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.     

Finite-time decentralized adaptive neural constrained control for interconnected nonlinear time-delay systems with dynamics couplings among subsystems

The problem of finite-time decentralized neural adaptive constrained control is studied for large-scale nonlinear time-delay systems in the non-affine form. The main features of the considered system are that 1) unknown unmatched time-delay interactions are considered, 2) the couplings among the nested subsystems are involved in uncertain nonlinear systems, 3) based on finite-time stability approach, asymmetric saturation actuators and output constraints are studied in large-scale systems. First, the smooth asymmetric saturation nonlinearity and barrier Lyapunov functions are used to achieve the input and output constraints. Second, the appropriately designed Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions, and the neural networks are employed to approximate the unknown nonlinearities. Note that, due to unknown time-delay interactions and the couplings among subsystems, the controller design is more meaningful and challenging. At last, based on finite-time stability theory and Lyapunov stability theory, a decentralized adaptive controller is proposed, which decreases the number of learning parameters. It is shown that the designed controller can ensure that all closed-loop signals are bounded and the tracking error converges to a small neighborhood of the origin. The simulation studies are presented to show the effectiveness of the proposed method.     

State and output feedback fuzzy variable structure controllers for multivariable nonlinear systems subject to input nonlinearities

This paper presents three fuzzy adaptive controllers for a class of uncertain multivariable nonlinear systems with both sector nonlinearities and dead zones: two first controllers are state feedbacks and the last controller is an output feedback. The design of the first controller concerns systems with symmetric and positive definite control–gain matrix, while the second control design is extended to the case of nonsymmetric control–gain matrix thanks to an appropriate decomposition, namely the product of a symmetric positive definite matrix, a diagonal matrix with diagonal entries +1 or ?1, and a unity upper triangular matrix. The third controller is an output feedback extension of the second controller. In this controller, a high-gain observer is incorporated to estimate the unmeasurable states. An appropriate adaptive fuzzy logic system is used to reasonably approximate the uncertain functions. A Lyapunov approach is adopted to derive the parameter adaptation laws and prove the stability of those control systems as well as the exponential convergence of their underlying tracking errors within an adjustable region. The effectiveness of the proposed fuzzy adaptive controllers is illustrated through simulation results.     

Tracking control of robot manipulators via output feedback linearization

This paper presents a robot manipulator tracking controller based on output feedback linearization. A sliding mode perturbation observer (SPO) is designed to estimate unmeasurable states and system perturbations that involve system nonlinearities, disturbances and unmodelled dynamics. The use of SPO allows to input/output linearize and decouple the strongly coupled nonlinear robot manipulator system merely by the feedback of joint angles. The controller design does not need an accurate model of the robot manipulator. Simulation studies are undertaken based on a two-link robot manipulator to evaluate the proposed approach. The simulation results show that the proposed controller has more superior tracking control performance, with payload changing in a wide range, in comparison with a sliding mode controller (SMC) designed based on state feedback linearization with full states available. Selected from Journal of Shenzhen University (Science & Engineering), 2005, 22(3)     

Digital redesign of analog smith predictor for systems with input time delays

This paper presents a new methodology for digitally redesigning an existing analog Smith predictor control system, such that the cascaded analog controller with input delay can be implemented with a digital controller. A traditional analog Smith predictor system is reformulated into an augmented system, which is then digitally redesigned using the predicted intersampling states. The paper extends the prediction-based digital redesign method from a delay free feedback system to an input time-delay cascaded system. A tuning parameter v is optimally determined online such that in any sampling period, the output response error between the original analogously controlled time-delay system and the digitally controlled sampled-data time-delay system is significantly reduced. The proposed method gives very good performance in dealing with systems with delays in excess of several integer sampling periods and shows good robustness to sampling period selection.     

Nonlinear adaptive robust backstepping force control of hydraulic load simulator: Theory and experiments

High performance robust force control of hydraulic load simulator with constant but unknown hydraulic parameters is considered. In contrast to the linear control based on hydraulic linearization equations, hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative (PID) control not yield to high performance requirements. Furthermore, the hydraulic system may be subjected to non-smooth and discontinuous nonlinearities due to the directional change of valve opening. In this paper, based on a nonlinear system model of hydraulic load simulator, a discontinuous projection-based nonlinear adaptive robust back-stepping controller is developed with servo valve dynamics. The proposed controller constructs a novel stable adaptive controller and adaptation laws with additional pressure dynamic related unknown parameters, which can compensate for the system nonlinearities and uncertain parameters, meanwhile a well-designed robust controller is also synthesized to dominate the model uncertainties coming from both parametric uncertainties and uncertain nonlinearities including unmodeled and ignored system dynamics. The controller theoretically guarantee a prescribed transient performance and final tracking accuracy in presence of both parametric uncertainties and uncertain nonlinearities; while achieving asymptotic output tracking in the absence of unstructured uncertainties. The implementation issues are also discussed for controller simplification. Some comparative results are obtained to verify the high-performance nature of the proposed controller.     

Robust covariance control for discrete system by Takagi-Sugeno fuzzy controllers

Variances of the system states or outputs often play vital roles in the problem for performance requirements of many stochastic control systems. For linear stochastic systems, the covariance control technique has been applied to deal with the variance constrained design problem. This paper extends this technique to a class of discrete-time nonlinear perturbed stochastic systems, which are modeled by the Takagi-Sugeno (TS) fuzzy systems. By fuzzy IF-THEN rules, which represent local linear input-output relations, the nonlinear systems can be described by TS fuzzy models. According to the parallel distributed compensation (PDC) concept, the discrete-time nonlinear perturbed stochastic systems can be driven by the linear feedback gains. The purpose of this paper is to provide a method to design an output feedback fuzzy controller, which is based on the upper bound state covariance control technique and PDC concept, for the discrete-time perturbed stochastic systems using TS fuzzy models.     

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.     

A genuine nonlinear approach for controller design of a boiler-turbine system

This paper proposes a genuine nonlinear approach for controller design of a drum-type boiler-turbine system. Based on a second order nonlinear model, a finite-time convergent controller is first designed to drive the states to their setpoints in a finite time. In the case when the state variables are unmeasurable, the system will be regulated using a constant controller or an output feedback controller. An adaptive controller is also designed to stabilize the system since the model parameters may vary under different operating points. The novelty of the proposed controller design approach lies in fully utilizing the system nonlinearities instead of linearizing or canceling them. In addition, the newly developed techniques for finite-time convergent controller are used to guarantee fast convergence of the system. Simulations are conducted under different cases and the results are presented to illustrate the performance of the proposed controllers.     

A new approach to design of a dynamic output feedback stabilizing control law for LTI systems

We present a new state-space approach to construct a dynamic output feedback controller which stabilizes a class of linear time invariant systems All the states of the given system are not measurable and only the output is used to design the stabilizing control law In the design scheme, however, we first assume that the given system can be stabilized by a feedback law composed of the output and its derivatives of a certain order Beginning with this assumption, we systematically construct a dynamic system which removes the need of the derivatives The mam advantage of the proposed controller is regarding the controller order, which may be smaller than that of conventional output feedback controller Using a simple numerical example, it is shown that the order of the proposed controller is indeed smaller than that of reduced-order observer based output feedback controller     

An alternative LMI static output feedback control design for discrete-time nonlinear systems represented by Takagi–Sugeno models

This paper presents a static output feedback controller design for discrete-time nonlinear systems exactly represented by Takagi–Sugeno models. By introducing past states in the control law as well as in the Lyapunov function, more relaxed results are obtained. Different conditions in terms of linear matrix inequalities are provided. The proposed conditions are less demanding than the ones in the literature. This is illustrated via numerical examples.     

GA-optimized feedforward-PID tracking control for a rugged electrohydraulic system design

Rugged electrohydraulic systems are preferred for remote and harsh applications. Despite the low bandwidth, large deadband and flow nonlinearities in proportional valves valve and highly nonlinear friction in industry-grade cylinders that comprise rugged systems, their maintenance are much easier than very sophisticated and delicate servocontrol and servocylinder systems. With the target of making the easily maintainable system to perform comparably to a servosystem, a feedforward control has been designed here for compensating the nonlinearities. A PID feedback of the piston displacement has been employed in tandem for absorbing the unmodeled effects. All the controller parameters have been optimized by a real-coded genetic algorithm. The agreement between the achieved real-time responses for step and sinusoidal demands with those achieved by modern servosystems clearly establishes the acceptability of the controller design.     

非线性不确定系统的自适应反馈控制方法

针对具有模型不确定且参数未知的单输入单输出的非线性系统的特点,文中提出了一种自适应反馈控制方法。该方法中,假设系统被调整量最高阶导数的理想值为已知。由于方法仅需要对被控对象的调整量的输出进行反馈,而不要求状态量的具体值,所以降低了算法实现的难度。通过数值仿真验证了方法的可行性和有效性。     

转向缸系统反馈线性化分析与系统解耦

为解决汽车转向缸加载控制中出现的诸如强位置干扰、多通道耦合、非线性等问题,将线性系统和非线性系统理论引入系统控制器的设计中,对各通道耦合问题开展了以前馈补偿为基础的解耦控制,所设计的前馈补偿结构简单,解耦网络阶次低;针对非线性问题提出了将非线性系统精确反馈线性化与最优控制相结合的方法,设计了基于精确反馈线性化的最优控制器,该方法将复杂的非线性系统问题转化为线性系统的综合问题,采用渐近输出跟踪方法实现系统控制。仿真结果表明:采用前馈补偿解耦控制器可以有效消除耦合,但当系统存在高度非线性时,仅采用前馈补偿解耦控制不能达到高品质的性能要求,而进一步设计的基于精确反馈线性化的最优控制器考虑系统非线性时,系统能快速、准确达到预置设定。     

Quasi-minimal active disturbance rejection control of MIMO perturbed linear systems based on differential neural networks and the attractive ellipsoid method

This study addresses the problem of designing an output-based controller to stabilize multi-input multi-output (MIMO) systems in the presence of parametric disturbances as well as uncertainties in the state model and output noise measurements. The controller design includes a linear state transformation which separates uncertainties matched to the control input and the unmatched ones. A differential neural network (DNN) observer produces a nonlinear approximation of the matched perturbation and the unknown states simultaneously in the transformed coordinates. This study proposes the use of the Attractive Ellipsoid Method (AEM) to optimize the gains of the controller and the gain observer in the DNN structure. As a consequence, the obtained control input minimizes the convergence zone for the estimation error. Moreover, the control design uses the estimated disturbance provided by the DNN to obtain a better performance in the stabilization task in comparison with a quasi-minimal output feedback controller based on a Luenberger observer and a sliding mode controller. Numerical results pointed out the advantages obtained by the nonlinear control based on the DNN observer. The first example deals with the stabilization of an academic linear MIMO perturbed system and the second example stabilizes the trajectories of a DC-motor into a predefined operation point.     

Trajectory tracking control of a pneumatic X-Y table using neural network based PID control

This paper deals with the use of Neural Network based PID control scheme in order to assure good tracking performance of a pneumatic X-Y table. Pneumatic servo systems have inherent nonlinearities such as compressibility of air and nonlinear frictions present in cylinder. The conventional PID controller is limited in some applications where the affection of nonlinear factor is dominant. In order to track the reference model output, the primary control function is provided by the PID control and then the auxiliary control function is given by neural network for learning and compensating the inherent nonlinearities, A self-excited oscillation method is applied to derive the dynamic design parameters of a linear model. The experiment using the proposed control scheme has been performed and a significant reduction in tracking error is achieved.     

基于干扰观测器的时滞非线性切换系统滑模控制方法

为实现更加精准的时滞非线性切换系统滑模控制,应用干扰观测器设计一种新的系统滑模控制方法。构建时滞非线性切换系统模型,针对系统在发生结构变化时会产生复合干扰变化的情况,设计了一种非线性切换干扰观测器,实施系统不连续干扰的估计。通过 Backstepping 方法结合干扰观测器,设计一种切换滑模控制器,依据标量非线性特性打造一个滑模面,通过滑模控制器算法使时滞非线性切换系统能够满足滑模面的实际可达性条件,完成切换滑模控制器设计,实现系统的滑模控制。对设计的滑模控制方法进行测试,实验中选择的时滞非线性切换系统为一种变后掠翼 NSV 。实验结果表明,该设计方法能够实现较为准确地切入信号跟踪,表现出了很好的切换复合干扰估计性能。     

汽轮机/调速器系统的时滞无关分散控制器的设计

针对具有非线性关联作用和时变时滞的一类关联电力大系统,对其进行分散反馈控制。首先把非线性函数变化成子系统状态变量的二次有界不等式形式,然后基于Lyapunov稳定性理论,利用矩阵的Schur补定理及线性矩阵不等式方法,通过构造适当的Lyapunov泛函,得到了使电力系统渐近稳定的时滞无关的充分条件,并作为特例,给出了常...     

Static output feedback stabilization of networked control systems with a parallel-triggered scheme

This paper investigates the parallel-triggered static output feedback stabilization problem for linear networked control systems. A new parallel-triggered scheme is proposed by using both the relative error and the absolute error information. The scheme can reduce transmission rate while maintaining the global asymptotical stability. The linear parallel-triggered networked control system is modeled as a time-delay system. By employing Lyapunov stability theory, sufficient conditions are established for the closed-loop system to be globally asymptotically stable in terms of linear matrix inequalities. Moreover, a co-design algorithm is developed to obtain both the optimal trigger parameters and the output feedback controller gain in the sense that the transmission rate is minimized. Finally, two examples are given to illustrate the advantages of the proposed scheme.     

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.