Multivariable robust adaptive sliding mode control of an industrial boiler–turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller

To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler–turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler–turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input–output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions.     

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.     

Dynamic characteristic analysis and lmi-basedh∞, controller design for a line of sight stabilization system

This paper is concerned with the design of an LMI (Linear Matrix Inequality)-basedH∞, controller for a line of sight (LOS) stabilization system and with its robustness performance. The linearization of the system is necessary to analyze various nonlinear characteristics, but the linearization entails modeling uncertainties which reduce its performance. In addition, the stability of the LOS can be adversely affected by angular velocity disturbances while the vehicle is moving. As the vehicle accelerates, all the factors that are ignored and simplified for the linearization tend to inhibit the performance of the system. The robustness in the face of these uncertainties needs to be assured. This paper employsH∞ control theory to address these problems and the LMI method to provide a suitable controller with minimal constraints for the system. Even though the system matrix does not have a full rank, the proposed method makes it possible to design aH∞ controller and to deal withR and S matrices for reducing the system order. It can be also shown that the proposed robust controller has a better disturbance attenuation and tracking performance. The LMI method is also used to enhance the applicability of the proposed reduced-orderH∞ controller for the system given. The LMI-basedH∞ controller has superior disturbance attenuation and reference input tracking performance, compared with that of the conventional controller under real disturbances.     

Nonlinear robust control of hypersonic aircrafts with interactions between flight dynamics and propulsion systems

This paper addresses the nonlinear robust tracking controller design problem for hypersonic vehicles. This problem is challenging due to strong coupling between the aerodynamics and the propulsion system, and the uncertainties involved in the vehicle dynamics including parametric uncertainties, unmodeled model uncertainties, and external disturbances. By utilizing the feedback linearization technique, a linear tracking error system is established with prescribed references. For the linear model, a robust controller is proposed based on the signal compensation theory to guarantee that the tracking error dynamics is robustly stable. Numerical simulation results are given to show the advantages of the proposed nonlinear robust control method, compared to the robust loop-shaping control approach.     

基于灰色预测的永磁同步电动机速度控制

本文针对永磁同步电动机非线性动态数学模型，采用直接反馈线性化控制，建立了闭环系统的输入-输出模型，通过线性化模型来设计控制器，该方法简单适用；同时，为了克服此反馈线性化控制对模型要求精确化这一不足，提出了基于灰色理论的不确定预测器，它能在线预测永磁同步电机的不确定因素并相应的调整反馈线性化控制法则，从而提高了系统的动态性能。仿真与实验结果表明，该方法对永磁同步电机速度控制具有很好的跟踪性能和鲁棒性能。     

Design and experimental realization of a robust decentralized PI controller for a coupled tank system

This paper presents design and realization of a robust decentralized PI controller for regulating the level of a coupled tank system. The proposed controller is designed based on a predefined reference transfer function model in which we adopt a frequency matching of actual and reference models. Realization of control algorithms for a multivariable system is often complicated owing to uncertainties in the process dynamics. In this paper, initially a frequency response fitting model reduction technique is adopted to obtain a First Order Plus Dead Time (FOPDT) model of each higher order decoupled subsystem. Further, using the obtained reduced order model, the proposed robust decentralized PI controller is designed. The stability and performance of the proposed controller are verified by considering multiplicative input and output uncertainties. The performance of the proposed robust decentralized controller has been compared with that of a decentralized PI controller. To validate the performance of the proposed control approach, real-time experimentation is pursed on a Feedback Instrument manufactured coupled tank system.     

Spatial curvilinear path following control of underactuated AUV with multiple uncertainties

This paper investigates the problem of spatial curvilinear path following control of underactuated autonomous underwater vehicles (AUVs) with multiple uncertainties. Firstly, in order to design the appropriate controller, path following error dynamics model is constructed in a moving Serret–Frenet frame, and the five degrees of freedom (DOFs) dynamic model with multiple uncertainties is established. Secondly, the proposed control law is separated into kinematic controller and dynamic controller via back-stepping technique. In the case of kinematic controller, to overcome the drawback of dependence on the accurate vehicle model that are present in a number of path following control strategies described in the literature, the unknown side-slip angular velocity and attack angular velocity are treated as uncertainties. Whereas in the case of dynamic controller, the model parameters perturbations, unknown external environmental disturbances and the nonlinear hydrodynamic damping terms are treated as lumped uncertainties. Both kinematic and dynamic uncertainties are estimated and compensated by designed reduced-order linear extended state observes (LESOs). Thirdly, feedback linearization (FL) based control law is implemented for the control model using the estimates generated by reduced-order LESOs. For handling the problem of computational complexity inherent in the conventional back-stepping method, nonlinear tracking differentiators (NTDs) are applied to construct derivatives of the virtual control commands. Finally, the closed loop stability for the overall system is established. Simulation and comparative analysis demonstrate that the proposed controller exhibits enhanced performance in the presence of internal parameter variations, external unknown disturbances, unmodeled nonlinear damping terms, and measurement noises.     

Sliding mode based trajectory linearization control for hypersonic reentry vehicle via extended disturbance observer

This paper proposes a novel hybrid control framework by combing observer-based sliding mode control (SMC) with trajectory linearization control (TLC) for hypersonic reentry vehicle (HRV) attitude tracking problem. First, fewer control consumption is achieved using nonlinear tracking differentiator (TD) in the attitude loop. Second, a novel SMC that employs extended disturbance observer (EDO) to counteract the effect of uncertainties using a new sliding surface which includes the estimation error is integrated to address the tracking error stabilization issues in the attitude and angular rate loop, respectively. In addition, new results associated with EDO are examined in terms of dynamic response and noise-tolerant performance, as well as estimation accuracy. The key feature of the proposed compound control approach is that chattering free tracking performance with high accuracy can be ensured for HRV in the presence of multiple uncertainties under control constraints. Based on finite time convergence stability theory, the stability of the resulting closed-loop system is well established. Also, comparisons and extensive simulation results are presented to demonstrate the effectiveness of the control strategy.     

Concept design,modeling and station-keeping attitude control of an earth observation platform

The stratosphere airship provides a unique and promising platform for earth observation. Researches on the project design and control scheme for earth observation platforms are still rarely documented. Nonlinear dynamics, model uncertainties, and external disturbances contribute to the difficulty in maneuvering the stratosphere airship. A key technical challenge for the earth observation platform is station keeping, or the ability to remain fixed over a geo-location. This paper investigates the conceptual design, modeling and station-keeping attitude control of the near-space earth observation platform. A conceptual design of the earth observation platform is presented. The dynamics model of the platform is derived from the Newton-Euler formulation, and the station-keeping control system of the platform is formulated. The station-keeping attitude control approach for the platform is proposed. The multi-input multi-output nonlinear control system is decoupled into three single-input single-output linear subsystems via feedback linearization, the attitude controller design is carried out on the new linear systems using terminal sliding mode control, and the global stability of the closed-loop system is proven by using the Lyapunov theorem. The performance of the designed control system is simulated by using the variable step Runge-Kutta integrator. Simulation results show that the control system tracks the commanded attitude with an error of zero, which verify the effectiveness and robustness of the designed control system in the presence of parametric uncertainties. The near-space earth observation platform has several advantages over satellites, such as high resolution, fast to deploy, and convenient to retrieve, and the proposed control scheme provides an effective approach for station-keeping attitude control of the earth observation platform.     

Global finite-time adaptive control for uncalibrated robot manipulator based on visual servoing

The paper addresses the finite-time convergence problem of a uncalibrated camera-robot system with uncertainties. These uncertainties include camera extrinsic and intrinsic parameters, robot dynamics and feature depth parameters, which are all considered as time-varying uncertainties. In order to achieve a better dynamic stability performance of the camera-robot system, a novel FTS adaptive controller is presented to cope with rapid convergence problem. Meanwhile, FTS adaptive laws are proposed to handle these uncertainties which exist both in robot and in camera model. The finite-time stability analysis is discussed in accordance with homogeneous theory and Lyapunov function formalism. The control method we proposed extends the asymptotic stability results of visual servoing control to a finite-time stability. Simulation has been conducted to demonstrate the performance of the trajectory tracking errors convergence under control of the proposed method.     

Novel fuzzy feedback linearization strategy for control via differential geometry approach

The study investigates a novel fuzzy feedback linearization strategy for control. The main contributions of this study are to construct a control strategy such that the resulting closed-loop system is valid for any initial condition with almost disturbance decoupling performance, and develop the feedback linearization design for some class of nonlinear control systems. The feedback linearization control guarantees the almost disturbance decoupling performance and the uniform ultimate bounded stability of the tracking error system. Once the tracking errors are driven to touch the global final attractor with the desired radius, the fuzzy logic control is immediately applied via a human expert’s knowledge to improve the convergence rate. One example, which cannot be solved by the first paper on the almost disturbance decoupling problem, is proposed in this paper to exploit the fact that the almost disturbance decoupling and the convergence rate performances are easily achieved by the proposed approach.     

Active disturbance rejection based trajectory linearization control for hypersonic reentry vehicle with bounded uncertainties

This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy.     

Flight control of a hexa-rotor airship: Uncertainty quantification for a range of temperature and pressure conditions

The present paper is concerned with the dynamic modeling and design of control laws for a small non-rigid multi-rotor airship constituted of an oblate-spheroid helium balloon coupled with an electric-powered hexa-rotor airframe. The vehicle is assumed to operate in windless and low-speed conditions. A six-degree-of-freedom nonlinear dynamic model is derived for it using the Newton–Euler approach and considering, among other efforts, a restoring torque due to the displacement of the balloon’s center of buoyancy above the vehicle’s center of mass and the added-mass effect resulting from the air–structure interaction. Using the derived model and assuming a time-scale separation between the translational and rotational dynamics, the attitude and position control laws are designed separately from each other. Both laws are formulated using feedback linearization combined with control input saturation within appropriate parallelepipedal sets, which are carefully chosen to respect pre-defined bounds on the control torque, control force and maximum inclination angle. The effect of temperature and pressure fluctuations is taken into account through a parametric probabilistic approach, where Maximum Entropy Principle is used to construct a physically consistent stochastic model and Monte Carlo method is used as the stochastic solver to propagate the uncertainties through the system. Extensive simulation results show the effectiveness of the proposed control system and quantify the uncertainty of its performance over a wide range of local temperature and pressure.     

Sufficient LMI conditions and Lyapunov redesign for the robust stability of a class of feedback linearized dynamical systems

The robust stability of a class of feedback linearizable minimum-phase nonlinear system, having parametric uncertainties, is investigated in this study. The system in new coordinates is represented to an equivalent formulation after the attempt of feedback linearization. Due to the parametric uncertainties the approximately linearized system entails a norm bounded input nonlinearity such that the equilibrium point condition in error dynamics can not be satisfied. Accordingly, to guarantee the regional asymptotic stability a control synthesis problem is proposed by means of sufficient Linear Matrix Inequalities (LMIs) together with an amended nonlinear control term, derived from the Lyapunov redesign method, which tackles zero steady-state error condition. The numerical examples of a general aviation aircraft's longitudinal dynamics and inverted pendulum are simulated to show the proficiency of the proposed control technique.     

Neural robust control for perturbed crane systems

In this paper, we present a new control methodology for perturbed crane systems. Nonlinear crane systems are transformed to linear models by feedback linearization. An inverse dynamic equation is applied to compute the system PD control force. The PD control parameters are selected based on a nominal model and are therefore suboptimal for a perturbed system. To achieve the desired performance despite model perturbations, we construct a neural network auxiliary controller to compensate for modeling errors and disturbances. The overall control input is the sum of the nominal PD control and the neural auxiliary control. The neural network is iteratively trained with a perturbed system until acceptable performance is attained. We apply the proposed control scheme to 2- and 3-degree-of-freedom (D.O.F.) crane systems, with known bounds on the payload mass. The effectiveness of the control approach is numerically demonstrated through computer simulation experiments.     

Continuous high order sliding mode controller design for a flexible air-breathing hypersonic vehicle

This paper investigates the problem of tracking control with uncertainties for a flexible air-breathing hypersonic vehicle (FAHV). In order to overcome the analytical intractability of this model, an Input–Output linearization model is constructed for the purpose of feedback control design. Then, the continuous finite time convergence high order sliding mode controller is designed for the Input–Output linearization model without uncertainties. In addition, a nonlinear disturbance observer is applied to estimate the uncertainties in order to compensate the controller and disturbance suppression, where disturbance observer and controller synthesis design is obtained. Finally, the synthesis of controller and disturbance observer is used to achieve the tracking for the velocity and altitude of the FAHV and simulations are presented to illustrate the effectiveness of the control strategies.     

Precision position control of servo systems using adaptive back-stepping and recurrent fuzzy neural networks

To improve position tracking performance of servo systems, a position tracking control using adaptive back-stepping control(ABSC) scheme and recurrent fuzzy neural networks(RFNN) is proposed. An adaptive rule of the ABSC based on system dynamics and dynamic friction model is also suggested to compensate nonlinear dynamic friction characteristics. However, it is difficult to reduce the position tracking error of servo systems by using only the ABSC scheme because of the system uncertainties which cannot be exactly identified during the modeling of servo systems. Therefore, in order to overcome system uncertainties and then to improve position tracking performance of servo systems, the RFNN technique is additionally applied to the servo system. The feasibility of the proposed control scheme for a servo system is validated through experiments. Experimental results show that the servo system with ABS controller based on the dual friction observer and RFNN including the reconstruction error estimator can achieve desired tracking performance and robustness.     

多关节机器人反馈线性化双模糊滑模控制

为了提高多关节机器人轨迹跟踪控制性能,提出了一种反馈线性化双模糊滑模控制方法。该方法在对机器人非线性动力学模型反馈线性化的基础上,设计了一种双模糊滑模控制器。通过设计一个模糊控制器,根据跟踪误差和误差变化率自适应地调整滑模面的斜率,从而加快响应速度。通过设计另一个模糊控制器,根据滑模面自适应地调整滑模控制的切换控制部分,从而减弱抖振。利用李亚普诺夫定理证明了控制系统的稳定性。针对空间三关节机器人进行了仿真实验,结果表明了所提方法的有效性。     

Tuning of PID controllers for boiler-turbine units

A simple two-by-two model for a boiler-turbine unit is demonstrated in this paper. The model can capture the essential dynamics of a unit. The design of a coordinated controller is discussed based on this model. A PID control structure is derived, and a tuning procedure is proposed. The examples show that the method is easy to apply and can achieve acceptable performance.     

Neural adaptive pointing control of a moving tank gun with lumped uncertainties based on dynamic simulation

This study focuses on the pointing control problem of a moving tank gun. Model uncertainty and foundation vibration, which may be nonlinear, coupled, or time-varying but bounded, are considered. First, the electrohydraulic servo system of a vertical stabilizer is constructed as a nonlinear dynamic system with lumped uncertainties. Second, a neural adaptive controller is proposed to improve the control performance of the vertical stabilizer. A back-propagation neural network is introduced to compensate for the uncertainties, and its weight and threshold values are self-tuned online. Third, a co-simulation model of the moving tank is established. Dynamic simulation verifies that the proposed controller exhibits better performance than typical controllers. Finally, the influence of hull foundation vibration on the proposed controller is analyzed. The pointing accuracy of a moving tank gun is verified to be controlled effectively by the proposed controller under different driving conditions. This work combines control theory with multi-body dynamics to provide a feasible solution for the pointing control problem of a moving tank with model uncertainty and foundation vibration.