive an observation error model based on the state tracking error observer. Then, by introducing some auxiliary signals, the iterative learning controller is proposed based on the use of an aver...
Fang, H.; Quijano, U.; Bach, V.; Hill, J.; Wang, K. W.
Due to their ultra lightweight and high packaging efficiency, membrane reflectors are getting more and more attentions for mission architectures that need extremely large inspace deployable antennas. However how to maintain the surface shape of a membrane reflector to the instrument precision requirements is a very challenging problem. This experimental study investigated using PVDF membrane piezoelectric material as actuators to control the surface figures of membrane reflectors. The feasibility of this approach is demonstrated by several sets of test results.
Rasmussen, Henrik,; Larsen, Lars F. S.
In a refrigeration process heat is absorbed in an evaporator by evaporating a flow of liquid refrigerant at low pressure and temperature. Controlling the evaporator inlet valve and the compressor in such a way that a high degree of liquid filling in the evaporator is obtained at all compressor capacities ensures a high energy efficiency. The level of liquid filling is indirectly measured by the superheat. Introduction of variable speed compressors and electronic expansion valves enables the u...
In this paper, we study chaos (lag) synchronization of a new LC chaotic system, which can exhibit not only a two-scroll attractor but also two double-scroll attractors for different parameter values, via three types of state feedback controls: (i) linear feedback control; (ii) adaptive feedback control; and (iii) a combination of linear feedback and adaptive feedback controls. As a consequence, ten families of new feedback control laws are designed to obtain global chaos lag synchronization for τ < 0 and global chaos synchronization for τ = 0 of the LC system. Numerical simulations are used to illustrate these theoretical results. Each family of these obtained feedback control laws, including two linear (adaptive) functions or one linear function and one adaptive function, is added to two equations of the LC system. This is simpler than the known synchronization controllers, which apply controllers to all equations of the LC system. Moreover, based on the obtained results of the LC system, we also derive the control laws for chaos (lag) synchronization of another new type of chaotic system
Full Text Available A systematic controller design and implementation for a matrix-converter-based induction motor drive system is proposed. A nonlinear adaptive backstepping controller is proposed to improve the speed and position responses of the induction motor system. By using the proposed adaptive backstepping controller, the system can track a time-varying speed command and a time-varying position command well. Moreover, the system has a good load disturbance rejection capability. The realization of the controller is very simple. All of the control loops, including the current loop, speed loop and position loop, are implemented by a digital signal processor. Several experimental results are given to validate the theoretical analysis.
Boutalis, Yiannis; Kottas, Theodore; Christodoulou, Manolis A
Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering s...
Cong, Shuang; Liang, Yanyang; Shang, Weiwei
In this chapter, two sliding mode adaptive control strategies have been proposed for SISO and SIMO systems with unknown bound time-varying uncertainty respectively. Firstly, for a typical SISO system of position tracking in DC motor with unknown bound time-varying dead
Ahmad, Israr, E-mail: firstname.lastname@example.org; Saaban, Azizan Bin, E-mail: email@example.com; Ibrahim, Adyda Binti, E-mail: firstname.lastname@example.org [School of Quantitative Sciences, College of Arts & Sciences, UUM (Malaysia); Shahzad, Mohammad, E-mail: email@example.com [College of Applied Sciences Nizwa, Ministry of Higher Education, Sultanate of Oman (Oman)
This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme.
Ahmad, Israr; Saaban, Azizan Bin; Ibrahim, Adyda Binti; Shahzad, Mohammad
This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme.
This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme
Jiang Changsheng; Zhang Chunyu; Zhu Liang
A robust adaptive trajectory linearization control (RATLC) algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.
Larson, Richard R.; Burken, John J.; Butler, Bradley S.; Yokum, Steve
The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) is used to test and develop these algorithms. Modifications to this airplane include adding canards and changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals include demonstration of revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions and advancement of neural-network-based flight control technology for new aerospace system designs. This report presents an overview of the processes utilized to develop adaptive controller algorithms during a flight-test program, including a description of initial adaptive controller concepts and a discussion of modeling formulation and performance testing. Design finalization led to integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness; these are also discussed.
Full Text Available An adaptive robust fault tolerant control approach is proposed for a class of uncertain nonlinear systems with unknown signs of high-frequency gain and unmeasured states. In the recursive design, neural networks are employed to approximate the unknown nonlinear functions, K-filters are designed to estimate the unmeasured states, and a dynamical signal and Nussbaum gain functions are introduced to handle the unknown sign of the virtual control direction. By incorporating the switching function σ algorithm, the adaptive backstepping scheme developed in this paper does not require the real value of the actuator failure. It is mathematically proved that the proposed adaptive robust fault tolerant control approach can guarantee that all the signals of the closed-loop system are bounded, and the output converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by the simulation examples.
Full Text Available In order to retrain chaotic oscillation of marine power system which is excited by periodic electromagnetism perturbation, a novel command-filtered adaptive fuzzy neural network backstepping control method is designed. First, the mathematical model of marine power system is established based on the two parallel nonlinear model. Then, main results of command-filtered adaptive fuzzy neural network backstepping control law are given. And the Lyapunov stability theory is applied to prove that the system can remain closed-loop asymptotically stable with this controller. Finally, simulation results indicate that the designed controller can suppress chaotic oscillation with fast convergence speed that makes the system return to the equilibrium point quickly; meanwhile, the parameter which induces chaotic oscillation can also be discriminated.
Chen, Mou; Tao, Gang
In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems. PMID:26340792
Abedini, Mohammad; Nojoumian, Mohammad Ali; Salarieh, Hassan; Meghdari, Ali
In this paper, model reference control of a fractional order system has been discussed. In order to control the fractional order plant, discrete-time approximation methods have been applied. Plant and reference model are discretized by Grünwald-Letnikov definition of the fractional order derivative using "Short Memory Principle". Unknown parameters of the fractional order system are appeared in the discrete time approximate model as combinations of parameters of the main system. The discrete time MRAC via RLS identification is modified to estimate the parameters and control the fractional order plant. Numerical results show the effectiveness of the proposed method of model reference adaptive control.
The present paper addresses the problem of synchronization for the uncertain novel chaotic system (Qi system). Based on the Lyapunov stability theory and Barbalat's lemma, an adaptive controller is proposed via only one scalar feedback to make the states of two identical Qi systems with unknown parameters asymptotically synchronized. Furthermore, all the unknown parameters can be estimated dynamically from the time series of the drive and response systems. Numerical simulations demonstrate the validity and feasibility of the proposed method.
Sornmo O.; Olofsson B.; Robertsson A.; Johansson R.
This paper considers the problem of performing mid-ranging control of two closed-loop controlled systems that have internal saturations. The problem originates from previous work in machining with industrial robots, where an external compensation mechanism is used to compensate for position errors. Because of the limited workspace and the considerably higher bandwidth of the compensator, a mid-ranging control approach is proposed. An adaptive, model-based solution is presented, which is verif...
Full Text Available This paper considers an adaptive neural control for a class of outputs time-delay nonlinear systems with perturbed or no. Based on RBF neural networks, the radius basis function (RBF neural networks is employed to estimate the unknown continuous functions. The proposed control guarantees that all closed-loop signals remain bounded. The simulation results demonstrate the effectiveness of the proposed control scheme.
The paper addresses control problem for the modified projective synchronization of the Genesio-Tesi chaotic systems with three uncertain parameters. An adaptive control law is derived to make the states of two identical Genesio-Tesi systems asymptotically synchronized up to specific ratios. The stability analysis in the paper is proved using a well-known Lyapunov stability theory. A numerical simulation is presented to show the effectiveness of the proposed chaos synchronization scheme
Oh, B. J.; Jamshidi, M.; Seraji, H.
A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.
Thompson, Sarah; Davies, Misty D.; Gundy-Burlet, Karen
Adaptive flight control systems hold tremendous promise for maintaining the safety of a damaged aircraft and its passengers. However, most currently proposed adaptive control methodologies rely on online learning neural networks (OLNNs), which necessarily have the property that the controller is changing during the flight. These changes tend to be highly nonlinear, and difficult or impossible to analyze using standard techniques. In this paper, we approach the problem with a variant of compositional verification. The overall system is broken into components. Undesirable behavior is fed backwards through the system. Components which can be solved using formal methods techniques explicitly for the ranges of safe and unsafe input bounds are treated as white box components. The remaining black box components are analyzed with heuristic techniques that try to predict a range of component inputs that may lead to unsafe behavior. The composition of these component inputs throughout the system leads to overall system test vectors that may elucidate the undesirable behavior
Full Text Available In this study an Adaptive Neuro Fuzzy Inference System is introduced to select the switching states of Matrix Converters. Matrix converters have received more attention in research and industrial application due its advantages like four quadrant operation, sinusoidal input and output waveforms, controllable displacement factor, less number of switches etc., Matrix Converters are efficient in speed control of Induction motors than the conventional converters. There are two different control techniques namely field oriented control and Direct Torque Control systems available for closed loop operation of induction motors. The Direct Torque Control technique provides control of torque and flux directly. The major drawback of Direct Torque Control technique is the presence of ripples in torque and flux curves. This due to the presence of two level and three level hysteresis controllers in torque and flux control stages respectively. Also the conventional space vector and look up table method of switching state selection reduces the accuracy of switch state selection in the appropriate time width. This reduces the speed control performance of the motor. Also in this paper the hysteresis controllers are replaced by fuzzy controllers. the complete ANFIS based DTC for Matrix Converter is simulated in MATLAB/SIMULINK and the results shows that the use of Adaptive neuro fuzzy inference in Matrix Converter system increases the speed control performance of Induction Motor.
Full Text Available This paper presents a new hyperchaotic system by introducing an additional state variable into Lorenz system. The system’s characteristics, including the dissipativity, equilibrium, and Lyapunov exponents, are studied. A controller is developed which consists of an active control term and a variable universe adaptive fuzzy system. By using this controller, the synchronization of the new hyperchaotic systems with uncertain linear part is accomplished according to Lyapunov’s direct method. Simulation results illustrate the effectiveness of the proposed method.
ZHURong-gang; JIANGChangsheng; FENGBin
A discussion is devoted to the design of an adaptive flight control system of the armed helicopter using wavelet neural network method. Firstly, the control loop of the attitude angle is designed with a dynamic inversion scheme in a quick loop and a slow loop. respectively. Then, in order to compensate the error caused by dynamic inversion, the adaptive flight control system of the armed helicopter using wavelet neural network method is put forward, so the BP wavelet neural network and the Lyapunov stable wavelet neural network are used to design the helicopter flight control system. Finally, the typical maneuver flight is simulated to demonstrate its validity and effectiveness. Result proves that the wavelet neural network has an engineering practical value and the effect of WNN is good.
Wang, Ning; Er, Meng Joo; Sun, Jing-Chao; Liu, Yan-Cheng
In this paper, a novel adaptive robust online constructive fuzzy control (AR-OCFC) scheme, employing an online constructive fuzzy approximator (OCFA), to deal with tracking surface vehicles with uncertainties and unknown disturbances is proposed. Significant contributions of this paper are as follows: 1) unlike previous self-organizing fuzzy neural networks, the OCFA employs decoupled distance measure to dynamically allocate discriminable and sparse fuzzy sets in each dimension and is able to parsimoniously self-construct high interpretable T-S fuzzy rules; 2) an OCFA-based dominant adaptive controller (DAC) is designed by employing the improved projection-based adaptive laws derived from the Lyapunov synthesis which can guarantee reasonable fuzzy partitions; 3) closed-loop system stability and robustness are ensured by stable cancelation and decoupled adaptive compensation, respectively, thereby contributing to an auxiliary robust controller (ARC); and 4) global asymptotic closed-loop system can be guaranteed by AR-OCFC consisting of DAC and ARC and all signals are bounded. Simulation studies and comprehensive comparisons with state-of-the-arts fixed- and dynamic-structure adaptive control schemes demonstrate superior performance of the AR-OCFC in terms of tracking and approximation accuracy. PMID:26219099
Agapito, G.; Quiros-Pacheco, F.; Tesi, P.; Esposito, S.; Xompero, M.
In this paper we will discuss the application of different optimal control techniques for the adaptive optics system of the LBT telescope which comprises a pyramid wavefront sensor and an adaptive secondary mirror. We have studied the application of both the Kalman and the H∞ filter to estimate the temporal evolution of the phase perturbations due to the atmospheric turbulence and the telescope vibrations. We have evaluated the performance of these control techniques with numerical simulations in preparation of the laboratory tests that will be carried out in the Arcetri laboratories.
Klenk, W. J.
An adaptive load relief control system for a SATURN type vehicle which significantly reduces aerodynamically induced structural loads without incurring excessive velocity dispersions has been studied. This control system utilizes pendulous accelerometers to measure the angle between the total vehicle acceleration vector and the vehicle body. This measurement is used to fly the vehicle along the nominal trajectory to minimize velocity dispersions. However, if unusually high values of wind velocity are encountered, the system will cause the vehicle to turn into the wind to reduce the lateral structural loads. Results of an anal6g computer study show that the adaptive system can reduce aerodynam3cally induced peak structural loads as much as 50 percent under those encountered using conventional control techniques. relief is used only when required, velocity dispersions are held to a minimum.
WANG Dong-dong; WANG Ya-lin; MA Tao
To resolve the control adaptability problem of TV media in complex competitive environment, a con-trol system model of TV media organization structure was designed. Based on the designed system model for TV media organization structure, the relations among the main factors of the system constitution, missions, organi-zing decision entity, and carrying bodies were analyzed. By means of applying multi-objective decision method and complex control system theory, and combining the integration model of TV media organization structure, the basic model was concluded and the corresponding parameters were designed. The current organization process of TV media is analyzed by this model, which comes to the adaptability appearance with different parameters. The results indicate that the model can estimate current TV media organization structure for the chain appearance of communications and the correlation between platforms and policy-making agencies.
Vrabie, Draguna; Lewis, Frank
In this paper we present in a continuous-time framework an online approach to direct adaptive optimal control with infinite horizon cost for nonlinear systems. The algorithm converges online to the optimal control solution without knowledge of the internal system dynamics. Closed-loop dynamic stability is guaranteed throughout. The algorithm is based on a reinforcement learning scheme, namely Policy Iterations, and makes use of neural networks, in an Actor/Critic structure, to parametrically represent the control policy and the performance of the control system. The two neural networks are trained to express the optimal controller and optimal cost function which describes the infinite horizon control performance. Convergence of the algorithm is proven under the realistic assumption that the two neural networks do not provide perfect representations for the nonlinear control and cost functions. The result is a hybrid control structure which involves a continuous-time controller and a supervisory adaptation structure which operates based on data sampled from the plant and from the continuous-time performance dynamics. Such control structure is unlike any standard form of controllers previously seen in the literature. Simulation results, obtained considering two second-order nonlinear systems, are provided. PMID:19362449
The present study aims at numerically investigating the feasibility of an adaptive TMD control system applied on lightweight, flexible structures characterized by time-varying inertial properties. The case study will consist of a photovoltaic support structure subject to snow drifting and slippage in windy conditions.
An anti-synchronization scheme is proposed to achieve the anti-synchronization behavior between chaotic systems with fully unknown parameters. A sliding surface and an adaptive sliding mode controller are designed to gain the anti-synchronization. The stability of the error dynamics is proven theoretically using the Lyapunov stability theory. Finally numerical results are presented to justify the theoretical analysis
Anil Kumar Yadav; Prerna Gaur
The objective of this paper is to design an autopilot system for unmanned aerial vehicle (UAV) to control the speed and altitude using electronic throttle control system (ETCS) and elevator, respectively. A DC servo motor is used for designing of ETCS to control the throttle position for appropriate amount of air mass flow. Artificial Intelligence (AI)-based controllers such as fuzzy logic PD, fuzzy logic PD + I, self-tuning fuzzy logic PID (STF-PID) controller and fuzzy logic-based sliding mode adaptive controller (FLSMAC) are designed for stable autopilot system and are compared with conventional PI controller. The target of throttle, speed and altitude controls are to achieve a wide range of air speed, improved energy efficiency and fuel economy with reduced pollutant emission. The energy efficiency using specific energy rate per velocity of UAV is also presented in this paper.
This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.
Huang, Shiuh-Jer; Chen, Hung-Yi
In this paper, an adaptive sliding controller is developed for controlling a vehicle active suspension system. The functional approximation technique is employed to substitute the unknown non-autonomous functions of the suspension system and release the model-based requirement of sliding mode control algorithm. In order to improve the control performance and reduce the implementation problem, a fuzzy strategy with online learning ability is added to compensate the functional approximation error. The update laws of the functional approximation coefficients and the fuzzy tuning parameters are derived from the Lyapunov theorem to guarantee the system stability. The proposed controller is implemented on a quarter-car hydraulic actuating active suspension system test-rig. The experimental results show that the proposed controller suppresses the oscillation amplitude of the suspension system effectively.
Rodriguez, Guillermo (Editor)
Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.
Yin, Shen; Shi, Peng; Yang, Hongyan
In this paper, an approximated-based adaptive fuzzy control approach with only one adaptive parameter is presented for a class of single input single output strict-feedback nonlinear systems in order to deal with phenomena like nonlinear uncertainties, unmodeled dynamics, dynamic disturbances, and unknown time delays. Lyapunov-Krasovskii function approach is employed to compensate the unknown time delays in the design procedure. By combining the advances of the hyperbolic tangent function with adaptive fuzzy backstepping technique, the proposed controller guarantees the semi-globally uniformly ultimately boundedness of all the signals in the closed-loop system from the mean square point of view. Two simulation examples are finally provided to show the superior effectiveness of the proposed scheme. PMID:26302525
Xiujuan Dong; Shengtao Li; Nan Jiang; Yuanwei Jing
Transient stability problem for multi-machine infinite bus system with the generator excitation was addressed via the non-certainty equivalent nonlinear re-parameterization method. The system need not to be linearized. The damping coefficient uncertainty was considered. A non-certainty equivalent excitation controller and a novel parameter updating law were obtained simultaneously via adaptive backstepping and Lyapunov methods to achieve stability of the error systems. Simulation results show...
Wu, J.; Yokoyama, A. [Tokyo Univ., Tokyo (Japan); Lu, Q. [TsingHua Univ., Tsinghua (China); Goto, M. [Nagoya Univ., Nagoya (Japan); Konishi, H. [Hitachi Ltd. (Japan)
Decentralised nonlinear control of generator excitation and turbine governor based on the feedback linearization approach is proposed. To make the proposed nonlinear control possess adaptive ability under the changing conditions of power systems, the extended observation decoupled state space in which mechanical power is considered as variable is proposed, and the local stability of the post fault equilibrium point is established rigorously from a mathematical viewpoint. Nonlinear simulations are performed in a three-machine power system and in the ten-machine West Japan power system, and the effectiveness of the proposed nonlinear control and the convergence characteristics of the post fault equilibrium point observer are validated. (Author)
Full Text Available First, this paper announces a seven-term novel 3-D conservative chaotic system with four quadratic nonlinearities. The conservative chaotic systems are characterized by the important property that they are volume conserving. The phase portraits of the novel conservative chaotic system are displayed and the mathematical properties are discussed. An important property of the proposed novel chaotic system is that it has no equilibrium point. Hence, it displays hidden chaotic attractors. The Lyapunov exponents of the novel conservative chaotic system are obtained as L1 = 0.0395,L2 = 0 and L3 = −0.0395. The Kaplan-Yorke dimension of the novel conservative chaotic system is DKY =3. Next, an adaptive controller is designed to globally stabilize the novel conservative chaotic system with unknown parameters. Moreover, an adaptive controller is also designed to achieve global chaos synchronization of the identical conservative chaotic systems with unknown parameters. MATLAB simulations have been depicted to illustrate the phase portraits of the novel conservative chaotic system and also the adaptive control results.
LI Hong; ZHOU Zhiyuan; DAI Rongyang; LUO Bo; ZHENG Xiaoli; YANG Wenli; HE Tao; WU Minglu
In cells, the interactions of distinct signaling transduction pathways originating from cross-talkings between signaling molecules give rise to the formation of signaling transduction networks, which contributes to the changes (emergency) of kinetic behaviors of signaling system compared with single molecule or pathway. Depending on the known experimental data, we have constructed a model for complex cellular signaling transduction system, which is derived from signaling transduction of epidermal growth factor receptor in neuron. By the computational simulating methods, the self-adaptive controls of this system have been investigated. We find that this model exhibits a relatively stable selfadaptive system, especially to over-stimulation of agonist, and the amplitude and duration of signaling intermediates in it could be controlled by multiple self-adaptive effects, such as "signal scattering", "positive feedback", "negative feedback" and "B-Raf shunt". Our results provide an approach to understanding the dynamic behaviors of complex biological systems.
Fluid power systems have been in use since 1795 with the rst hydraulic press patented by Joseph Bramah and today form the basis of many industries. Electro hydraulic servo systems are uid power systems controlled in closed-loop. They transform reference input signals into a set of movements in...... detected early and handled. Moreover, the task of controlling electro hydraulic systems for high performance operations is challenging due to the highly nonlinear behaviour of such systems and the large amount of uncertainties present in their models. This thesis focuses on nonlinear adaptive fault......-tolerant control for a representative electro hydraulic servo controlled motion system. The thesis extends existing models of hydraulic systems by considering more detailed dynamics in the servo valve and in the friction inside the hydraulic cylinder. It identies the model parameters using experimental data from a...
Zhao, Xudong; Yang, Haijiao; Karimi, Hamid Reza; Zhu, Yanzheng
In this paper, an adaptive neural output-feedback tracking controller is designed for a class of multiple-input and multiple-output nonstrict-feedback nonlinear systems with time delay. The system coefficient and uncertain functions of our considered systems are both unknown. By employing neural networks to approximate the unknown function entries, and constructing a new input-driven filter, a backstepping design method of tracking controller is developed for the systems under consideration. The proposed controller can guarantee that all the signals in the closed-loop systems are ultimately bounded, and the time-varying target signal can be tracked within a small error as well. The main contributions of this paper lie in that the systems under consideration are more general, and an effective design procedure of output-feedback controller is developed for the considered systems, which is more applicable in practice. Simulation results demonstrate the efficiency of the proposed algorithm. PMID:26099151
Singh, B.; Goel, S.
This paper presents a grid interfaced solar photovoltaic (SPV) energy system with a novel adaptive harmonic detection control for power quality improvement at ac mains under balanced as well as unbalanced and distorted supply conditions. The SPV energy system is capable of compensation of linear and nonlinear loads with the objectives of load balancing, harmonics elimination, power factor correction and terminal voltage regulation. The proposed control increases the utilization of PV infrastructure and brings down its effective cost due to its other benefits. The adaptive harmonic detection control algorithm is used to detect the fundamental active power component of load currents which are subsequently used for reference source currents estimation. An instantaneous symmetrical component theory is used to obtain instantaneous positive sequence point of common coupling (PCC) voltages which are used to derive inphase and quadrature phase voltage templates. The proposed grid interfaced PV energy system is modelled and simulated in MATLAB Simulink and its performance is verified under various operating conditions.
Nishino, Toshimasa; Fujitani, Yasuhiro; Kato, Norihiko; Tsuda, Naoaki; Nomura, Yoshihiko; Matsui, Hirokazu
The objective of this paper is to establish a technique that levitates and conveys a hand, a kind of micro-robot, by applying magnetic forces: the hand is assumed to have a function of holding and detaching the objects. The equipment to be used in our experiments consists of four pole-pieces of electromagnets, and is expected to work as a 4DOF drive unit within some restricted range of 3D space: the three DOF are corresponding to 3D positional control and the remaining one DOF, rotational oscillation damping control. Having used the same equipment, Khamesee et al. had manipulated the impressed voltages on the four electric magnetics by a PID controller by the use of the feedback signal of the hand's 3D position, the controlled variable. However, in this system, there were some problems remaining: in the horizontal direction, when translating the hand out of restricted region, positional control performance was suddenly degraded. The authors propose a method to apply an adaptive control to the horizontal directional control. It is expected that the technique to be presented in this paper contributes not only to the improvement of the response characteristic but also to widening the applicable range in the horizontal directional control.
Lewis, Frank L; Hengster-Movric, Kristian; Das, Abhijit
Task complexity, communication constraints, flexibility and energy-saving concerns are all factors that may require a group of autonomous agents to work together in a cooperative manner. Applications involving such complications include mobile robots, wireless sensor networks, unmanned aerial vehicles (UAVs), spacecraft, and so on. In such networked multi-agent scenarios, the restrictions imposed by the communication graph topology can pose severe problems in the design of cooperative feedback control systems. Cooperative control of multi-agent systems is a challenging topic for both control theorists and practitioners and has been the subject of significant recent research. Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs. It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design. B...
Man, Yongchao; Liu, Yungang
This paper addresses the global adaptive stabilisation via switching and learning strategies for a class of uncertain nonlinear systems. Remarkably, the systems in question simultaneously have unknown control directions, unknown input disturbance and unknown growth rate, which makes the problem in question challenging to solve and essentially different from those in the existing literature. To solve the problem, an adaptive scheme via switching and learning is proposed by skilfully integrating the techniques of backstepping design, adaptive learning and adaptive switching. One key point in the design scheme is the introduction of the learning mechanism, in order to compensate the unknown input disturbance, and the other one is the design of the switching mechanism, through tuning the design parameters online to deal with the unknown control directions, unknown bound and period of input disturbance and unknown growth rate. The designed controller guarantees that all the signals of the resulting closed-loop systems are bounded, and furthermore, the closed-loop system states globally converge to zero.
Marakhimov, A. R.; Igamberdiev, H. Z.; Umarov, Sh. X.
This paper considers the problem of building adaptive fuzzy-logic traffic control systems (AFLTCS) to deal with information fuzziness and uncertainty in case of heavy traffic streams. Methods of formal description of traffic control on the crossroads based on fuzzy sets and fuzzy logic are proposed. This paper also provides efficient algorithms for implementing AFLTCS and develops the appropriate simulation models to test the efficiency of suggested approach. PMID:27517081
WANG Ping; YANG Ru-qing
A self-adaptive control method is proposed basedon an artificial neural network(ANN) with acceleratedevolutionary programming(AEP.) algorithm. The neuralnetwork is used to model the uncertainty process, fromwhich the teacher signals are produced online to regulate theparameters of the controller. The accelerated evolutionaryprogramming is used to train the neural network. Theexperiment results show that the method can obviouslyimprove the dynamic performance of uncertainty systems.
An adaptive robust fault tolerant control approach is proposed for a class of uncertain nonlinear systems with unknown signs of high-frequency gain and unmeasured states. In the recursive design, neural networks are employed to approximate the unknown nonlinear functions, K-filters are designed to estimate the unmeasured states, and a dynamical signal and Nussbaum gain functions are introduced to handle the unknown sign of the virtual control direction. By incorporating the switching function...
Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai
In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.
Arpaia, Pasquale [Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Napoli (Italy); Technology Department, European Organization for Nuclear Research (CERN), 1217 Geneva (Switzerland); Ballarino, Amalia; Montenero, Giuseppe [Technology Department, European Organization for Nuclear Research (CERN), 1217 Geneva (Switzerland); Daponte, Vincenzo [Technology Department, European Organization for Nuclear Research (CERN), 1217 Geneva (Switzerland); Department of Electronics, Information, and Bioengineering, Polytechnic of Milan, 20133 Milano (Italy); Svelto, Cesare [Department of Electronics, Information, and Bioengineering, Polytechnic of Milan, 20133 Milano (Italy)
A smart monitoring system for superconducting cable test is proposed with an adaptive current control of a superconducting transformer secondary. The design, based on Fuzzy Gain Scheduling, allows the controller parameters to adapt continuously, and finely, to the working variations arising from transformer nonlinear dynamics. The control system is integrated in a fully digital control loop, with all the related benefits, i.e., high noise rejection, ease of implementation/modification, and so on. In particular, an accurate model of the system, controlled by a Fuzzy Gain Scheduler of the superconducting transformer, was achieved by an experimental campaign through the working domain at several current ramp rates. The model performance was characterized by simulation, under all the main operating conditions, in order to guide the controller design. Finally, the proposed monitoring system was experimentally validated at European Organization for Nuclear Research (CERN) in comparison to the state-of-the-art control system [P. Arpaia, L. Bottura, G. Montenero, and S. Le Naour, “Performance improvement of a measurement station for superconducting cable test,” Rev. Sci. Instrum.83, 095111 (2012)] of the Facility for the Research on Superconducting Cables, achieving a significant performance improvement: a reduction in the system overshoot by 50%, with a related attenuation of the corresponding dynamic residual error (both absolute and RMS) up to 52%.
A smart monitoring system for superconducting cable test is proposed with an adaptive current control of a superconducting transformer secondary. The design, based on Fuzzy Gain Scheduling, allows the controller parameters to adapt continuously, and finely, to the working variations arising from transformer nonlinear dynamics. The control system is integrated in a fully digital control loop, with all the related benefits, i.e., high noise rejection, ease of implementation/modification, and so on. In particular, an accurate model of the system, controlled by a Fuzzy Gain Scheduler of the superconducting transformer, was achieved by an experimental campaign through the working domain at several current ramp rates. The model performance was characterized by simulation, under all the main operating conditions, in order to guide the controller design. Finally, the proposed monitoring system was experimentally validated at European Organization for Nuclear Research (CERN) in comparison to the state-of-the-art control system [P. Arpaia, L. Bottura, G. Montenero, and S. Le Naour, “Performance improvement of a measurement station for superconducting cable test,” Rev. Sci. Instrum.83, 095111 (2012)] of the Facility for the Research on Superconducting Cables, achieving a significant performance improvement: a reduction in the system overshoot by 50%, with a related attenuation of the corresponding dynamic residual error (both absolute and RMS) up to 52%
Corley, Melissa S.
The Navy is interested in developing systems for horizontal, near ocean surface, high-energy laser propagation through the atmosphere. Laser propagation in the maritime environment requires adaptive optics control of aberrations caused by atmospheric distortion. In this research, a multichannel transverse adaptive filter is formulated in Matlab's Simulink environment and compared to a complex lattice filter that has previously been implemented in large system simulations. The adaptive fil...
Chak, Yew-Chung; Varatharajoo, Renuganth
Many spacecraft attitude control systems today use reaction wheels to deliver precise torques to achieve three-axis attitude stabilization. However, irrecoverable mechanical failure of reaction wheels could potentially lead to mission interruption or total loss. The electrically-powered Solar Array Drive Assemblies (SADA) are usually installed in the pitch axis which rotate the solar arrays to track the Sun, can produce torques to compensate for the pitch-axis wheel failure. In addition, the attitude control of a flexible spacecraft poses a difficult problem. These difficulties include the strong nonlinear coupled dynamics between the rigid hub and flexible solar arrays, and the imprecisely known system parameters, such as inertia matrix, damping ratios, and flexible mode frequencies. In order to overcome these drawbacks, the adaptive Jacobian tracking fuzzy control is proposed for the combined attitude and sun-tracking control problem of a flexible spacecraft during attitude maneuvers in this work. For the adaptation of kinematic and dynamic uncertainties, the proposed scheme uses an adaptive sliding vector based on estimated attitude velocity via approximate Jacobian matrix. The unknown nonlinearities are approximated by deriving the fuzzy models with a set of linguistic If-Then rules using the idea of sector nonlinearity and local approximation in fuzzy partition spaces. The uncertain parameters of the estimated nonlinearities and the Jacobian matrix are being adjusted online by an adaptive law to realize feedback control. The attitude of the spacecraft can be directly controlled with the Jacobian feedback control when the attitude pointing trajectory is designed with respect to the spacecraft coordinate frame itself. A significant feature of this work is that the proposed adaptive Jacobian tracking scheme will result in not only the convergence of angular position and angular velocity tracking errors, but also the convergence of estimated angular velocity to
Full Text Available The interconnected systems is continually increasing in size and extending over whole geographical regions, it is becoming increasingly more difficult to maintain synchronism between various parts of the power system. This paper work presents an advanced adaptive Particle swarm optimization technique to optimize the SVC controller parameters for enhancement of the steady state stability & overcoming the premature convergence & stagnation problems as in basic PSO algorithm & Particle swarm optimization with shrinkage factor & inertia weight approach (PSO-SFIWA. In this paper SMIB system along with PID damped SVC controller is considered for study. The generator speed deviation is used as an auxiliary signal to SVC, to generate the desired damping. This controller improves the dynamic performance of power system by reducing the steady-state error. The controller parameters are optimized using basic PSO, PSO-SFIWA & Advanced Adaptive PSO. Computational results show that Advanced Adaptive based SVC controller is able to find better quality solution as compare to conventional PSO & PSO-SFIWA Techniques.
Full Text Available A prescribed performance fuzzy adaptive output-feedback control approach is proposed for a class of single-input and single-output nonlinear stochastic systems with unmeasured states. Fuzzy logic systems are used to identify the unknown nonlinear system, and a fuzzy state observer is designed for estimating the unmeasured states. Based on the backstepping recursive design technique and the predefined performance technique, a new fuzzy adaptive output-feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin with the prescribed performance bounds. A simulation example is provided to show the effectiveness of the proposed approach.
A synchronization scheme for R?ssler system based on Dynamic Surface Control (DSC) is proposed in this paper. The DSC method is a recursive design procedure like conventional backstepping methods. Different from the backstepping design, a first-order filter is introduced in every DSC design step. For this introduced filter, the derivative of the selected virtual control is avoided and then the drawback of "explosion of complexity" existing in backstepping design is overcome. Moreover, adaptive method is used for controller design when the system parameters are unknown. Finally, a numerical example is given to illustrate the effectiveness and performance of the proposed method.
A. A. Saifizul
Full Text Available A self-erecting single inverted pendulum (SESIP is one of typical nonlinear systems. The control scheme running the SESIP consists of two main control loops. Namely, these control loops are swing-up controller and stabilization controller. A swing-up controller of an inverted pendulum system must actuate the pendulum from the stable position. While a stabilization controller must stand the pendulum in the unstable position. To deal with this system, a lot of control techniques have been used on the basis of linearized or nonlinear model. In real-time implementation, a real inverted pendulum system has state constraints and limited amplitude of input. These problems make it difficult to design a swing-up and a stabilization controller. In this paper, first, the mathematical models of cart and single inverted pendulum system are presented. Then, the Position-Velocity controller is designed to swing-up the pendulum considering physical behavior. For stabilizing the inverted pendulum, a Takagi-Sugeno fuzzy controller with Adaptive Neuro-Fuzzy Inference System (ANFIS architecture is used to guarantee stability at unstable equilibrium position. Experimental results are given to show the effectiveness of these controllers.
Ali Moltajaei Farid
Full Text Available ANFIS is combining a neural network with a fuzzy system results in a hybrid neuro-fuzzy system, capable of reasoning and learning in an uncertain and imprecise environment. In this paper, an adaptive neuro-fuzzy inference system (ANFIS is employed to control an unmanned aircraft vehicle (UAV. First, autopilots structure is defined, and then ANFIS controller is applied, to control UAVs lateral position. The results of ANFIS and PID lateral controllers are compared, where it shows the two controllers have similar results. ANFIS controller is capable to adaptation in nonlinear conditions, while PID has to be tuned to preserves proper control in some conditions. The simulation results generated by Matlab using Aerosim Aeronautical Simulation Block Set, which provides a complete set of tools for development of six degree-of-freedom. Nonlinear Aerosonde unmanned aerial vehicle model with ANFIS controller is simulated to verify the capability of the system. Moreover, the results are validated by FlightGear flight simulator.
LI Chun-hua; ZHU Xin-jian; SUI Sheng; HU Wan-qi; HU Ming-ruo
To prevent the oxygen starvation and improve the system output performance, an adaptive inverse control (AIC) strategy is developed to regulate the air supply flow of a proton exchange membrane fuel cell (PEMFC) system in this paper.The PEMFC stack and the air supply system including a compressor and a supply manifold are modeled for the purpose of performance analysis and controller design. A recurrent fuzzy neural network (RFNN) is utilized to identify the inverse model of the controlled system and generates a suitable control input during the abrupt step change of external disturbances.Compared with the PI controller, numerical simulations are performed to validate the effectiveness and advantages of the proposed AIC strategy.