Global adaptive output feedback control for a class of nonlinear time-delay systems

This paper addresses the problem of global output feedback control for a class of nonlinear time-delay systems. The nonlinearities are dominated by a triangular form satisfying linear growth condition in the unmeasurable states with an unknown growth rate. With a change of coordinates, a linear-like controller is constructed, which avoids the repeated derivatives of the nonlinearities depending on the observer states and the dynamic gain in backstepping approach and therefore, simplifies the design procedure. Using the idea of universal control, we explicitly construct a universal-type adaptive output feedback controller which globally regulates all the states of the nonlinear time-delay systems.     

Indirect adaptive fuzzy fault-tolerant tracking control for MIMO nonlinear systems with actuator and sensor failures

In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach.     

Static feedback stabilization of nonlinear systems with single sensor and single actuator

This paper considers a single sensor and single actuator approach to the static feedback stabilization of nonlinear systems. This is essentially a remote control problem that is present in many engineering applications. The proposed method solves this problem that is less expensive to implement and more reliable in practice. Significant results are obtained on the design of controllers for stabilizing the nonlinear systems. Important issues on control implementation are also discussed. The proposed design method is validated through its application to nonlinear control of aircraft engines.     

Finite-time stabilization for a class of stochastic nonlinear systems via output feedback

This paper investigates the problem of global finite-time stabilization in probability for a class of stochastic nonlinear systems. The drift and diffusion terms satisfy lower-triangular or upper-triangular homogeneous growth conditions. By adding one power integrator technique, an output feedback controller is first designed for the nominal system without perturbing nonlinearities. Based on homogeneous domination approach and stochastic finite-time stability theorem, it is proved that the solution of the closed-loop system will converge to the origin in finite time and stay at the origin thereafter with probability one. Two simulation examples are presented to illustrate the effectiveness of the proposed design procedure.     

Adaptive control for a class of MIMO nonlinear time delay systems against time varying actuator failures

This paper investigates an adaptive controller for a class of Multi Input Multi Output (MIMO) nonlinear systems with unknown parameters, bounded time delays and in the presence of unknown time varying actuator failures. The type of considered actuator failure is one in which some inputs may be stuck at some time varying values where the values, times and patterns of the failures are unknown. The proposed approach is constructed based on a backstepping design method. The boundedness of all the closed-loop signals is guaranteed and the tracking errors are proved to converge to a small neighborhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark and a chemical reactor system. The simulation results show the effectiveness of the proposed method.     

Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS

This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations.     

Adaptive output feedback tracking of nonlinear systems with uncertain nonsymmetric dead-zone input

In this paper, the problem of adaptive practical tracking is investigated by output feedback for a class of uncertain nonlinear systems subject to nonsymmetric dead-zone input nonlinearity with parameters of dead-zone being unknown. Instead of constructing the inverse of dead-zone nonlinearity, an adaptive robust control scheme is developed by designing an output compensator including two dynamic gains based respectively on identification and non-identification mechanism. With the aid of dynamic high-gain scaling approach and Backstepping method, stability analysis of the closed-loop system is proceeded using non-separation principle, which shows that the proposed controller guarantees that all closed-loop signal is bounded while the output of system tracks a broad class of bounded reference trajectories by arbitrarily small error prescribed previously. Finally, two examples are given to illustrate our controller effective.     

Output feedback model predictive control of hydraulic systems with disturbances compensation

Enhancing the robustness of output feedback control has always been an important issue in hydraulic servo systems. In this paper, an output feedback model predictive controller (MPC) with the integration of an extended state observer (ESO) is proposed for hydraulic systems. The ESO was designed to estimate not only the unmeasured system states but also the disturbances, which will be synthesized into the design of the output prediction equation. Based on the mechanism of receding horizon and repeating optimization of MPC, the output prediction equation will be updated in real time and the future behavior of the system will be accurately predicted since the disturbances are compensated effectively. Hence, the ability of the traditional MPC to suppress disturbances will be improved evidently. The experiment results show that the proposed controller has high-performance nature and strong robustness against various model uncertainties, which verifies the effectiveness of the proposed control strategy.     

Output feedback stabilization for time-delay nonholonomic systems with polynomial conditions

This paper addresses the problem of output feedback stabilization for a class of time-delay nonholonomic systems. One distinct characteristic or difficulty of this paper is that time-delay exists in polynomial nonlinear growing conditions. Based on input-state-scaling technique, homogeneous domination approach and Lyapunov–Krasovskii theorem, a new output feedback control law which guarantees all the system states converge to the origin is designed. Examples are provided to demonstrate the validness of the proposed approach.     

Observer-based reliable stabilization of uncertain linear systems subject to actuator faults,saturation, and bounded system disturbances

A matrix inequality approach is proposed to reliably stabilize a class of uncertain linear systems subject to actuator faults, saturation, and bounded system disturbances. The system states are assumed immeasurable, and a classical observer is incorporated for observation to enable state-based feedback control. Both the stability and stabilization of the closed-loop system are discussed and the closed-loop domain of attraction is estimated by an ellipsoidal invariant set. The resultant stabilization conditions in the form of matrix inequalities enable simultaneous optimization of both the observer gain and the feedback controller gain, which is realized by converting the non-convex optimization problem to an unconstrained nonlinear programming problem. The effectiveness of proposed design techniques is demonstrated through a linearized model of F-18 HARV around an operating point.     

Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV

A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies.     

A pressure output feedback control of turbo compressor surge with a thrust magnetic bearing actuator

This paper presents a pressure output feedback control of turbo compressor surge using tip clearance actuation with a thrust magnetic bearing actuator. First, static and dynamic compressor models were obtained for a commercial turbocharger, and the surge point was found through local stability analysis. Then, the effect of tip clearance on the compressor pressure rise was derived, and Lyapunov analysis was used to establish a limit of stability with tip clearance modulation. After that, a linear quadratic (LQ) state feedback control was designed considering the limit established by the Lyapunov analysis. In addition, an extended Kalman filter (EKF) was designed to estimate the mass flow rate from the measured compressor pressure. Finally, the pressure output feedback controller was built by combining the LQ state feedback control and EKF. Control simulation proved the effectiveness of the output feedback controller. This paper was recommended for publication in revised form by Associate Editor Dong Hwan Kim Dr. Ahn earned Ph.D. from Seoul National University in 2001. He was a research associate of University of Virginia. He is currently an assistant professor of department of mechanical engineering at Soongsil University and serving as an editor of international journal of rotating machinery. His research interests are rotordynamics, control and mechatronics. Mr. Park is a junior research engineer in Doosan infracore. He received his master from Seoul National University. His research area is on dynamics and control of rotating machinery. Dr. Sanadgol is an assistant Professor of Physics and Engineering at Sweet Briar College. She earned her PhD in Mechanical and Aerospace Engineering with a focus in controls from the University of Virginia in 2006. Her research interests are in controlling flow instabilities in compressors and application of nonlinear control theories to mechatronics systems. Dr. Park received his PhD degree from the Seoul National University, Korea in 2007. He is currently director of research institute at KMB&SENSOR company. His research interests include the precision machine design, rotor dynamics, and magnetic actuators. Dr. Han received the Dipl.-Ing. and Dr.-Ing. in mechanical engineering from University of Karsruhe, Germany in 1975 and 1979, respectively. In 1982, he joined the school of mechanical and aerospace engineering, Seoul National University as an assistant professor. He is currently an honorary professor of mechanical engineering. His research interests are in machine element design, magnetic bearing, lubrication engineering and Bio-MEMS devices. Dr. Maslen is a Professor of Mechanical and Aerospace Engineering at the University of Virginia. He earned his Bachelor of Science in 1980 from Cornell University and his doctorate from the University of Virginia in 1991. His research focuses on application of automatic controls to electromechanical systems with a concentration in magnetic bearings.     

Robust feedback linearization for nonlinear processes control

In this research, a robust feedback linearization technique is studied for nonlinear processes control. The main contributions are described as follows: 1) Theory says that if a linearized controlled process is stable, then nonlinear process states are asymptotically stable, it is not satisfied in applications because some states converge to small values; therefore, a theorem based on Lyapunov theory is proposed to prove that if a linearized controlled process is stable, then nonlinear process states are uniformly stable. 2) Theory says that all the main and crossed states feedbacks should be considered for the nonlinear processes regulation, it makes more difficult to find the controller gains; consequently, only the main states feedbacks are utilized to obtain a satisfactory result in applications. This introduced strategy is applied in a fuel cell and a manipulator.     

饱和离散时间系统非保守输出反馈控制器设计

针对输入饱和离散系统由于采用输出反馈而导致的控制器设计存在很强保守性的问题,将凸多面体分析的方法应用于系统吸引域描述中,给出了基于状态的系统可控域的顶点描述和面描述形式,建立了系统输出反馈与基于状态的系统可控域之间的关系;为解决由于不稳定系统输出反馈第一步控制不施加任何控制作用而造成的系统状态可控域大大减小的保守性问题,提出了基于状态观测器的输出反馈非保守控制器设计方法;针对二阶不稳定系统,根据系统输出矩阵及输出初始值的不同情况,给出了输出反馈控制器第一步控制作用的具体形式,并证明了在该控制器作用下,系统的可控域达到最大,从而最大程度减小了控制器的保守性。最后通过Matlab进行了数值仿真实例研究。研究结果验证了所设计控制器的有效性。     

Output feedback boundary control of an axially moving system with input saturation constraint

This paper is concerned with boundary control for an axially moving belt system with high acceleration/deceleration subject to the input saturation constraint. The dynamics of belt system is expressed by a nonhomogeneous hyperbolic partial differential equation coupled with an ordinary differential equation. First, state feedback boundary control is designed for the case that the boundary states of the belt system can be measured. Subsequently, output feedback boundary control is developed when some of the system states can not be accurately obtained. The well-posedness and the uniformly bounded stability of the closed-loop system are achieved through rigorous mathematical analysis. In addition, high-gain observers are utilized to estimate those unmeasurable states, the auxiliary system is introduced to eliminate the constraint effects of the input saturation, and the disturbance observer is adopted to cope with unknown boundary disturbance. Finally, the control performance of the belt system is illustrated by carrying out numerical simulations.     

Event-triggered decentralized adaptive fault-tolerant control of uncertain interconnected nonlinear systems with actuator failures

This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults.     

Event-triggered consensus control of disturbed multi-agent systems using output feedback

In this article, the event-triggered consensus control is investigated for general linear multi-agent systems with external disturbances, by using the accessible measurement outputs. In particular, a novel protocol is proposed using the local observed state variables at event-triggered instants, which are respectively derived by adopting an observer to each agent based on output signal. Then it is proved that under the designed event-triggered control protocol consensus can be achieved with the desired disturbance attenuation ability and no Zeno behavior occurs. A numerical simulation is given to demonstrate the effectiveness of the developed control strategy     

Output feedback integral control of piezoelectric actuators considering hysteresis

In this paper, output feedback integral control of piezoelectric actuators is considered with respect to the hysteresis effect. The linear dynamics of the piezoelectric actuator is modeled as a linear state space system with an input nonlinearity that considers the hysteresis effect. A proof of the Lyapunov stability of the system with integral control is presented, and a method for deriving the upper bound for the regulating gain is shown. A simple example is used to illustrate the approach, and then the approach is applied for tracking a step signal with an experimental single-axis piezoelectric actuator to verify that the system is stable.     

Adaptive predictive functional control of a class of nonlinear systems

This paper describes the use of pseudo-partial derivative (PPD) to dynamically linearize a nonlinear system, and aggregation is applied to the predicted PPD, resulting in a model-free adaptive predictive control algorithm for a nonlinear system. The algorithm design is only based on the PPD derived online from the input/output data of the controlled process, however it does provide bounded input/output sequence and setpoint tracking without steady-state error. A detailed discussion on parameter selection is also provided. To show the capability of the algorithm, simulations of a time-delay plant and a pH neutralization process show that the proposed method is effective for system parameter perturbation and external disturbance rejection.