Robust sensor fault estimation scheme for satellite attitude control systems

The present paper proposes two new schemes of sensor fault estimation for a class of nonlinear systems and investigates their performances by applying these to satellite control systems. Both of the schemes essentially transform the original system into two subsystems (subsystems 1 and 2), where subsystem-1 includes the effects of system uncertainties, but is free from sensor faults and subsystem-2 has sensor faults but without any uncertainties. Sensor faults in subsystem-2 are treated as actuator faults by using integral observer based approach. The effects of system uncertainties in subsystem-1 can be completely eliminated by a sliding mode observer (SMO). In the first scheme, the sensor faults present in subsystem-2 are estimated with arbitrary accuracy using a SMO. In the second scheme, the sensor faults are estimated by designing an adaptive observer (AO). The sufficient condition of stability of the proposed schemes has been derived and expressed as a linear matrix inequality (LMI) optimization problem and the design parameters of the observers are determined by using LMI techniques. The effectiveness of the schemes in estimating sensor faults is illustrated by considering an example of a satellite control system. The results of the simulation demonstrate that the proposed schemes can successfully estimate sensor faults even in the presence of system uncertainties.     

Adaptive fault-tolerant attitude control for hypersonic reentry vehicle subject to complex uncertainties

In this paper, a novel fast attitude adaptive fault-tolerant control (FTC) scheme based on adaptive neural network and command filter is presented for the hypersonic reentry vehicles (HRV) with complex uncertainties which contain parameter uncertainties, un-modeled dynamics, actuator faults, and external disturbances. To improve the performance of closed-loop FTC, command filter and neural network are introduced to reconstruct system nonlinearities that are related to complex uncertainties. Compared with the FTC scheme with only neural network, the FTC scheme with command filter and neural network has fewer controller design parameters so that the computational complexity is decreased and the control efficiency is improved, which is of great significance for HRV. Then, the adaptive backstepping fault-tolerant controller based on command filter and neural network is designed, which can solve the complexity explosion problem in the standard backstepping control and the small uncertainty problem in the backstepping control only containing command filter. Moreover, to improve the approximation accuracy of the neural network-based universal approximator, an adaptive update law of neural network weights is designed by using the convex optimization technique. It is proved that the presented FTC scheme can ensure that the closed-loop control system is stable and the tracking errors are convergent. Finally, simulation results are carried out to verify the superiority and effectiveness of the presented FTC scheme.     

Dynamic learning-based fault tolerant control for robotic manipulators with actuator faults

In this paper, a learning-based active fault-tolerant control (FTC) scheme for robot manipulators with uncertainties and actuator faults is proposed. Unlike traditional FTC methods, with dynamic learning theory, both uncertainties and actuator faults can be accurately identified/learned by radial basis function networks. Based on the learned knowledge, dynamical classifiers and experience-based controllers corresponding to different fault modes are constructed. With the help of dynamical classifiers, fault detection and isolation can be obtained rapidly and accurately, and the correct experience-based controller (instead of the controller reconfigured online) corresponding to the current fault system is selected to compensate for faults, and superior control performance is achieved, even in the presence of faults. The simulation studies demonstrate the feasibility of the proposed FTC method.     

Neural network-based sensor fault estimation and active fault-tolerant control for uncertain nonlinear systems

In this work, we developed a novel active fault-tolerant control (FTC) design scheme for a class of nonlinear dynamic systems subjected simultaneously to modelling imperfections, parametric uncertainties and sensor faults. Modelling imperfections and parametric uncertainties are dealt with using an adaptive radial basis function neural network (RBFNN) that estimates the uncertain part of the system dynamics. For sensor fault estimation (FE), a nonlinear observer based on the estimated dynamics is designed. A scheme to estimate sensor faults in real-time using the nonlinear observer and an additional RBFNN is developed. The convergence properties of the RBFNN, used in the fault FE part, are improved by using a sliding surface function. For FTC design, a sliding surface is designed that incorporates the real-time sensor FE. The resulting sliding mode control (SMC) technique-based FTC law uses the estimated dynamics and real-time sensor FE. A double power-reaching law is adopted to design the switching part of the control law to improve the convergence and mitigate the chattering associated with the SMC. The FTC works well in the presence and absence of sensor faults without the requirement for controller reconfiguration. The stability of the proposed active FTC law is proved using the Lyapunov method. The developed scheme is implemented on a nonlinear simulation of an unmanned aerial vehicle (UAV). The results show good performance of the proposed unified FE and the FTC framework.     

Synchronization for chaotic systems via mixed-objective dynamic output feedback robust model predictive control

This paper focuses on mixed-objective dynamic output feedback robust model predictive control (OFRMPC) for the synchronization of two identical discrete-time chaotic systems with polytopic uncertainties, energy bounded disturbances, and input constraint. Using active control strategy, the chaos synchronization is transformed into standard dynamic OFRMPC scenarios tractable through receding horizon min–max optimization. Utilizing the notion of quadratic boundedness, the augmented closed-loop stability is further characterized. Then, the concepts of mixed performance criteria are firstly incorporated into the dynamic OFRMPC scheme to guarantee both the robust stability and the disturbance attenuation ability while preserving better dynamical behaviors. Necessary and/or sufficient conditions for desired mixed-objective dynamic OFRMPC are formulated involving linear matrix inequalities (LMIs). Finally, two numerical examples are given to demonstrate the theoretical results.     

Design and implementation of a new sliding mode controller on an underactuated wheeled inverted pendulum

In this paper, a sliding mode controller (SMC) is proposed for control of a wheeled inverted pendulum (WIP) system, which consists of a pendulum and two wheels in parallel. The control objective is to use only one actuator to perform setpoint control of the wheels while balance the pendulum around the upright position, which is an unstable equilibrium. When designing the SMC for the WIP system, various uncertainties are taken into consideration, including matched uncertainties such as the joint friction, and unmatched uncertainties such as the ground friction, payload variation, or road slope. The SMC proposed is capable of handling system uncertainties and applicable to general underactuated systems with or without input coupling. For switching surface design, the selection of the switching surface coefficients is in general a sophisticated design issue because those coefficients are nonaffine in the sliding manifold. In this work, the switching surface design is transformed into a linear controller design, which is simple and systematic. By virtue of the systematic design, various linear control techniques, such as linear quadratic regulator (LQR) or linear matrix inequality (LMI), can be incorporated in the switching surface design to achieve optimality or robustness for the sliding manifold. To further improve the WIP responses, the design of reference signals is addressed. The reference position for the pendulum is adjusted according to the actual equilibrium of the pendulum, which depends on the size of the friction and slope angle of the traveling surface. A smooth reference trajectory for the setpoint of the wheel is applied to avoid abrupt jumps in the system responses, meanwhile the reaching time of the switching surface can be reduced. The effectiveness of the SMC is validated using intensive simulations and experiment testings.     

Output feedback Cross-Coupled Nonlinear PID based MIMO control scheme for Pressurized Heavy Water Reactor

The dynamics of Pressurized Heavy Water Reactor (PHWR) are complex and open-loop unstable in nature. In such systems, parametric and input disturbances may cause instability if the control system fails to reject these disturbances. For such a large, unstable and uncertain process, designing a control scheme with the ability to reject disturbances along with good reference tracking capabilities is a challenging problem. The control scheme should not only be robust but also deterministic and easier to implement. In order to fulfill all these control scheme requirements for nuclear industries, in this work, a Cross-Coupled Nonlinear Proportional Integral Derivative (CCN-PID) scheme is suggested for a 70th order Multi-Input Multi-Output (MIMO) PHWR. It is also shown in this work that the proposed CCN-PID is a simple Cross-Coupled Proportional, Nonlinear Integrator and Derivative (CC-PNID) sliding surface based Sliding Mode Control (SMC). Furthermore, for the output feedback design, a High Gain Observer (HGO) is constructed for the PHWR process. In order to assure robust stability of the closed loop system, a Lyapunov based analysis of the state feedback CCN-PID control scheme is firstly presented. Then, in a similar way, robust stability analysis of HGO is carried out and finally, the stability analysis of the HGO and CCN-PID based output feedback control scheme is evaluated. In order to investigate the performance of the designed HGO based output feedback CCN-PID control scheme, four different scenarios are simulated. The results of these simulations show that the suggested control scheme efficiently rejects parametric uncertainties and input disturbances and corrects the power tilts while keeping the reactor stable and within safe limits of operation. The results also show that the scheme controls the reactor in an effective manner such that the reactor power closely follows the reference signal. The results of the control scheme presented in this work are also compared with earlier works.     

Decoupling and robust control of velocity-varying four-wheel steering vehicles with uncertainties via solving Attenuating Diagonal Decoupling problem

This paper is devoted to solve the combined problem of input–output decoupling and robust control of the four-wheel steering vehicles. A more practical three-degree-of-freedom systems covering longitudinal, lateral and yaw motions are used to improve the safety and steerability while uncertainties and external disturbances are considered. A novel decoupling conception Attenuating Diagonal Decoupling and a new index Coupling Attenuation Index are introduced and the system is divided up into two systems with a special structure. The first system is caused by uncertainties and disturbances and the second system is a certain system coupling with the first one. A control scheme composed of a coupling attention controller and a decoupling controller are explored. The influences of the uncertainties and disturbances on the output are attenuated under the coupling index by the coupling attention controller designed for the first system while the input–output decoupling is achieved by employing the decoupling controller designed for the second system. Furthermore, we prove in theory that the input–output decoupling and robust control are both established for the closed-loop system of the control scheme and the primordial vehicle system. Besides these works, a switching law is introduced such that the above excellent performances are realizable in four-wheel steering vehicles with conventional steering interfaces. Simulations show that even with a large velocity varying range, the decoupling and robust performances are guaranteed simultaneously, i.e. the handling stability and steerability are improved.     

Real time observer and control scheme for a wind turbine system based on a high order sliding modes

The introduction of advanced control algorithms may improve considerably the efficiency of wind turbine systems. This work proposes a high order sliding mode (HOSM) control scheme based on the super twisting algorithm for regulating the wind turbine speed in order to obtain the maximum power from the wind. A robust aerodynamic torque observer, also based on the super twisting algorithm, is included in the control scheme in order to avoid the use of wind speed sensors. The presented robust control scheme ensures good performance under system uncertainties avoiding the chattering problem, which may appear in traditional sliding mode control schemes. The stability analysis of the proposed HOSM observer is provided by means of the Lyapunov stability theory. Experimental results show that the proposed control scheme, based on HOSM controller and observer, provides good performance and that this scheme is robust with respect to system uncertainties and external disturbances.     

Iterative learning control for boundary tracking of uncertain nonlinear wave equations

This work presents a framework of iterative learning control (ILC) design for a class of nonlinear wave equations. The main contribution lies in that it is the first time to extend the idea of well-established ILC for lumped parameter systems to boundary tracking control of nonlinear hyperbolic distributed parameter systems (DPSs). By fully utilizing the system repetitiveness, the proposed control algorithm is capable of dealing with time-space-varying and even state-dependent uncertainties. The convergence and robustness of the proposed ILC scheme are analyzed rigorously via the contraction mapping methodology and differential/integral constraints without any system dynamics simplification or discretization. In the end, two examples are provided to show the efficacy of the proposed control scheme.     

Natural surface design for sliding mode control with multiple discontinuous inputs

It is well known that sliding mode control is based on the definition of an invariant manifold, where the system dynamics are forced to in a finite time. Such a manifold is somewhat arbitrarily defined, as long as the system dynamics are stable on it. Computational and control effort may vary depending on selected manifold. Obviously, if a system has naturally acceptable stable dynamics around a desired equilibrium point, no control is needed unless uncertainties or disturbances are present. It would be desirable that if such a system had uncertainties or disturbances, the control effort be designed only to overcome the effect of such factors. For a system with first order dynamics and affine control input, designing a sliding mode control overcoming only such uncertainties or disturbances is a trivial task. When a higher order dynamics system is involved, unit control may be used, where the input control signals are not discontinuous, but when only discontinuous control inputs are available, a design approach is not readily available. In this paper, taking advantage of the natural stable dynamics of a system, a sliding mode control approach is introduced for designing multiple discontinuous control inputs, where the control effort overcomes only uncertainties, disturbances or unstable dynamics. Two illustrative examples are given in order to show the feasibility of the method.     

Decentralized event-triggered finite-time attitude consensus control of multiple spacecraft under directed graph

This article investigates the finite-time consensus problem for the attitude system of multiple spacecraft under directed graph, where the communication bandwidth constraint, inertia matrix uncertainties and external disturbances are considered. An event-triggered communication mechanism is developed to address the problem of communication bandwidth constraint. In this event-triggered mechanism, spacecraft sends their attitude information to their neighbors only when the given event is triggered. Furthermore, an adaptive law is designed to counteract the effect of inertia matrix uncertainties and external disturbances. Then, a finite-time attitude consensus tracking control scheme is proposed based on the event-triggered communication mechanism and adaptive law. The proposed control scheme can guarantee the finite-time stability and convergence of the multiple spacecraft systems and exclude the Zeno phenomenon. Finally, simulation results validate the effectiveness of the proposed control scheme.     

Adaptive learning tracking for uncertain systems with partial structure information and varying trial lengths

This paper considers the adaptive iterative learning control (ILC) for continuous-time parametric nonlinear systems with partial structure information under iteration-varying trial length environments. In particular, two types of partial structure information are taken into account. The first type is that the parametric system uncertainty can be separated as a combination of time-invariant and time-varying part. The second type is that the parametric system uncertainty mainly contains time-invariant part, whereas the designed algorithm is expected to deal with certain unknown time-varying uncertainties. A mixing-type adaptive learning scheme and a hybrid-type differential-difference learning scheme are proposed for the two types of partial structure information cases, respectively. The convergence analysis under iteration-varying trial length environments is strictly derived based on a novel composite energy function. Illustrative simulations are provided to verify the effectiveness of the proposed schemes.     

Design of digital controllers for uncertain chaotic systems using fuzzy logic

A new and systematic method to design digital controllers for uncertain chaotic systems with structured uncertainties is presented in this paper. Takagi-Sugeno (TS) fuzzy model is used to model the chaotic dynamic system, while the uncertainties are decomposed such that the uncertain chaotic system can be rewritten as a set of local linear models with an additional disturbed input. Conventional control techniques are utilized to develop the continuous-time controllers first. Then, the digital controllers are obtained as the digital redesign of the continuous-time controllers using the state-matching approach. The performance of the proposed controller design is illustrated through numerical examples.     

Approximate decoupling and output tracking for MIMO nonlinear systems with mismatched uncertainties via ADRC approach

In this paper, we consider output tracking for a class of MIMO nonlinear systems which are composed of coupled subsystems with vast mismatched uncertainties. First, all uncertainties influencing the performance of controlled outputs, which include internal unmodelled dynamics, external disturbances, and uncertain nonlinear interactions between subsystems, are refined into the total disturbance in the control channels of subsystems. The total disturbance is shown to be sufficiently reflected in the measured output of each subsystem so that it can be estimated in real time by an extended state observer (ESO) in terms of the measured outputs. Second, we decouple approximately the MIMO systems by cancelling the total disturbance based on ESO estimation so that each subsystem becomes approximately independent linear time invariant one without uncertainty and interaction with other subsystems. Finally, we design an ESO based output feedback for each subsystem separately to ensure that the closed-loop state is bounded, and the closed-loop output of each subsystem tracks practically a given reference signal. This is completely in comply with the spirit of active disturbance rejection control (ADRC). Some numerical simulations are presented to demonstrate the effectiveness of the proposed output feedback control scheme.     

Robust non-fragile proportional plus derivative state feedback control for a class of uncertain Takagi–Sugeno fuzzy singular systems

This paper proposes a novel robust non-fragile proportional plus derivative state feedback (PDSF) control scheme for a class of uncertain nonlinear singular systems. The Takagi–Sugeno (T–S) fuzzy model is employed to represent the nonlinear singular system with parameter uncertainties appearing not only in distinct state matrices, but also in distinct derivative matrices. By using the free-weighting matrix technique, some sufficient conditions, which guarantee the resulting closed-loop system to be normal and stable (NS), are presented. With these conditions, the problems of non-fragile PDSF controllers design with additive and multiplicative uncertainties are respectively solved in terms of linear matrix inequalities (LMIs), which can be conveniently solved via the convex optimization technique. Finally, two examples are provided to illustrate the validity of the presented results.     

Stabilization of switched delay systems with polytopic uncertainties under asynchronous switching

In this paper, the problem of stabilization for a class of switched delay systems with polytopic type uncertainties under asynchronous switching is investigated. When the switching of the controllers has a lag to the switching of subsystems, i.e. the switching signal of the switched controller involves delay, parameter-dependent Lyapunov functionals are constructed, which are allowed to increase during the running time of active subsystems with the mismatched controller. Based on the average dwell time method, sufficient conditions for exponential stability are developed for a class of switching signals. Finally, a river pollution control problem is given to demonstrate the feasibility and effectiveness of the proposed design techniques.     

Active fault tolerant control design for reusable launch vehicle using adaptive sliding mode technique

In this paper, the problem of active fault tolerant control for a reusable launch vehicle (RLV) with actuator fault using both adaptive and sliding mode techniques is investigated. Firstly, the kinematic equations and dynamic equations of RLV are given, which represent the characteristics of RLV in reentry flight phase. For the dynamic model of RLV in faulty case, a fault detection scheme is proposed by designing a nonlinear fault detection observer. Then, an active fault tolerant tracking strategy for RLV attitude control systems is presented by making use of both adaptive control and sliding mode control techniques, which can guarantee the asymptotic output tracking of the closed-loop attitude control systems in spite of actuator fault. Finally, simulation results are given to demonstrate the effectiveness of the developed fault tolerant control scheme.     

Exponential synchronization of coupled neutral-type neural networks with mixed delays via quantized output control

In this paper, new control scheme is considered for exponential synchronization of coupled neutral-type neural networks (NTNNs) with both bounded discrete-time delay and unbounded distributed delay (mixed delays). It is assumed that only the measured output can be utilized to design the controller. Quantized output controllers (QOCs) are considered to save the bits rate of communication channels and the bandwidth. The main difficulty in solving this problem is to cope with the neutral terms, the delays, and the uncertainties induced by the quantization simultaneously. By designing new Lyapunov–Krasovskii functionals and proposing novel analytical techniques, sufficient conditions are derived to ensure the exponential synchronization of the interested NTNNs. The control gains are given by solving a set of linear matrix inequalities (LMIs), which are not necessarily to be negative-definite matrices. Numerical examples are provided to verify the effectiveness and merits of the proposed approach.     

Robust input shaping control for multi-mode flexible structures using neuro-sliding mode output feedback control

Input shaping provides an effective method for suppressing residual vibration of flexible structure systems. However, it is not very robust to parameter uncertainties and external disturbances. In this paper, a closed-loop input shaping method is developed for suppressing residual vibration of multi-mode flexible structure systems with parameter uncertainties and external disturbances. The proposed scheme integrates both input shaping control and discrete-time neuro-sliding mode output feedback control (NSMOFC). The input shaper is designed for the reference model and implemented outside of the feedback loop to achieve the exact elimination of residual vibration. In the feedback loop, the discrete-time NSMOFC technique is employed to make the closed-loop system behave like the reference model with input shaper, where the residual vibration is suppressed. The selection of switching surface and the existence of sliding mode have been addressed. The knowledge of upper bound of uncertainties is not required. Furthermore, it is shown that increasing the robustness to parameter uncertainties does not lengthen the duration of the impulse sequence. Simulation results demonstrate the efficacy of the proposed closed-loop input shaping control scheme.