Neural adaptive dynamic surface control for uncertain strict-feedback nonlinear systems with nonlinear output and virtual feedback errors

Nonlinear Dynamics - This paper addresses a new nonlinear gain feedback-based neural adaptive dynamic surface control (DSC) method for a sort of strict-feedback nonlinear systems in the presence of...     

空间机器人执行器自适应分散容错控制算法设计

针对执行器发生部分失效故障的漂浮基空间机器人系统,提出了一种自适应H_∞分散容错控制算法。利用拉格朗日第二类方程建立了系统的动力学模型。根据分散原理将系统分解为以基座或臂杆为单元的多个子系统,并将表示执行器控制能力的有效因子融入到每个子系统,使得单个子系统的执行器故障不会影响相邻执行器的正常运行。通过对每个故障子系统设计形式一致的自适应容错算法实现对整个系统的容错控制。仿真结果表明,与现有某非奇异终端滑模容错算法相比,本文算法具有更快的跟踪速度和更高的跟踪精度。     

Adaptive output feedback control of uncertain nonlinear chaotic systems based on dynamic surface control technique

In this paper, an adaptive output feedback control algorithm based on the dynamic surface control (DSC) is proposed for a class of uncertain chaotic systems. Because the system states are assumed to be unavailable, an observer is designed to estimate those unavailable states. The main advantage of this algorithm can overcome the problem of “explosion of complexity” inherent in the backstepping design. Thus, the proposed control approach is simpler than the traditional backstepping control for the uncertain chaotic systems. The stability analysis shows that the system is stable in the sense that all signals in the closed-loop system are uniformly ultimately bounded (UUB) and the system output can track the reference signal to a bounded compact set. Finally, an example is provided to illustrate the effectiveness of the proposed control system.     

Adaptive dynamic surface neural network control for nonstrict-feedback uncertain nonlinear systems with constraints

This paper presents an adaptive dynamic surface neural network control for a class of nonstrict-feedback uncertain nonlinear systems subjected to input saturation, dead zone and output constraint. The problem of input saturation is solved by designing an anti-windup compensator, and the issue of output constraint is addressed by introducing tan-type Barrier Lyapunov function. Furthermore, based on adaptive backstepping technique, a series of novel stabilizing functions are derived. First-order sliding mode differentiator is introduced into backstepping design to obtain the first-order derivative of virtual control. The real control input is obtained using dead-zone inverse method. It is proved that the proposed control scheme can achieve finite time convergence of the output tracking error into a small neighbor of the origin and guarantee all the closed-loop signals are bounded. Simulation results demonstrate the effectiveness of the proposed control scheme.     

Single neural network approximation based adaptive control for a class of uncertain strict-feedback nonlinear systems

A new adaptive control design approach is presented for a class of uncertain strict-feedback nonlinear systems. In the controller design process, all unknown functions at intermediate steps are passed down, and only one neural network is used to approximate the lumped unknown function of the system at the last step. By this approach, the designed controller contains only one actual control law and one adaptive law, and can be given directly. Compared with existing methods, the structure of the designed controller is simpler and the computational burden is lighter. Stability analysis shows that all the closed-loop system signals are uniformly ultimately bounded, and the steady state tracking error can be made arbitrarily small by appropriately choosing control parameters. Simulation studies demonstrate the effectiveness and merits of the proposed approach.     

Quantized feedback adaptive command filtered backstepping control for a class of uncertain nonlinear strict-feedback systems

Nonlinear Dynamics - An adaptive command filtered backstepping control design strategy in the presence of quantized states is presented for uncertain nonlinear systems in the strict-feedback form....     

Event-triggered robust adaptive control for uncertain nonlinear systems preceded by actuator dead-zone

It is both theoretically and practically important to investigate the problem of event-triggered adaptive tracking control for a class of uncertain nonlinear systems subject to actuator dead-zone, which aims at reducing communication rate and compensating actuator nonlinearity simultaneously. In this paper, to handle such a problem, an event-trigger based adaptive compensation scheme is proposed for the system preceded by actuator dead-zone. The challenges of this work can be roughly classified into two categories: how to compensate the nonsmooth dead-zone nonlinearity and how to eliminate the quantization signal effects caused by event-triggered strategy. To resolve the first challenge, a new decomposition of dead-zone mathematical model is employed so that dead-zone nonlinearity can be successively compensated by using robust approach. In addition, an adaptive controller and its triggering event are co-designed based on the relative threshold strategy, such that an asymptotic tracking performance can be ensured. The proposed scheme is proved to guarantee the globally bounded of all closed-loop signals and the asymptotic convergence performance of tracking error toward zero. The simulation results illustrate the effectiveness of our proposed control scheme.     

Fault tolerant control for a class of uncertain chaotic systems with actuator saturation

This paper studies the fault tolerant control problem for a class of uncertain chaotic systems via sliding mode control. Both actuator faults and saturation are considered. Under an actuator redundancy assumption, an important lemma is first given and proved to find a lower bound of fault information and saturation degree. Then an adaptive sliding mode controller is designed to guarantee locally asymptotical stability of synchronization error. Compared with existing literature, an obvious relationship between actuator fault information and stability region is revealed. An improved strategy is also proposed to reduce conservativeness when estimating stability region. Finally, a model of Chua’s circuit systems is used to demonstrate these results.     

Fault-tolerant sliding mode attitude control for flexible spacecraft under loss of actuator effectiveness

In this paper, a novel fault-tolerant attitude control synthesis is carried out for a flexible spacecraft subject to actuator faults and uncertain inertia parameters. Based on the sliding mode control, a fault-tolerant control law for the attitude stabilization is first derived to protect against the partial loss of actuator effectiveness. Then the result is extended to address the problem that the actual output of the actuators is constrained. It is shown that the presented controller can accommodate the actuator faults, even while rejecting external disturbances. Moreover, the developed control law can rigorously enforce actuator-magnitude constraints. An additional advantage of the proposed fault-tolerant control strategy is that the control design does not require a fault detection and isolation mechanism to detect, separate, and identify the actuator faults on-line; the knowledge of certain bounds on the effectiveness factors of the actuator is not used via the adaptive estimate method. The associated stability proof is constructive and accomplished by the development of the Lyapunov function candidate, which shows that the attitude orientation and angular velocity will globally asymptotically converge to zero. Numerical simulation results are also presented which not only highlight the ensured closed-loop performance benefits from the control law derived here, but also illustrate its superior fault tolerance and robustness in the face of external disturbances when compared with the conventional approaches for spacecraft attitude stabilization control.     

A delay partitioning approach to output feedback control for uncertain discrete time-delay systems with actuator saturation

This paper is concerned with the problems of output feedback control for uncertain discrete time-delay systems with input saturation. The delay partitioning approach is proposed to obtain new stability criteria. The dynamic output feedback controller is designed based on a linear matrix inequality framework. A sufficient condition is developed, which guarantees the existence of dynamic output feedback controllers such that all trajectories of the closed-loop system starting from an admissible initial condition domain converge to a smaller ellipsoid. Simulation examples are provided to show the potential of the proposed techniques.     

Output feedback stabilization based on dynamic surface control for a class of uncertain stochastic nonlinear systems

In this paper, the dynamic surface control (DSC) algorithm is proposed for a class of stochastic nonlinear systems with nonminimum phase and the standard output-feedback form. The proposed algorithm is a stochastic vision by combining the traditional back-stepping together with the DSC technique, which can overcome the problem of ‘explosion of complexity’ in the back-stepping designing procedure for the stochastic nonlinear systems. Thus, it can reduce the computation complexity and is easy to be used in the actual implementation. It is shown that all the signals of the resulting closed-loop system are uniformly ultimately bounded.     

Finite-time attitude control for rigid spacecraft subject to actuator saturation

Nonlinear Dynamics - This paper considers the problem of attitude stabilizing control for rigid spacecraft in the presence of input constraints. To address this problem, a smooth model is first...     

Fuzzy observer-based command filtered tracking control for uncertain strict-feedback nonlinear systems with sensor faults and event-triggered technology

For the trajectory tracking problem of nth-order uncertain nonlinear systems with sensor faults, a fuzzy controller based on command filtered and event-triggered technology is designed to improve the tracking error of the system. Concurrently, a fault-tolerant control scheme is introduced to effectively solve the problem of sudden output sensor failure. Additionally, the proposed controller can also greatly avoid complexity explosion problem of derivations of virtual control laws, which makes the design of the controller simpler. Furthermore, an effective observer is designed to solve the problem of system state immeasurability. Therefore, the proposed control scheme makes the design of the controller more convenient and flexible. According to Lyapunov stability theory, it is proved that all closed-loop signals are uniformly and ultimately bounded. Finally, two simulation examples of second-order nonlinear system and single-link robot show the effectiveness of the proposed scheme.

     

Adaptive fuzzy voltage-based backstepping tracking control for uncertain robotic manipulators subject to partial state constraints and input delay

Nonlinear Dynamics - The aim of this paper is to tackle the problem of adaptive fuzzy voltage-based tracking control for uncertain electrically driven robotic manipulators subject to input delay...     

Observer-based adaptive fuzzy backstepping control of MIMO stochastic nonlinear strict-feedback systems

In this paper, an adaptive fuzzy output feedback control approach is proposed for a class of multiinput and multioutput (MIMO) uncertain stochastic nonlinear strict-feedback systems without the measurements of the states. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy state observer is designed for estimating the unmeasured states. Utilizing the designed the fuzzy state observer and by combining the adaptive backstepping control design, an adaptive fuzzy output feedback control approach is developed. It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semiglobally uniformly ultimately bounded (SUUB) in probability, and the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. A simulation example is provided to show the effectiveness of the proposed approach.     

Distributed adaptive neural control for uncertain multi-agent systems with unknown actuator failures and unknown dead zones

Nonlinear Dynamics - In actuality, the dead zones and failures often occur in actuators, but the existing algorithms have difficulty simultaneously tolerating dead zones and actuator failures in...