Adaptive Robust Control for a Class of Uncertain MIMO Non-affine Nonlinear Systems

In this paper, the adaptive robust tracking control scheme is proposed for a class of multi-input and multioutput(MIMO) non-affine systems with uncertain structure and parameters, unknown control direction and unknown external disturbance based on backstepping technique. The MIMO nonaffine system is first transformed into a time-varying system with strict feedback structure using the mean value theorem,and then the bounded time-varying parameters are estimated by adaptive algorithms with projection. To handle the possible"controller singularity" problem caused by unknown control direction, a Nussbaum function is employed, and the dynamic surface control(DSC) method is applied to solve the problem of"explosion of complexity" in backstepping control. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through Lyapunov stability theorem and decoupled backstepping method. Simulation results are presented to illustrate the effectiveness of the proposed control scheme.

Pressure Regulation for Earth Pressure Balance Control on Shield Tunneling Machine by Using Adaptive Robust Control

Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control（ARC） are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve＇s dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.

Adaptive robust control for triple avoidance - striking - arrival performance of uncertain tank mechanical systems

This paper puts forward an unprecedented avoidance-striking-arrival problem aiming to address the need for tank's uncertain mechanical systems on the intelligent battlefield.The associated system uncertainties(possibly rapid)are time-varying but bounded(possibly unknown).The goal is to design a controller that enables the tank to aim at and attack the enemy tank while keeping itself(out of the enemy fire zone).The tank maintains this condition until reaching the predefined region.In this paper,an approximate constraint following control method is adopted to solve this problem,and the original constraints are creatively divided into two categories:the avoidance-tracking constraint and the striking-arrival constraint.An adaptive robust control method is proposed and consequently verified through simulation experiments.It is proved that the system fully obeys the avoidance-tracking-constraint and strictly obeys the striking-arrival constraint under the control input.Besides,the control of the tank vehicle running system and tank gun bidirectional stabilization system are unified to deal with the control signal delay caused by complex uncertainties on the battlefield.Overall,this paper reduced the delay of signal transmission in the system while solved the avoidance-striking-arrival problem.

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.

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.

Adaptive Robust Tracking Control of Pressure Trajectory Based on Kalman Filter

When adaptive robust control（ARC） strategy based on backstepping design is applied in pneumatic servo control, accurate pressure tracking in motion is especially necessary for both force and position trajectories tracking ofrodless pneumatic cylinders, and therefore an adaptive robust pressure controller is developed in this paper to improve the tracking accuracy of pressure trajectory in the chamber when the pneumatic cylinder is moving. In the proposed adaptive robust pressure controller, off-line fitting of the orifice area and on-line parameter estimation of the flow coefficient are utilized to have improved model compensation, and meanwhile robust feedback and Kalman filter are used to have strong robustness against uncertain nonlinearities, parameter fluctuations and noise. Research results demonstrate that the adaptive robust pressure controller could not only track various pressure trajectories accurately even when the pneumatic cylinder is moving, but also obtain very smooth control input, which indicates the effectiveness of adaptive model compensation. Especially when a step pressure trajectory is tracked under the condition of the movement of a rodless pneumatic cylinder, maximum tracking error of ARC is 4.46 kPa and average tracking error is 0.99 kPa, and steady-state error of ARC could achieve 0.84 kPa, which is very close to the measurement accuracy of pressure transducer.

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.

Motion synchronization of dual-cylinder pneumatic servo systems with integration of adaptive robust control and cross-coupling approach

We investigate motion synchronization of dual-cylinder pneumatic servo systems and develop an adaptive robust synchronization controller. The proposed controller incorporates the cross-coupling technology into the integrated direct/indirect adaptive robust control(DIARC) architecture by feeding back the coupled position errors, which are formed by the trajectory tracking errors of two cylinders and the synchronization error between them. The controller employs an online recursive least squares estimation algorithm to obtain accurate estimates of model parameters for reducing the extent of parametric uncertainties, and uses a robust control law to attenuate the effects of parameter estimation errors, unmodeled dynamics, and disturbances. Therefore, asymptotic convergence to zero of both trajectory tracking and synchronization errors can be guaranteed. Experimental results verify the effectiveness of the proposed controller.

Adaptive robust control of soft bending actuators:an empirical nonlinear model-based approach

Soft robotics,compared with their rigid counterparts,are able to adapt to uncharted environments,are superior in safe human-robot interactions,and have low cost,owing to the native compliance of the soft materials.However,customized complex structures,as well as the nonlinear and viscoelastic soft materials,pose a great challenge to accurate modeling and control of soft robotics,and impose restrictions on further applications.In this study,a unified modeling strategy is proposed to establish a complete dynamic model of the most widely used pneumatic soft bending actuator.First,a novel empirical nonlinear model with parametric and nonlinear uncertainties is identified to describe the nonlinear behaviors of pneumatic soft bending actuators.Second,an inner pressure dynamic model of a pneumatic soft bending actuator is established by introducing a modified valve flow rate model of the unbalanced pneumatic proportional valves.Third,an adaptive robust controller is designed using a backstepping method to handle and update the nonlinear and uncertain system.Finally,the experimental results of comparative trajectory tracking control indicate the validity of the proposed modeling and control method.

Guaranteeing the Fault Transient Performance of Aerospace Multiphase Permanent Magnet Motor System: an Adaptive Robust Speed Control Approach

To enhance the fault transient performance of aerospace multiphase permanent magnet synchronous motor(PMSM)system,an adaptive robust speed control is proposed regardless of the phase open-circuit(OC)and short-circuit(SC)fault in this paper,which can be applied for both the redundant motor system and fault tolerant motor system.For aerospace multiphase PMSM system,besides external load disturbance and system parameter perturbation,there inevitably exists the electromagnetic torque ripple in fault transient process,which can degrade the system performance and even cause the system instability.To cope with this issue,the electromagnet torque ripple of the multiphase PMSM system in fault transient process is first analyzed.Then,by considering the electromagnet torque fluctuation caused by fault transient as a system uncertainty,a novel adaptive robust speed control scheme is proposed,while the adaptive law is constructed to emulate the total system uncertainty bound,which include the load disturbance,the parameter variation,and the electromagnetic torque fluctuation due to fault transient.The resulting control can ensure the speed control performance even in fault transient process regardless of the uncertainty,in which no prior estimation of the uncertainty bound is required.In addition,the proposed adaptive robust speed control is demonstrated by a six-phase PMSM experimental platform.The novelty of this research is to explore a novel adaptive robust speed control to strengthen the fault tolerance performance of multiphase PMSM system even in fault transient process,which requires no prior estimation of the uncertainty bound.

Adaptive robust control for four-motor driving servo system with uncertain nonlinearities

A novel adaptive robust control （ARC） is presented for the four-motor driving servo systems with the uncertain nonlinearities and actuation failures, such that the load tracking control is achieved with the proximate optimal-time. By applying the proposed scheme, several control objectives are achieved. First, the nonlinear synchronization algorithm is presented to maintain the velocity synchronization of each motor, which provides fast convergence without chatting. Moreover, the time-varying bias torque is applied to eliminate the effect of backlash and reduce the waste of energy. Then, the ARC is designed to achieve the proximate optimal-time output tracking with the transient performance in L2 norm, where the friction and actuation failures are addressed by the adaptive scheme based on the norm estimation of unknown parameter vector. Finally, the extensive simulated and experimental results validate the effectiveness of the proposed method.

Impact dynamics analysis of free-floating space manipulator capturing satellite on orbit and robust adaptive compound control algorithm design for suppressing motion

The impact dynamics, impact effect, and post-impact unstable motion sup- pression of free-floating space manipulator capturing a satellite on orbit are analyzed. Firstly, the dynamics equation of free-floating space manipulator is derived using the sec- ond Lagrangian equation. Combining the momentum conservation principle, the impact dynamics and effect between the space manipulator end-effector and satellite of the cap- ture process are analyzed with the momentum impulse method. Focusing on the unstable motion of space manipulator due to the above impact effect, a robust adaptive compound control algorithm is designed to suppress the above unstable motion. There is no need to control the free-floating base position to save the jet fuel. Finally, the simulation is proposed to show the impact effect and verify the validity of the control algorithm.

Robust adaptive fuzzy tracking control for a class of strict-feedback nonlinear systems based on backstepping technique

In this paper, the robust adaptive fuzzy tracking control problem is discussed for a class of perturbed strict-feedback nonlinear systems. The fuzzy logic systems in Mamdani type are used to approximate unknown nonlinear functions. A design scheme of the robust adaptive fuzzy controller is proposed by use of the backstepping technique. The proposed controller guarantees semi-global uniform ultimate boundedness of all the signals in the derived closed-loop system and achieves the good tracking performance. The possible controller singularity problem which may occur in some existing adaptive control schemes with feedback linearization techniques can be avoided. In addition, the number of the on-line adaptive parameters is not more than the order of the designed system. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed control scheme.

Robust Adaptive Control for Mobile Manipulators

This paper addresses the trajectory tracking control of a nonholonomic wheeled mobile manipulator with parameter uncertainties and disturbances. The proposed algorithm adopts a robust adaptive control strategy where parametric uncertainties are compensated by adaptive update techniques and the disturbances are suppressed. A kinematic controller is first designed to make the robot follow a desired end-effector and platform trajectories in task space coordinates simultaneously. Then, an adaptive control scheme is proposed, which ensures that the trajectories are accurately tracked even in the presence of external disturbances and uncertainties. The system stability and the convergence of tracking errors to zero are rigorously proven using Lyapunov theory. Simulations results are given to illustrate the effectiveness of the proposed robust adaptive control law in comparison with a sliding mode controller.

Research of robust adaptive trajectory linearization control based on T-S fuzzy system

A robust adaptive trajectory linearization control （RATLC） algorithm for a class of nonlinear systems with uncertainty and disturbance based on the T-S fuzzy system is presented. The unknown disturbance and uncertainty are estimated by the T-S fuzzy system, and a robust adaptive control law is designed by the Lyapunov theory. Irrespective of whether the dimensions of the system and the rules of the fuzzy system are large or small, there is only one parameter adjusting on line. Uniformly ultimately boundedness of all signals of the composite closed-loop system are proved by theory analysis. Finally, a numerical example is studied based on the proposed method. The simulation results demonstrate the effectiveness and robustness of the control scheme.

Fuzzy adaptive robust control for space robot considering the effect of the gravity

Space robot is assembled and tested in gravity environment, and completes on-orbit service（OOS） in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control（FARC） strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative（PD） controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.

Adaptive robust feedback control of moving target tracking for all-Electrical tank with uncertainty

A moving target tracking control problem for marching tank based on adaptive robust feedback control scheme is addressed.A series of preparations is needed for tank gun before shooting a target,the purpose of this paper is to design a control system to fulfill two requirements in this process:the turretbarrel system of tank needs to be adjusted from off-target position to command position and point to the moving target stably when there are strong uncertainties(modeling error,uncertain disturbance with unknown boundaries and road excitation) in the system.Considering the characteristic of coupled interaction,the first thing we do in this paper is to build a coupled analysis model of turret-barrel system with uncertainty term in state-space form.Second,an adaptive robust feedback control scheme is proposed by adding adaptive law to overcome the uncertainty.Third,multi-body dynamics software is used to establish the mechanical mechanism of the tank,and DC-motor module is established in SIMULINK environment,thus the target information and tracking error of the control system is collected and transferred,the gear-ball screw is derived directly by the output torque of the DC-motor module.Finally,the control system and the 3D model are combined together by means of Recur Dyn/SIMULINK co-simulation,the turret-barrel system of tank can approximately track the moving target in a certain range.With the adaptive robust feedback control,the target action is completely followed when the target location is constantly changing.

A New Robust Adaptive Neural Network Backstepping Control for Single Machine Infinite Power System With TCSC

For a single machine infinite power system with thyristor controlled series compensation(TCSC) device, which is affected by system model uncertainties, nonlinear time-delays and external unknown disturbances, we present a robust adaptive backstepping control scheme based on the radial basis function neural network(RBFNN). The RBFNN is introduced to approximate the complex nonlinear function involving uncertainties and external unknown disturbances, and meanwhile a new robust term is constructed to further estimate the system residual error,which removes the requirement of knowing the upper bound of the disturbances and uncertainty terms. The stability analysis of the power system is presented based on the Lyapunov function,which can guarantee the uniform ultimate boundedness(UUB) of all parameters and states of the whole closed-loop system. A comparison is made between the RBFNN-based robust adaptive control and the general backstepping control in the simulation part to verify the effectiveness of the proposed control scheme.

Improved Robust Adaptive Control of a Fluidized Bed Combustor for Sewage Sludge

This paper presents a robust model reference adaptive control scheme to deal with un-certain time delay in the dynamical model of a ?uidized bed combustor for sewage sludge. Thetheoretical analysis and simulation results show that the proposed scheme can guarantee not onlystability and robustness, but also the adaptive decoupling performance of the system.

Robust adaptive control for dynamic systems with mixed uncertainties

The control problem for single-input single-output（SISO） systems in the presence of mixed uncertainties, both stochastic and deterministic uncertainties, is considered. The stochastic uncertainties are modeled as exogenous noises, while the deterministic uncertainties are time invariant and appear as the unknown parameters which lie in a bounded interval. Based on a subdivision for the continuous interval, a robust adaptive controller is designed. The controller can not only realize the system output to track the desired output, but also learn a more accurate interval which contains the true value of the unknown parameter with a learning error given in advance. An example is given finally to demonstrate the effectiveness of the proposed method.