具有模糊监督控制器的积分变结构间接自适应控制

针对一类不确定非线性系统, 基于变结构控制原理, 并利用具有非线性可调参数的模糊系统去逼近过程未知函数, 提出一种具有模糊监督控制器的积分变结构间接自适应控制方案. 该方案通过监督控制器保证闭环系统所有信号有界. 进一步, 通过引入最优逼近误差的自适应补偿项来消除建模误差的影响. 理论分析证明了跟踪误差收敛到零. 仿真结果表明了该方法的有效性.     

A robust indirect adaptive regulation algorithm withself-excitation capability

A robust version of the adaptive control algorithm established by G. Kreisselmeier (1989) is presented. If the conventional dead-zone adaptive law is used in the adaptive system, it is troublesome that the size of the unmodeled dynamics, denoted by ∈, must be within the chosen dead-zone size for robustness. In this robust version, by introducing a positive design parameter, the robust stability can be achieved without this constraint. It is also shown that the plant output and control input will converge asymptotically within a certain bound. Moreover, in the ideal case, the plant output and control input will converge to zero under some condition     

A globally convergent pole placement indirect adaptive controller

A pole displacement indirect adaptive control algorithm is discussed for discrete-time linear deterministic plants with arbitrary zeros. The global convergence of the resulting closed-loop control system is achieved subject to the assumptions that the plant order and a nonzero lower bound on its degree of controllability are known. The problem of controllability of the plant model estimate is handled by using both a parameter correction and time-varying nonlinear feedback. A key property of the algorithm is that the plant estimate reaches a reasonable degree of controllability in a finite time, after which the parameter correction and the nonlinear feedback are no longer used     

机器人间接自适应模糊控制器及其应用

归纳并证明了机器人间接自适应模糊控制的几个重要特性并阐述了其用于多关节机器人跟踪控制的策略. 对一个具有远程独立电机驱动的双连杆机械臂的仿真结果证实了可行性.     

Stable indirect adaptive neural controller for a class of nonlinear system

The paper presents an indirect adaptive neural control scheme for a general high-order nonlinear continuous system. In the proposed scheme a neural controller is constructed based on the single-hidden layer feedforward network (SLFN) for approximating the unknown nonlinearities of dynamic systems. A sliding mode controller is also incorporated to compensate for the modelling errors of SLFN. The parameters of the SLFN are modified using the recently proposed neural algorithm named extreme learning machine (ELM), where the parameters of the hidden nodes are assigned randomly. However different from the original ELM algorithm, the output weights are updated based on the Lyapunov synthesis approach to guarantee the stability of the overall control system, even in the presence of modelling errors which are offset using the sliding mode controller. Finally the proposed adaptive neural controller is applied to control the inverted pendulum system with two different reference trajectories. The simulation results demonstrate that good tracking performance is achieved by the proposed control scheme.     

一类非线性系统的间接自适应模糊控制器的研究

研究一类不确定非线性系统的间适应模糊控制问题。基于Wang提出的监督控制方案，利用Ⅰ型模糊系统的逼近能力，提出一种自适应模糊控制器设计的新方案，该方案通过引入最优逼近误差的自适应补偿项来消除建模误差的影响，从而在稳定性分析中取消了要求逼近误差平方可积或逼近误差的上确界已知的条件，理论分析证明了闭环控制系统是全局稳定的，跟踪误差收敛到零，仿真结果表明了该方法的有效性。     

机器人轨迹跟踪的间接自适应模糊控制

为把已有的模糊控制算法应用于多自由度机器人的实时控制中,将间接自适应模糊控制算法从单输入单输出(SISO)系统推广至多输入多输出(MIMO)系统,并给出了系统收敛的严格数学证明.另外对于n关节的机器人轨迹跟踪问题,设计了一种新型控制器能够保证系统的最终一致有界性(u.u.b.).通过对具有远程独立电机驱动的双连杆机械臂的仿真试验证明了该方案的可行性.     

An adaptive controller for nonlinear teleoperators

In Chopra et al (2008) [Chopra, N., Spong, M. W., & Lozano, R. (2008). Synchronization of bilateral teleoperators with time-delay. Automatica, 44(8), 2142-2148], an adaptive controller for teleoperators with time-delays, which ensures synchronization of positions and velocities of the master and slave manipulators, and does not rely on the use of the ubiquitous scattering transformation, is proposed. In this paper it is shown that this controller will tend to drive to zero the positions of the joints where gravity forces are non-zero. Hence, the scheme is, in general, applicable only to systems without gravity. We also prove in this paper that this limitation can be obviated, replacing the positions and velocities-that are used in the coordinating torques and the adaptation laws-by their errors. Simulation results illustrate the performance of both schemes.     

Takagi-Sugeno fuzzy model based indirect adaptive fuzzy observer and controller design

This paper proposes the design scheme of the alternative adaptive observer and controller based on the Takagi-Sugeno (T-S) fuzzy model. The T-S fuzzy modeling and the state feedback control technique are adopted for the simple structure. The proposed method maintains consistent performance in the presence of parameter uncertainties and incorporates linguistic fuzzy information from human operators. In addition, with the simple adaptive state feedback controller, it solves the singularity problem, which occurs in the inverse dynamics based on the feedback linearization method. Using Lyapunov theory and Lipschitz condition, the stability analysis is conducted, and the adaptive law is derived. The proposed method is applied to the stabilization problem of a flexible joint manipulator in order to guarantee its performance.     

An indirect stochastic adaptive scheme with on-line choice ofweighting polynomials

An indirect adaptive control algorithm combining a quadratic cost measure of the Clarke-Gawthrop type and the classical control strategy of pole placement is presented. It updates the weighting polynomials of the cost function online in such a way that the closed-loop poles are located at prespecified positions. The convergence and stability of the adaptive control algorithm is also given without the assumption that the system is minimum phase     

An approach to stable indirect adaptive control

Stable indirect adaptive control of minimum and nonminimum phase plants is established for cases where a priori bounds on the unknown plant parameters are known and where for each set of parameter values within these bounds the plant has no unstable pole-zero cancellation. By incorporating this partial parameter knowledge in the adaptive law and using a nonminimal representation of the plant, it is shown that the adaptive closed loop control system can be written as an exponentially stable system driven by the identification error. The stability of the adaptive control system is then shown using techniques similar to those known from the model reference adaptive control approach.     

应用局部函数估计的自适应控制方法

针对一类非线性、不确定性系统结构,提出一种应用局部函数估计的自适应控制器设计方法,并分析该控制器的结构和系统稳定收敛性,最后通过仿真试验表明该控制器设计的简单实用和优越性能。     

An adaptive dead-zone inverse controller for systems with sandwiched dead-zones

This paper addresses adaptive control of sandwich non-linear systems having an unknown sandwiched dead-zone between the linear dynamic blocks, as illustrated by a hydraulic valve system. An adaptive hybrid control scheme for control of such sandwiched dead-zone systems is developed. The proposed control scheme employs an inner-loop discrete-time feedback design and an outer-loop continuous-time feedback design, combined with an adaptive dead-zone inverse to cancel the dead-zone effect for improving output tracking. Stability and tracking performance of the closed-loop control system are analysed. Simulation results are used to illustrate the effectiveness of the proposed adaptive dead-zone inverse controller.     

An adaptive controller which provides Lyapunov stability

An adaptive controller that can provide exponential Lyapunov stability for an unknown linear time-invariant (LTI) system is presented. The only required a priori information about the plant is that the order of an LTI stabilizing compensator be known, although this can be reduced to assuming only that the plant is stabilizable and detectable at the expense of using a more complicated controller. This result extends the work of M. Fu and B.R. Barmish (see ibid., vol.AC-31, p.1097-1103, Dec. 1986) in which it is shown that there exists an adaptive controller which provides exponential Lyapunov stability if it is assumed that an upper bound on the plant order is known and that the plant lies in a known compact set; it shows that adaptive stabilization is possible under very mild assumptions without large state deviations     

一种自适应广义预测极点配置加权控制器

针对预测控制存在如何减小计算量，保证实时性问题，提出一种用计算量小的递推算法辨识方程参数的新方案，并推广了以往献有关Diophantine方程的递推算法，应用表明，所提出的方案是有效的。     

An adaptive controller based on disturbance attenuation

This paper discusses the control of linear systems with uncertain parameters in the control coefficient matrix, under the influence of both process and measurement noise. A disturbance attenuation approach is used, and from this a multiplayer game problem is generated. First, the minimax formulation is presented, which represents an upper bound on the game cost criterion. Second, a dynamic programming approach is used to solve the game. It is necessary to significantly extend the method over earlier implementations, as the class of problems does not satisfy certain assumptions generally made. It is shown that for this class of problems, the controller determined from the dynamic programming approach is equivalent to the minimax controller. Therefore, the minimax controller is also a saddlepoint strategy for the differential game. Controller development appears to be much simpler from the dynamic programming standpoint. A simple scalar example is presented     

Robust fault-tolerant controller design for linear time-invariant systems with actuator failures: an indirect adaptive method

In this paper, indirect adaptive state feedback control schemes are developed to solve the robust faulttolerant control (FTC) design problem of actuator fault and perturbation compensations for linear time-invariant systems. A more general and practical model of actuator faults is presented. While both eventual faults on actuators and perturbations are unknown, the adaptive schemes are addressed to estimate the lower and upper bounds of actuator-stuck faults and perturbations online, as well as to estimate control effectiveness on actuators. Thus, on the basis of the information from adaptive schemes, an adaptive robust state feed-back controller is designed to compensate the effects of faults and perturbations automatically. According to Lyapunov stability theory, it is shown that the robust adaptive closed-loop systems can be ensured to be asymptotically stable under the influence of actuator faults and bounded perturbations. An example is provided to further illustrate the fault compensation effectiveness.     

Robust fault-tolerant controller design for linear time-invariant systems with actuator failures: an indirect adaptive method

In this paper, indirect adaptive state feedback control schemes are developed to solve the robust faulttolerant control (FTC) design problem of actuator fault and perturbation compensations for linear time-invariant systems. A more general and practical model of actuator faults is presented. While both eventual faults on actuators and perturbations are unknown, the adaptive schemes are addressed to estimate the lower and upper bounds of actuator-stuck faults and perturbations online, as well as to estimate control effectiveness on actuators. Thus, on the basis of the information from adaptive schemes, an adaptive robust state feed-back controller is designed to compensate the effects of faults and perturbations automatically. According to Lyapunov stability theory, it is shown that the robust adaptive closed-loop systems can be ensured to be asymptotically stable under the influence of actuator faults and bounded perturbations. An example is provided to further illustrate the fault compensation effectiveness.     

An adaptive controller design for linear state-delay systems with actuator failures

In this paper, an adaptive fault tolerant controller is developed for a class of linear state delay systems against actuator failures. To design the controller, all parameters of the system are considered to be unknown, but the time delay value is assumed to be known. Actuator failures are characterized by some unknown system inputs are stuck at some unknown fixed values and at unknown time instants. The adaptive controller is designed based on SPR-Lyapunov approach for the cases with the relative degrees of one and two. Closed-loop system stability and asymptotic output tracking are proved using a suitable Lyapunov-Krasovskii functional for each case and the effectiveness of the proposed results has been illustrated through simulation studies.     

An adaptive variable structure output tracking controller with improved transient performance

This paper presents an adaptive variable structure output tracking controller that achieves improved transient response over conventional adaptive controllers and, at the same time, retains asymptotic output tracking performance even in the presence of bounded external disturbances. The main properties of the proposed controller are analytically established in two theorems, and the paper also includes simulation results which demonstrate the effectiveness of the proposed approach.