Udwadia-Kalaba Equation Based Adaptive Robust Control for Two-wheeled Inverted Pendulum System: Underactuation and Uncertainty

A new adaptive robust control method based on Udwadia-Kalaba(U-K) approach which can be applied to the underactuated system is designed and used to a two-wheeled inverted pendulum system in this paper. We separate this typical underactuated system into two subsystems(forward subsystem and yaw subsystem), which are fully underactuated and actuated. For these different subsystems, we use different control methods. We apply an adaptive robust control method which has been proved many times to the fully actuated subsystem. Based on this adaptive robust method, a new control strategy can be redesigned and applied to the underactuated subsystem by modifying the adaptive law and other things. This adaptive robust control with a leakage-type adaptive law could guarantee the uniform boundedness and uniform ultimate boundedness of the system. Finally, the simulation is executed to demonstrate the advantage and simplicity of the proposed method.

     

Dynamic surface active fault tolerant control design for the attitude control systems of UAV with actuator fault

In this paper, an active fault tolerant control (FTC) approach based on transient performance index is proposed for the attitude control systems of unmanned aerial vehicle (UAV) with actuator fault. The nonlinear attitude control system model for UAV with actuator faults is given, which represents the dynamic characteristics of UAV. A fault diagnosis component is used for fault detection and estimation. According to the fault estimation information obtained during the fault diagnosis, the fault tolerant control scheme is developed by adopting the adaptive dynamic surface control technique, which guarantees the asymptotic output tracking and ultimate uniform boundedness of the closed-loop attitude control systems of UAV in actuator faulty case. Further, a prescribed transient performance of the FTC attitude control systems is considered which characterizes the convergence rate and maximum overshoot of the attitude tracking error. Finally, simulation results are shown that the attitude control system states remain bounded and the output tracking errors converge to a neighborhood of zero.     

A New High‐Order Adaptive Robust Control for Constraint Following of Mechanical Systems

A mechanical system is to follow a class of prescribed holonomic or nonholonomic constraints. The system contains time‐varying bounded uncertainty. However, the bound is unknown. The objective is to design a control which renders constraint following. A new high‐order adaptive robust control is proposed. The control guarantees uniform boundedness and uniform ultimate boundedness even in the presence of the uncertainty. Significant advantages of this new control are demonstrated both analytically and numerically. It is shown that the system performance, including the finite entering time, constraint‐following error, and control magnitude, can be improved by tuning the control order.     

Adaptive discrete-time controller design with neural network for hypersonic flight vehicle via back-stepping

In this article, the adaptive neural controller in discrete time is investigated for the longitudinal dynamics of a generic hypersonic flight vehicle. The dynamics are decomposed into the altitude subsystem and the velocity subsystem. The altitude subsystem is transformed into the strict-feedback form from which the discrete-time model is derived by the first-order Taylor expansion. The virtual control is designed with nominal feedback and neural network (NN) approximation via back-stepping. Meanwhile, one adaptive NN controller is designed for the velocity subsystem. To avoid the circular construction problem in the practical control, the design of coefficients adopts the upper bound instead of the nominal value. Under the proposed controller, the semiglobal uniform ultimate boundedness stability is guaranteed. The square and step responses are presented in the simulation studies to show the effectiveness of the proposed control approach.     

Adaptive control for an uncertain robotic manipulator with input saturations

In this paper, we address the control problem of an uncertain robotic manipulator with input saturations. For this purpose, a model reference adaptive control like (MRAC-like) approach is proposed to solve the problem. The model reference enjoyed input to state stable (ISS) property and driven by the current control signal is introduced. A combination of the regressor and non-regressor based approaches is used to estimate the uncertain parameters. The resulting controller ensures that the control signals satisfy the input saturations. In addition, the semi-global uniform ultimate boundedness of the closed-loop system is guaranteed and the tracking error converges to the compact set which depends on the predetermined bound of the control inputs. Simulation on a planar elbow manipulator with two joints is provided to illustrate the effectiveness of the proposed control design.     

一类关于不确定性机器人的鲁棒控制策略1)

基于计算力矩结构,研究参数和结构不确定的机器人轨迹跟踪的鲁棒控制策略.其特点是利用了机器人不确定动力学的集中包络函数,在该包络函数已知的情况下,设计的非线性连续补偿控制律能够有效消除系统的不确定性影响,保证系统达到三种不同的稳定性结果.另外,在该包络函数参数未知时,还设计了一个新颖的在线辨识器,可保证系统指数意义下的渐近收敛或一致有界.     

一类关于不确定性机器人的鲁棒控制策略

基于计算力矩结构,研究参数和结构不确定的机器人轨迹跟踪的鲁棒控制策略.其 特点是利用了机器人不确定动力学的集中包络函数,在该包络函数已知的情况下,设计的非 线性连续补偿控制律能够有效消除系统的不确定性影响,保证系统达到三种不同的稳定性结 果.另外,在该包络函数参数未知时,还没计了一个新颖的在线辨识器,可保证系统指数意义 下的渐近收敛或一致有界.     

Indirect adaptive robust control of nonlinear systems with time‐varying parameters in a strict feedback form

Without any prior knowledge of the physical bounds of unknown parameters and uncertain nonlinearities, an indirect adaptive robust controller is constructed for uncertain nonlinear time‐varying systems in a strict‐feedback form. Firstly, an adaptive strong robust controller is derived based on the command filtered adaptive backstepping approach. This controller not only can guarantee the boundedness of the closed‐loop system signals in the presence of time‐varying (TV) parameters and uncertain nonlinearities but also obviate the need to compute analytic derivatives of virtual control functions. Thus, the problem of “explosion of terms” in the standard adaptive backstepping technique is avoided. Through introduction of a simple adaptation law on the upper bound of uncertainties, a smooth robust control term is used to realize the disturbance attenuation. Afterwards, based on the nonlinear X‐swapping techniques, a modular approach in which the controller and the identifier can be designed separately is exploited. A novel algorithm is proposed to estimate the TV parameters accurately. By adopting the variation trend of the covariance matrix as an indicator of the driving signals' persistent excitation level, this online parameter estimation law is switched between a modified least‐squares algorithm and a gradient algorithm based on fixed σ‐modification. Finally, a series of properties on the asymptotic stability and the global uniform ultimate boundedness of the closed‐loop system is established. Simulation results verify the effectiveness of the suggested method.     

Supervisory switching‐based prescribed performance control of unknown nonlinear systems against actuator failures

This article studies the fault‐tolerant control problem for unknown nonlinear strict‐feedback systems subject to actuator failures yet with dynamic redundancies. The prescribed performance control methodology is newly combined with a modification‐based supervisory switching strategy to solve the problem. To implement failure detection, the performance function is properly modified to synthesize a monitoring function to supervise the behavior of an error variable. Once a failure is detected, the current actuator is shut down and the backup actuator is switched in to execute the reconfigured control command. Compared with the existing results, (1) the postfailure and postswitching tracking performance is improved, other than uniform ultimate boundedness and (2) the dependence on extra robust control schemes (eg, adaptive or approximating structures) to deal with model uncertainties or the need to compute analytic derivatives of virtual control signals in the backstepping design is eliminated.     

A ROBUST ADAPTIVE CONTROL DESIGN FOR A CLASS OF UNCERTAIN NONLINEAR MARKOVIAN JUMP SYSTEMS

A direct robust adaptive nonlinear control scheme for a class of uncertain nonlinear Markovian jump systems with nonlinear state‐dependent uncertainty is presented. The proposed scheme is Lyapunov‐based and guarantees the global uniform ultimate boundedness of the closed‐loop system in the mean sense. A numerical example is given to demonstrate the validity of the results.