Analysis and robust control of system with uncertainty and disturbance using equivalent-input-disturbance approach

This paper addresses the control problem of an uncertain system suffering from an exogenous disturbance. A new degree of control freedom is developed to handle the problem based on the equivalent-input-disturbance (EID) approach. The effect of the disturbance and uncertainties is equivalent to that of a fictitious disturbance on the control input channel, which is called an EID. A state observer and an improved EID (IEID) estimator are devised to produce an estimate that is used to compensate for the disturbance and uncertainties in a control law. A second-order low-pass filter is employed in the estimator to provide a way to solve a tradeoff between disturbance rejection and noise suppression. The slope of the Bode magnitude curve at high frequencies is two times larger for the IEID estimator than for a conventional one. This makes the IEID estimator less sensitive to measurement noise and more practical. Sufficient analyses reveal the mechanism of disturbance rejection, uncertainty attenuation, and noise suppression of an IEID-based control system. A theorem is derived to guarantee system stability and a procedure is presented for system design. Simulations and experiments of the position control of a magnetic levitation system are carried out to show the validity of the presented method.     

Fuzzy sliding mode control design of Markovian jump systems with time-varying delay

This paper studies the robust stochastic stabilization problem for a class of fuzzy Markovian jump systems with time-varying delay and external disturbances via sliding mode control scheme. Based on the equivalent-input-disturbance (EID) approach, an online disturbance estimator is implemented to reject the unknown disturbance effect on the considered system. Specifically, to obtain exact EID estimation Luenberger fuzzy state observer and a low-pass filter incorporated to the closed-loop system. Moreover, novel fuzzy EID-based sliding mode control law is constructed to ensure the stability of the closed-loop system with satisfactory disturbance rejection performance. By employing Lyapunov stability theory and some integral inequalities, a new set of delay-dependent robust stability conditions is derived in terms of linear matrix inequalities (LMIs). The resulting LMI is used to find the gains of the state-feedback controller and the state observer a for the resulting closed-loop system. At last, numerical simulations based on the single-link arm robot model are provided to illustrate the proposed design technique.     

A case study on the universal compensation-improvement mechanism: A robust PID filter-shaped optimal PI tracker for systems with/without disturbances

Many dynamical systems are continuous-time non-square with unknown mismatched input and output disturbances. For such systems, a universal on-line robust optimal tracking control is often desirable. In this paper, the conventional proportional-integral-differential (PID) controller is utilized as a fictitious PID filter to shape the tracking error in the frequency-domain using a quadratic performance index as a weighting function, such that the robust PID-shaped PI tracker integrated with the equivalent input disturbance (EID) estimator is established to carry out the on-line robust optimal tracking control of the general disturbed system. The benefits and discrepancies of the proposed compensation improvement mechanism over the conventional optimal trackers for continuous-time non-square systems with/without unknown mismatched input and output disturbances are listed as follows: (i) It develops a new net EID estimator without any previously established constraints on the dimensions of the system and on the disturbances; (ii) It provides an efficient estimated-state-feedback-based EID estimator in contrast to the conventional output-feedback-based EID estimators; (iii) It is able to carry out on-line EID estimation of the tracking errors for systems with endogenous/exogenous output disturbances; (iv) It is a universal tracker which can be simply implemented as a plug-in EID estimator for most servo systems, to improve the performance of any existing observers/trackers which are not allowed to be removed from the system. The advantages of the proposed method over two existing outstanding approaches reported in the literature are pointed out using illustrative examples.     

Event-triggered adaptive fuzzy tracking control for high-order stochastic nonlinear systems

This paper is concerned with event-triggered adaptive fuzzy tracking control for high-order stochastic nonlinear systems. The approach of fuzzy logic systems (FLSs) approximation is extended to high-order stochastic nonlinear systems to deal with the unknown nonlinear uncertainties. A novel high-order adaptive fuzzy tracking controller is firstly presented via a backstepping approach and event-triggering mechanism which can mitigate the unnecessary waste of computation and communication resources. Based on the above techniques, frequently-used growth assumptions imposed on unknown system nonlinearities are removed and the influence for the high order is handled. The proposed high-order adaptive fuzzy tracking control method not only deals with the influence of high order, but also ensures that the tracking error converges to a small neighborhood of the origin in probability. Finally, the effectiveness of the proposed control method is illustrated by a numerical example.     

Design of a preview repetitive control with equivalent-input-disturbance system based on a continuous-discrete 2D model

This paper deals with the problem of two-dimensional (2D) system-based preview repetitive control (PRC) with equivalent-input-disturbance (EID) for uncertain continuous-time systems. First, to use the available values of the reference signal, we construct an equality constraint which includes the output of a basic repetitive controller, preview compensation and tracking error. Next, to compensate the unknown external disturbances, we incorporate an EID estimator into the PRC controller. Then, by employing the 2D system theory together with the linear matrix inequality (LMI) approach, we derive a sufficient condition to ensure the robust stability of the closed-loop system. By solving an LMI, the gains of the controller and state observer can be obtained. The results obtained in this paper generalize and include some results in the existings. literature. Finally, a numerical simulation demonstrates the effectiveness and superiority of the proposed method.     

Improved decentralized prescribed performance control for non-affine large-scale systems with uncertain actuator nonlinearity

This work considers a decentralized control problem for non-affine large-scale systems with non-affine functions possibly being discontinuous. A semi-bounded condition for non-affine functions is presented to guarantee the controllability, and the non-affine system is transformed to an equivalent pseudo-affine one based on the mild condition. Different from conventional control schemes on specific actuator nonlinearity, the controller proposed in this paper can deal with a series of actuator nonlinearities such as backlash and deadzone nonlinearity. A time-varying stable manifold involving the tracking error and its high-order derivatives is utilized to handle the high-order dynamics of each subsystem. Besides an improved prescribed performance controller independent of the initial condition is constructed to ensure the finite-time convergence of the error manifold to a predefined region. The boundedness and convergence of the closed-loop system are proved by Lyapunov theory and the counter-evidence method. Two examples are performed to verify the theoretical findings.     

Disturbance rejection for time-delay systems based on the equivalent-input-disturbance approach

This paper presents a disturbance rejection method for time-delay systems. The configuration of the control system is constructed based on the equivalent-input-disturbance (EID) approach. A modified state observer is applied to reconstruct the state of the time-delay plant. A disturbance estimator is designed to actively compensate for the disturbances. Under such a construction of the system, both matched and unmatched disturbances are rejected effectively without requiring any prior knowledge of the disturbance or inverse dynamics of the plant. The presentation of the closed-loop system is derived for the stability analysis and controller design. Simulation results demonstrate the validity and superiority of the proposed method.     

High-order moment stabilization for Markov jump systems with attenuation rate

This paper studies the high-order moment control problem for discrete-time Markov jump linear systems (MJLSs) with certain dynamic response performance and disturbance rejection specifications. An appropriate cumulant generating function is employed to express the original stochastic system in high-order component form. This facilities the high-order moment stabilization of MJLSs. Moreover, a pole region assignment approach is utilized to ensure desired dynamic response specifications with a certain attenuation rate. An arithmetic and geometric inequality approach is utilized to extract sufficient conditions ensuring the designed controller existence. These conditions ensure the high-order moment steady-state property and certain dynamic specifications for the MJLSs. The effectiveness of the proposed method is demonstrated through numerical and practical examples.     

Robust control of unmanned helicopters with high-order mismatched disturbances via disturbance-compensation-gain construction approach

In this paper, a novel robust control strategy based on disturbance-compensation-gain (DCG) construction approach is proposed for small-scale unmanned helicopters in the presence of high-order mismatched disturbances. The overall control structure consists of two hierarchical layers. The inner-loop controller is to guarantee the stability of the unmanned helicopters subject to high-order mismatched disturbances. With the estimation of the disturbances and their successive derivatives via finite-time disturbance observer (FTDO), by properly designing some disturbance compensation gains, a novel robust controller is developed to remove the high-order mismatched disturbances from the output channels. The outer-loop controller is to produce flight commands for inner-loop system, as well as to track the reference trajectory, which is carried out with the dynamic inversion technique. The simulation results demonstrate that the unmanned helicopters are capable to perform flight missions autonomously with the proposed control strategy.     

Decentralized adaptive neuro-fuzzy dynamic surface control for maximum power point tracking of a photovoltaic system

The current work proposes a decentralized adaptive dynamic surface control approach for extracting the maximum power from a photovoltaic (PV) system and then regulating the required voltage for charging the battery. In this regard, two cascaded direct current-direct current (DC-DC) converters are utilized. The boost converter is interposed between the PV system and the load to help extract the maximum power. The buck-boost converter is then exploited to maintain the output voltage at a specified level which must meet the battery demand. Therefore, to handle the interactions between the cascaded converters, a decentralized control approach is developed. In the suggested approach, by introducing a nonlinear filter, an effective dynamic surface control (DSC) scheme is proposed with guaranteeing asymptotic tracking convergence. Further, by incorporating a nonlinear compensation term into the proposed control approach, the robustness of the resulting controller is improved. In addition, since the model of the converters is nonlinear with unknown uncertainties, the neuro-fuzzy system is used to estimate lumped uncertainties. The proposed control method has good attributes in terms of having a low tracking error, an excellent transition response, and a quick response to changes in atmospheric conditions. The stability of the whole control system is proved by the Lyapunov stability theorem. Finally, comprehensive simulation results are performed to validate the effectiveness of the suggested control approach.     

新冠肺炎疫情对公共卫生应急法治的重大挑战及对策建议

新冠肺炎疫情从发生到快速暴发流行,对我国现行以《传染病防治法》《突发公共卫生事件应急条例》为核心的公共卫生应急法律制度体系形成了重大的挑战。在新发突发传染病预防控制、疾病控制与公共应急事权配置、信息公开发布及防控紧急措施合法性等方面,均暴露出原有体系的明显短板和不足。因此,亟须根据当前疫情防控形势,尽快依法决定在疫情严重的局部区域宣布紧急状态;而在后续修法、立法中,要完善新发突发传染病风险应对防控制度体系,建立常态化公共卫生预警的法律机制,依法有效维护公众健康知情权。     

Analysis and tuning of reduced-order active disturbance rejection control

To reduce the phase lag introduced by extended state observer (ESO), an reduced-order active disturbance rejection control (RADRC) method is recommended. This paper investigates the structure and parameter tuning of RADRC. Firstly, it is shown that RADRC can serve as a general-purpose fixed-structure controller because any proper controller with integrator can be realized via an RADRC. Then the relationship between the parameters of an RADRC and those of a full-order linear active disturbance rejection control (LADRC) is analyzed. It is shown that an RADRC with the proper controller and observer gains can obtain similar disturbance-rejection performance as a full-order LADRC. Simulation results demonstrate that any plant that can be controlled by LADRC can also be controlled by an RADRC with a similar disturbance-rejection performance.     

High-order command filtered adaptive backstepping control for second- and high-order fully actuated strict-feedback systems

In this paper, a high-order command filtered adaptive backstepping (HOCFAB)-based approach is proposed in order to track a given reference signal for the second- and high-order strict-feedback systems (SFSs) with parametric uncertainties, where both their subsystems hold a common full-actuation structure, namely, high-order fully actuated (HOFA) SFSs. Unlike the prevailing traditional first-order state-space backstepping approach which suffers from the problem of “explosion of terms”, the proposed HOCFAB approach circumvents the complexity arising owing to differentiating the virtual controllers repeatedly, and does not need to convert the high-order systems into first-order forms which is easier to carry out and demands fewer steps. Meanwhile, an error-compensating mechanism is constructed to reduce filtering errors. A critical analysis is theoretically proven which indicates that in both cases the entire system states are uniformly ultimately bounded under the proposed high-order controller, and the tracking error could be made arbitrarily small with predesigned parameters. Finally, the effectiveness of the proposed scheme is verified by a benchmark application in the robotic manipulator.     

Decentralized asymptotic fault tolerant control of near space vehicle with high order actuator dynamics

In this paper, a decentralized asymptotic fault tolerant control system is proposed for near space vehicle (NSV) attitude dynamics. First, NSV reentry mode is described, and the actuator failure model is developed whose behavior is described by high-order dynamics. Next, the multi-model based fault diagnosis and identification (FDI) algorithm is proposed for high order actuator dynamics, which can accurately diagnose and identify the fault in short time. Based on sliding mode, command filter, and backstepping technique, using information of FDI, a constrained fault tolerant control (FTC) is designed for reentry NSV. Finally, simulation results are given to demonstrate the effectiveness and potential of the proposed FTC scheme.     

Adaptive Fuzzy Output Feedback Control for High-Order Switched Systems with Fuzzy Dead Zone

In this paper, an observer-based adaptive control problem for a class of high-order switched nonlinear systems in non-strict feedback form with fuzzy dead zone and arbitrary switchings is investigated. Fuzzy logic system was utilized to model the unknown nonlinear function with the universal approximation ability. An adaptive high-order observer is constructed to estimate unavailable state variables. The effect of dead zone can be eliminated by a Nussbaum function. By using the Lyapunov stability theory and backstepping design procedure, the proposed adaptive controller can guarantee all the variables in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB). Simulation results are exhibited to demonstrate the effectiveness of the proposed control scheme.     

Distributed optimal consensus protocol for high-order integrator-type multi-agent systems

Optimal consensus control of high-order multi-agent systems (MASs) modeled by multiple integrator-type dynamics is studied. A fully distributed optimal control protocol that achieves the specific consensus behavior is designed for MASs with linear dynamics, where topology-dependent conditions are removed. Further, a distributed consensus protocol for high-order nonlinear MASs with one-sided Lipschitz continuity is presented using the optimization approach, and the optimal solution can be obtained by solving a standard algebraic Riccati equation. Some numerical examples are finally provided to illustrate the effectiveness of the presented approaches.     

Barrier Lyapunov function-based decentralized adaptive neural control for uncertain high-order stochastic nonlinear interconnected systems with output constraints

Decentralized adaptive neural backstepping control scheme is developed for uncertain high-order stochastic nonlinear systems with unknown interconnected nonlinearity and output constraints. For the control of high-order nonlinear interconnected systems, it is assumed that nonlinear system functions are unknown. It is for the first time to control stochastic nonlinear high-order systems with output constraints. Firstly, by constructing barrier Lyapunov functions, output constraints are handled. Secondly, at each recursive step, only one adaptive parameter is updated to overcome over-parameterization problems, and RBF neural networks are used to identify unknown nonlinear functions so that the difficulties caused by completely unknown system functions and stochastic disturbances are tackled. Finally, based on the Lyapunov stability method, the decentralized adaptive control scheme via neural networks approximator is proposed, ultimately reducing the number of learning parameters. It is shown that the designed controller can guarantee all the signals of the resulting closed-loop system to be semi-globally uniformly ultimately bounded (SGUUB), and the tracking errors for each subsystem are driven to a small neighborhood of zero. The simulation studies are performed to verify the effectiveness of the proposed control strategy.     

Extended dissipative filtering for Markov jump BAM inertial neural networks under weighted try-once-discard protocol

This paper investigates the problem of extended dissipative filtering for bidirectional associative memory inertial neural networks, where the Markov chain is introduced to describe the switching characteristic in the structure and parameters. Moreover, considering the limited network bandwidth, the weighted try-once-discard protocol, as a significant scheduling mechanism in determining which nodes can be accessed between the sensor nodes and the filter, is employed to avoid the data collisions under the constrained communication channel. The objective of the paper is to develop a filter that can ensure that the filtering error system is stochastically stable with extended dissipative performance. Based on the Lyapunov function and an improved decoupling approach, a set of sufficient conditions satisfying the above objective are derived, and the filter gains are obtained. Finally, an illustrative example is employed to verify the validity of the proposed method.     

Cooperative control with designated convergence rate for high-order integrators under heterogeneous couplings

In this paper, we investigate the cooperative control problem of high-order integrators under heterogeneous couplings. A new class of distributed control algorithms are developed for the designated convergence rate (DCR) problem of high-order integrators, which could explicitly show the convergence margin of the closed-loop system, and has better robustness than conventional consensus algorithms. We first propose state consensus control algorithms for high-order integrators, where necessary and sufficient convergence conditions are proposed by theoretical analysis. Then we extend the results to the case of output leaderless consensus of heterogeneous high-order integrators with heterogeneous couplings. Finally, simulation examples are given to validate the effectiveness of the proposed algorithms.     

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.