Nonlinear robust adaptive control for bidirectional stabilization system of all-electric tank with unknown actuator backlash compensation and disturbance estimation

Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.

Optimizing PID controller parameters for robust automatic voltage regulator system through indirect design approach-2

Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage.Although advanced PID tuning methods have been proposed,the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties.This requires continuous fine tuning of the PID parameters.However,manual adjustment of these parameters can compromise the stability and robustness of the AVR system.This study focuses on the online self-tuning of PID controllers called indirect design approach-2(IDA-2)in AVR systems while preserving robustness.In particular,we indirectly tune the PID controller by shifting the frequency response.The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters.Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously,thereby improving the control performance and robustness.We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins(GMs)and phase margins(PMs)with previously optimized PID parameters during parameter uncertainties.The proposed method is further evaluated in terms of disturbance rejection,measurement noise,and frequency response analysis during parameter uncertainty calculations against existing methods.Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system.In summary,online self-tuning enables automated PID parameter adjustment in an AVR system,while maintaining stability and robustness.

The prediction of projectile-target intersection for moving tank based on adaptive robust constraint-following control and interval uncertainty analysis

To improve the hit probability of tank at high speed,a prediction method of projectile-target intersection based on adaptive robust constraint-following control and interval uncertainty analysis is proposed.The method proposed provides a novel way to predict the impact point of projectile for moving tank.First,bidirectional stability constraints and stability constraint-following error are constructed using the Udwadia-Kalaba theory,and an adaptive robust constraint-following controller is designed considering uncertainties.Second,the exterior ballistic ordinary differential equation with uncertainties is integrated into the controller,and the pointing control of stability system is extended to the impact-point control of projectile.Third,based on the interval uncertainty analysis method combining Chebyshev polynomial expansion and affine arithmetic,a prediction method of projectile-target intersection is proposed.Finally,the co-simulation experiment is performed by establishing the multi-body system dynamic model of tank and mathematical model of control system.The results demonstrate that the prediction method of projectile-target intersection based on uncertainty analysis can effectively decrease the uncertainties of system,improve the prediction accuracy,and increase the hit probability.The adaptive robust constraint-following control can effectively restrain the uncertainties caused by road excitation and model error.

Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the Differential Evolution Algorithm

This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data.Sufficient conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack matrices.Subsequently,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect.Finally,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.

Adaptive Robust Control with Leakage-Type Control Law for Trajectory Tracking of Exoskeleton Robots

This paper investigates the trajectory following problem of exoskeleton robots with numerous constraints. However, as a typical nonlinear system with variability and parameter uncertainty, it is difficult to accurately achieve the trajectory tracking control for exoskeletons. In this paper, we present a robust control of trajectory tracking control based on servo constraints. Firstly, we consider the uncertainties (e.g., modelling errors, initial condition deviations, structural vibrations, and other unknown external disturbances) in the exoskeleton system, which are time-varying and bounded. Secondly, we establish the dynamic model and formulate a close-loop connection between the dynamic model and the real world. Then, the trajectory tracking issue is regarded as a servo constraint problem, and an adaptive robust control with leakage-type adaptive law is proposed with the guaranteed Lyapunov stability. Finally, we conduct numerical simulations to verify the performance of the proposed controller.

Robust Nonlinear Current Sensorless Control of the Boost Converter with Constant Power Load

The boost converter feeding a constant power load (CPL) is a non-minimum phase system that is prone to the destabilizing effects of the negative incremental resistance of the CPL and presents a major challenge in the design of stabilizing controllers. A PWM-based current-sensorless robust sliding mode controller is developed that requires only the measurement of the output voltage. An extended state observer is developed to estimate a lumped uncertainty signal that comprises the uncertain load power and the input voltage, the converter parasitics, the component uncertainties and the estimation of the derivative of the output voltage needed in the implementation of the controller. A linear sliding surface is used to derive the controller, which is simple in its design and yet exhibits excellent features in terms of robustness to external disturbances, parameter uncertainties, and parasitics despite the absence of the inductor’s current feedback. The robustness of the controller is validated by computer simulations.

ROBUST ADAPTIVE CONTROL SCHEME FOR IMPROVING LOW-SPEED PROFILE TRACKING PERFORMANCE OF HYBRID STEPPING MOTOR SERVO DRIVE

A robust adaptive control approach is presented to improve the performance of the control scheme proposed in the authors＇ previous work, aiming at producing a low ripple hybrid stepping motor servo drive for precision profile tracking at a low speed. In order to construct a completely integrated control design philosophy to reduce torque ripple and at the same time to enhance tracking performance, the properties of nonlinear uncertainties in the system dynamics are uncovered, and then incorporated into the design of the controller. The system uncertainties concerned with ripple dynamics and other external disturbances are composed of two categories. The first category of uncertainties with linear parameterization arising from the detention effect is dealt with by the wellknown adaptive control method. A robust adaptive method is used to deal with the second category of uncertainties resulting from the non-sinusoidal flux distribution. The μ-modification scheme is used to cease parameter adaptation by the robust adaptive control law, thus ensuring that the trajectory tracking error asymptotically converges to a pre-specified boundary. Experiments are performed with a typical hybrid stepping motor to test its profile tracking accuracy. Results confirm the proposed control scheme.

Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.

Delay-dependent Robust H∞ Control for Uncertain Singular Systems with State Delay

这份报纸讨论延期依赖者的问题为有州的延期的不明确的单个系统的柔韧的 H 控制。把途径基于线性矩阵不平等(LMI ) ，我们设计一个州的反馈控制器，它保证为所有可被考虑的无常，结果的靠近环的系统是常规的，推动与 H 免费、稳定的标准界限限制。所有获得的结果是延期依赖者并且由不包含系统矩阵的分解的严格的 LMI 提出。数字例子证明建议方法不比存在的保守。

Improved Hybrid Robust Control Method for the Electromechanical Actuator in Aircrafts

In the flight process of aircrafts, their electromechanical actuators（EMA） must have the ability of enduring uncertainties caused by factors such as load disturbance, the variation of work temperature and the EMA＇s nonlinearity. At present, in order to increase the EMA＇s robustness on the uncertainties, the H, control method has been applied in aircrafts. The major problems with standard H∞ control lie in the large overshoot of step response and the high orders of the controller. For the purpose of addressing the two problems, this paper investigates several kinds of robust control strategies of the EMA. A mathematical model of the EMA is first built, and then with MATLAB software a H∞ controller and an improved hybrid robust controller composed of a reduced order H∞controller and a lead compensator are designed. In order to make a scientific comparison of the control effects of H∞ controller, hybrid controller and classic proportion-integral-differential（PID） controller, a simulation research is made in respect of the open loop frequency response and the closed loop step response of the three controllers. For comparing the robustness of the three controllers, the load torque is entered as a disturbance and the disturbance response of error and control input are thus obtained. The experiments with the three controllers are also conducted. Through giving the EMA a command and a disturbance torque successively, the transient response and disturbing process of EMA are recorded. The simulation and experiment results show that with the help of the hybrid controller, the EMA not only guarantees good dynamic characteristics, but also has strong robustness of disturbance rejection. Therefore, the excogitated H∞ hybrid control method effectively solves the problem of large overshoot in dynamic response, and moderately meets the requirement of overcoming the uncertainties in the EMA of aircrafts.

An LMI approach to robust H-infinity control for uncertain singular time-delay systems

The problem of robust H-infinity control for a class of uncertain singular time-delay systems is studied in this paper. A new approach is proposed to describe the relationship between slow and fast subsystems of singular time- delay systems, based on which, a sufficient condition is presented for a singular time-delay system to be regular, impulse free and stable with an H-infinity performance. The robust H-infinity control problem is solved and an explicit expression of the desired state-feedback control law is also given. The obtained results are formulated in terms of strict linear matrix inequalities （LMIs） involving no decomposition of system matrices. A numerical example is given to show the effectiveness of the proposed method.

Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

Modeling and Robust Backstepping Sliding Mode Control with Adaptive RBFNN for a Novel Coaxial Eight-rotor UAV

This paper focuses on the robust attitude control of a novel coaxial eight-rotor unmanned aerial vehicles (UAV) which has higher drive capability as well as greater robustness against disturbances than quad-rotor UAV. The dynamical and kinematical model for the coaxial eight-rotor UAV is developed, which has never been proposed before. A robust backstepping sliding mode controller (BSMC) with adaptive radial basis function neural network (RBFNN) is proposed to control the attitude of the eightrotor UAV in the presence of model uncertainties and external disturbances. The combinative method of backstepping control and sliding mode control has improved robustness and simplified design procedure benefiting from the advantages of both controllers. The adaptive RBFNN as the uncertainty observer can effectively estimate the lumped uncertainties without the knowledge of their bounds for the eight-rotor UAV. Additionally, the adaptive learning algorithm, which can learn the parameters of RBFNN online and compensate the approximation error, is derived using Lyapunov stability theorem. And then the uniformly ultimate stability of the eight-rotor system is proved. Finally, simulation results demonstrate the validity of the proposed robust control method adopted in the novel coaxial eight-rotor UAV in the case of model uncertainties and external disturbances. © 2014 Chinese Association of Automation.

Robust H∞ Networked Control for Uncertain Fuzzy Systems with Time-delay

柔韧的 H 联网了控制方法因为有无常和时间的模糊系统推迟的 Takagi-Sugeno (T-S ) 被介绍。一个州的反馈控制器经由联网的控制系统(NCS ) 被设计理论。为有 H 性能的柔韧的稳定性的足够的状况被获得。在网络传播和包退学学生的导致网络的延期被分析。模拟结果显示出这个控制计划的有效性。

Robust adaptive control for a nonholonomic mobile robot with unknown parameters

A robust adaptive controller for a nonholonomic mobile robot with unknown kinematic and dynamic parameters is proposed. A kinematic controller whose output is the input of the relevant dynamic controller is provided by using the concept of backstepping. An adaptive algorithm is developed in the kinematic controller to approximate the unknown kinematic parameters, and a simple single-layer neural network is used to express the highly nonlinear robot dynamics in terms of the known and unknown parameters. In order to attenuate the effects of the uncertainties and disturbances on tracking performance, a sliding mode control term is added to the dynamic controller. In the deterministic design of feedback controllers for the uncertain dynamic systems, upper bounds on the norm of the uncertainties are an important clue to guarantee the stability of the closed-loop system. However, sometimes these upper bounds may not be easily obtained because of the complexity of the structure of the uncertainties. Thereby, simple adaptation laws are proposed to approximate upper bounds on the norm of the uncertainties to address this problem. The stability of the proposed control system is shown through the Lyapunov method. Lastly, a design example for a mobile robot with two actuated wheels is provided and the feasibility of the controller is demonstrated by numerical simulations.

Comparative Study of Trajectory Tracking Control for Automated Vehicles via Model Predictive Control and Robust H-infinity State Feedback Control

A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC controllers’performance in tracking predefined trajectory under different scenarios.MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire,which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode.RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison.Then,three test cases are built in CarSim-Simulink joint platform.Specifically,the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions.Besides,the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability.Furthermore,an extreme curve test is built where the road adhesion changes suddenly,in order to test the performance of both controllers under extreme conditions.Finally,the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.

Robust H_∞ control for aseismic structures with uncertainties in model parameters

This paper presents a robust H∞ output feedback control approach for structural systems with uncertainties in model parameters by using available acceleration measurements and proposes conditions for the existence of such a robust output feedback controller. The uncertainties of structural stiffness, damping and mass parameters are assumed to be norm-bounded. The proposed control approach is formulated within the framework of linear matrix inequalities, for which existing convex optimization techniques, such as the LM1 toolbox in MATLAB, can be used effectively and conveniently. To illustrate the effectiveness of the proposed robust H∞ strategy, a six-story building was subjected both to the 1940 E1 Centro earthquake record and to a suddenly applied Kanai-Tajimi filtered white noise random excitation. The results show that the proposed robust H∞ controller provides satisfactory results with or without variation of the structural stiffness, damping and mass parameters.

Neural Network Based Robust Controller for Trajectory Tracking of Underwater Vehicles

A robust neural network controller （NNC） is presented for tracking control of underwater vehicles with uncertainties. The controller is obtained by using backstepping technique and Lyapunov function design in combination with neural network identification. Modeling errors and environmental disturbances are considered in the mathematical model. A twolayer neural network is introduced to compensate the modeling errors, while H∞ control strategy is used to achieve the L2-gain performance. The uniformly ultimately bounded （UUB） stabilities of tracking errors and NN weights are guaran- teed through the proposed controller. An on-line NN weights tuning algorithm is also propesed. Good performances of the tracking control system are illustrated bv the results of numerical simulations.

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 fault-tolerant 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 H_∞ control for uncertain descriptor systems with state and control delay

The problem of robust stabilization for uncertain continuous descriptor system with state and control delay is considered. The time-varying parametric uncertainty is assumed to be norm-bounded. The purpose of the robust stabilization is to design a memoryless state feedback law such that the resulting closed-loop system is robustly stable A sufficient condition that uncertain continuous descriptor system is robustly stabilizabled by state feedback law is derived in terms of linear matrix inequality （LMI）. Finally, a numerical example is provided to demonstrate the application of the proposed method.