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• In this paper, the finite horizon linear quadratic tracking problem transforms to the finite-horizon linear quadratic regulator problem with the help of the augmented system. • The developed algorithm in this paper solves the time-varying Riccati equations offline and backward-in-time without the system dynamics or any model identification schemes through the defined time-varying Q-function. • Compare with the work in [56], the restrictions on initial state of the developed algorithm in this paper are not required. Besides, optimal tracking control can be achieved in this paper. • Compare with the work in [57], the discrete-time system is studied in this paper. While, continuous-time system is considered in [57]. Besides, there is no restriction on the initial value function of the developed algorithm in this paper, while the initial value function of the developed algorithm in [57] needs to meet certain conditions. Conventionally, the finite-horizon linear quadratic tracking (FHLQT) problem relies on solving the time-varying Riccati equations and the time-varying non-causal difference equations as the system dynamics is known. In this paper, with unknown system dynamics being considered, a Q -function-based model-free method is developed to solve the FHLQT problem. First, an augmented system consisting of the controlled system and the desired trajectory system is formulated, and the FHLQT problem transforms to the finite-horizon linear quadratic regulator (FHLQR) problem with the augmented system. Then, a time-varying Q -function which depends explicitly on the control input is defined. With the defined time-varying Q -function, a model-free finite-horizon control method is developed to approximate the solutions of the time-varying Riccati equations of the transformed FHLQR problem. At last, simulation studies are carried out to verify the validity of the developed method. [ABSTRACT FROM AUTHOR]

• The event-triggered distributed FTC problem of uncertain nonlinear interconnected systems subjected to unmatched interconnections and time-varying actuator faults is solved by integrating the ADP approach and the dynamic event-triggered control strategy for the first time. • A new cost function is introduced to handle the unmatched interconnections and actuator faults simultaneously. • A new dynamic event-triggered mechanism is established, which has the advantage of enlarging sampling interval. Moreover, the restriction on initial admissible control policy for each auxiliary subsystem is obviated by introducing a robust term into the weight learning law of critic NN. • Theoretical analysis shows that the adverse effects of actuator faults on the stability can be eliminated and the cost function of overall interconnected system can be guaranteed to have an upper bound. A novel dynamic event-triggered distributed fault tolerant control (FTC) scheme with guaranteed cost is proposed for uncertain nonlinear interconnected systems suffering from time-varying actuator faults. The event-triggered FTC problem of uncertain interconnected system is first converted to a series of equivalent event-triggered optimal control designs of isolated fault-free auxiliary subsystems by defining a modified cost function for each auxiliary subsystem. The equivalence of problem transformation is demonstrated meanwhile the upper bound of cost function of overall interconnected system is analyzed. Subsequently, for the isolated auxiliary subsystem, a dynamic event-triggered adaptive dynamic programming (DET-ADP) algorithm is proposed to obtain the optimal control policy, which can remove the restriction of initial admissible control, eliminate the actor network, and save more communication resources. Furthermore, we prove that the closed-loop auxiliary subsystems are ensured to be uniform ultimate bounded based on Lyapunov approach. Finally, simulation results are presented to validate the developed dynamic event-triggered distributed guaranteed cost FTC scheme. [ABSTRACT FROM AUTHOR]

• The adaptability against uplink data loss for nonlinear plant is enhanced evidently. • An additional constraint is for the first time proposed for updating the plant status instantly. • A worse health quality of uplink channels can be affordable in this study. The problem of promoting the adaptability to uplink data loss for nonlinear plant is addressed via developing the fuzzy gain-scheduling stabilization law based on a novel online evaluation mechanism. Different from those previous methods, the proposed online evaluation mechanism is dependent not only the current-time but also the past-time normalized fuzzy weighting functions, and thus much more information can be absorbed and utilized in the process of stabilization synthesis by introducing extra free matrices than before. More importantly, an additional constraint is for the first time proposed for updating the plant status instantly so that critical replacement operations can be implemented for reducing the conservativeness of the designing conditions. Therefore, the adaptability to uplink data loss is improved evidently and thus the worse communication quality of uplink channel is bearable in this study. Finally, the advantages relative to those reported ones are tested and validated through benchmark numerical comparisons. [ABSTRACT FROM AUTHOR]

• Few people consider the data-driven parameter adaptive control in the tracking control of AUV. Based on the traditional sliding mode control, a novel adaptive tracking control considering the external environment interference and uncertainty is designed using a data-based online ADHDP method. • The Lyapunov function of ADHDP algorithm considering experience replay is designed to obtain the stability results and ensure the convergence of data-driven neural network weights. • The weighted experience replay method is considered, and the historical data is weighted with a novel parameter λ and is used for the control strategy online real-time update. At present, there are few simultaneous studies. A novel adaptive trajectory tracking control method is proposed in this paper for autonomous underwater vehicle systems with external disturbances. The control action is composed of sliding mode control and action-depended heuristic dynamic programming (ADHDP) controller to track the expected sailing position and angle in the horizontal coordinate system with fixed depth. As an auxiliary control of sliding mode control, the ADHDP controller observes the difference between the actual sailing position/angle and the expected sailing position/angle, and adaptively provides corresponding supplementary control actions using a data-driven fashion. At the same time, we design a weight-related priority experience replay (PER) technology to update the online weight network by using the relevant historical data stored in the database to improve the learning rate. The proposed algorithm can adjust parameters online under various conditions. Furthermore, it is very suitable for underwater vehicle systems with parameter uncertainties and external disturbances. Based on Lyapunov stability method, the stability of closed-loop system state and network weight error is analyzed. Finally, the validity of our control strategy is verified by simulation. [ABSTRACT FROM AUTHOR]

• Power regulation cost of controllable unit is modeled to arrange adjustment order. • SoC is considered to reduce the number of switching times of MMG working mode. • Consistency algorithm based on the load rate accelerates convergence speed of SoC. • Power allocation based on consensus algorithm reduces MMG power regulation cost. The direct current(DC) multi-microgrid(MMG) with island operation mode is a system formed by interconnecting DC multiple microgrids, which is more complicated than a single microgrid. First of all, this paper proposes the modeling method of the power regulation cost for each controllable unit to guide their power regulation order, which reduces the power regulation cost. Second, the hierarchical control strategy is proposed. The top-level control allocates power through the consensus algorithm to accelerate the convergence rate of the state of charge(SoC) of energy storage batteries(ESBs). The convergence of SoC reduces the switching times of working mode of MMG system caused by the deviation of SoC from the normal working range, which further reduces the cost of power regulation. The bottom-level control performs constant power control on each controllable unit according to the load rate of ESB obtained by top-level control. Furthermore, the correction scheme of measured SoC value is proposed according to its predicted value when the measured SoC value of ESB is inaccurate, which ensures the stability of MMG system. Finally, the example simulation shows that the consensus algorithm can effectively solve the real-time power distribution problem of MMG. [ABSTRACT FROM AUTHOR]

• A prescribed tracking accuracy containment control scheme for non-affine nonlinear uncertain multi-agent systems is proposed in this paper. In the existing results, the presented strategy just ensure that the containment errors gather to a small neighborhood around the origin. In this note, each containment error can converge to a assigned precision value by the proposed method, and the magnitude of each error can be confirmed precisely before the containment controller is designed. • Two important auxiliary functions are used to help deal with the precision tracking issue. With the aid of these two n-order differentiable functions, the Lyapunov functions can be created. And in combination with adaptive and the backstepping techniques, the technical difficulties of the desire controller design are overcome for non-affine nonlinear uncertain multi-agent systems. • A novel analysis method of containment errors is proposed in this note. By using this method, we can conclude that the convergence error for each agent is a given constant. This paper concentrates on a containment control issue for multi-agent systems in non-affine form with a given accuracy. In comparison with the existing studies on multi-agent systems, precision-based containment control idea is first formulated. With the aid of the proposed strategy, the main merit of this note is that the synchronization errors converge to arbitrary given positive number. Simultaneously, the particular Layapunov functions are constructed by feat of two auxiliary functions. By employing the backstepping and adaptive control technique, the key variables and the actual controller are designed. Unlike the traditional stability analysis, a novel method is used to analyse the convergence of containment errors. In the end, some simulation results demonstrate the correctness for the proposed protocol. [ABSTRACT FROM AUTHOR]

• A fast finite-time criterion for deterministic systems is established. • We establish a fast finite-time control criterion for stochastic systems by revamping the fast finite time method. • The control strategy can effectively improve the control speed compared to the existing results in this paper. This paper elucidates the finite-time stability in probability problem for a class of p-norm stochastic nonlinear systems. Among them, from the point of view of convergence speed, finite-time control does have optimal properties. Consequently, a fast finite-time criterion for deterministic systems is established. However, although there exist a significant amount of results on fast finite time stability, there is no article involves p-norm stochastic nonlinear systems case available so far. There are random disturbance terms that made the traditional fast finite-time control methods inapplicable. To overcome this problem, we establish a fast finite-time control criterion for stochastic systems by revamping the fast finite time method of deterministic systems. Then, with the aid of sign function and adding a power integrator technology, a non-Lipschitz continuous state feedback controller is established successfully. Next, the control strategy can effectively improve the control speed compared to the existing results in this paper. Finally, numerical and dynamic suspension simulations are offered to augment our theoretical analysis results, and comparison plots with conventional control strategies are shown. [ABSTRACT FROM AUTHOR]

• Compared with the classical Janbu method, the addition of an adaptive dynamic programming algorithm has the following advantages. • In the limit equilibrium analysis of each slice, the individual safety factor is directly added to solve the critical instability trajectory iteratively. Instead of first solving the fractional average and safety factor of the sliding surface, judging the rationality, and then searching for the critical sliding surface, the computational task is vast. • When dealing with a complex engineering background, the reconstructed framework is based on a neural network to complete an iterative solution. The fuzzy relationship of safety factors between adjacent strips can be simplified and integrated into the model network. The interactive iterative update of the action and critic networks can complete the boundary curve corresponding to the limit sliding state. At the same time, in order to further simplify the calculation, the critic network uses a dual network design. Notwithstanding the rich research on the slicing method, it is still impossible to accomplish the limit equilibrium analysis of all phases before the evaluation of the safety factor. Bearing this dilemma in view, in this paper, the Janbu method is optimized and reformulated by introducing adaptive dynamic programming (ADP). The fractional average safety factor is no longer used; instead, a sequence of safety factors is used. The critical slip state is chosen as the equilibrium point, the nonlinearity of safety coefficients of adjacent blocks is approximated by the neural network, and the remaining variables and constraints of the system are added to assist in transforming the original redundant safety coefficient evaluation-finding optimal solution problem into a Janbu-qualified cost function. The action network and critic network of ADP accomplish the boundary trajectory solving and safety evaluation, respectively. The validity of the method is verified when the optimized and reorganized framework is applied to solve the critical slip surface of a clay slope. [ABSTRACT FROM AUTHOR]

This paper proposes an enhanced chaos synchronization control scheme of stochastic nonlinear systems for the permanent magnet synchronous motors(PMSMs) applications for dynamic operating mechanism under different working environment. Firstly, a novel fixed-time stochastic stability theorem and convergence for the stochastic nonlinear system is valid through formulating a novel Lyapunov function. Different from what has been achieved on the fixed-time stability, it's not the usual range but it's more precise for settling time which improving control performance effectually. Secondly, the chaos synchronization issue of driven-response PMSMs with stochastic noise is firstly investigated based on the proposed Lyapunov theorem synchronizing the complex dynamic systems considering practical significance. Finally, the fixed-time synchronization control scheme is developed via applying the adaptive algorithms, furthermore, through constructing a reasonable synchronization dynamic error system achieving stability in probability of fixed time. A simulation analysis is demonstrated to verify the availability of the proposed control strategy. [ABSTRACT FROM AUTHOR]

• There are few attempts to research semi-Markovian jump systems subject to generally uncertain TRs, Wiener process, state delays as well as input constraint at present. • For the semi-Markovian jump systems subject to generally uncertain TRs as well as Wiener process, the dynamic output feedback controller is proposed, which is studied rarely at present, and the state values are no longer required. • For the semi-Markovian jump systems subject to generally uncertain TRs as well as Wiener process, the FTB issue is little studied. This paper concentrates on robust finite-time H ∞ control for uncertain Itô stochastic semi-Markovian jump systems with generally uncertain transition rates, multiple state delays and input constraint. There are few attempts for Itô stochastic semi-Markovian jump systems with generally uncertain transition rates. In contrast to the existing results, the system explored in this paper is more general and has more potential applications. By means of the partial transition rate information, a semi-Markovian jump controller is developed to realize fault-tolerant control. Then, a closed-loop system can be gathered. Moreover, a cluster of stability conditions are attained via stochastic Lyapunov function with the way of linear matrix inequalities. Finally, two examples are presented to illustrate this effectiveness of the approach depicted in the work. [ABSTRACT FROM AUTHOR]

• A unified dynamic driven and observer-based security LFC framework is established for power systems in which the time delays and actuator saturation are considered simultaneously. While, in many existing studies [24,35], only partly conditions were considered. Different from [25,36], the actuator saturation is also considered in this paper. • A novel DETM is proposed by introducing the internal variable η (t) (t) and additional exponential term to reduce the pressure of data transmission. Compared with [17,23,41], we introduce an additional exponential term to further improve the communication bandwidth utilization.Moreover, the Zeno behavior is avoided naturally. • The observer-based resilient control strategy and stochastic Lyapunov stability theory are developed such that the LFC systems are mean-square exponential stable. Finally, the simulations are given to prove the usefulness of the proposed method. This paper focuses on the observer-based H ∞ load frequency control (LFC) of multi-area power systems with actuator saturation and deception attack. Firstly, a state observer is constructed to estimate the unmeasurable states and a time-delay model with the area control error is established. Secondly, a dynamic event triggering mechanism is developed, where dynamic parameter and a novel error-related exponential term are introduced to reduce the communication burden further in the network. Thirdly, considering time delays, data-packet losses and stochastic deception attack, a resilient LFC controller of power systems based on actuator saturation is designed and the security of the system is guaranteed with the condition of H ∞ mean-square exponential stability. Sufficient conditions to co-design the event-triggered scheme, observer and desired controller gain are derived by Lyapunov functional analysis approach. Finally, simulation example is given to demonstrate the efficiency of the developed method. [ABSTRACT FROM AUTHOR]

• A networked system model is constructed with the consideration of the network delay and deception attacks. • Sufficient conditions are provided to guarantee the H ∞ stability of FDF by using Lyapunov stability theory and LMI techniques. • The coefficient matrices of the FDF are also presented in explicit expressions calculated by a set of LMIs. • Two simulation examples are presented to show the effectiveness and practicability of the proposed method. This paper focuses on the fault detection for networked systems with deception attacks. Firstly, a fault detection filter (FDF) is presented as a residual generator to detect the random occurring fault signal timely in networked systems with the consideration of network delay and deception attacks. Then, by using the Lyapunov stability theory and linear matrix inequality (LMI) techniques, sufficient conditions are presented to guarantee the stability with an H ∞ performance index γ of our proposed fault detection system. Furthermore, the corresponding coefficient matrices of the FDF are also presented with the explicit expressions. Finally, two simulation examples demonstrate the effectiveness and practicability of the designed FDF. [ABSTRACT FROM AUTHOR]

• A novel finite-time DFEO is designed to estimate more general faults in all subsystems of CPSs based on the distributed functional observer with an adaptive compensator. Not only the order and complexity of observer are reduced, but also the unknown parameters of matched uncertainties are adaptively learned to improve the convergence and precision of observer. Both the transient performance in finite time and H ∞ disturbance attenuate performance of CPSs are achieved. • A DFTCr based on the integral SMC is designed to compensate the effect of faults on the interconnected CPSs, in which the sliding surface function does not include the system parameters, which makes the design more flexible. Moreover, compared with the existing research [23, 28], the controller in this paper does not need to give the limited assumption of pseudo inverse. • The FTB-H ∞ performance with nonzero initial conditions of CPSs is ensured by employing a new Lyapunov functional approach. Compared with the matched nonlinear function with known upper bounded conditions in [29], and measurable states [32], our works are more general and practical. This paper is concerned with finite-time distributed fault estimation (DFE) and fault-tolerant control (DFTC) for cyber-physical systems (CPSs) with actuator faults and matched uncertainties. First, in order to deal with the partly unmeasurable states, matched uncertainties and actuator faults with the loss of effectiveness and bias, a distributed fault estimation observer (DFEO) is designed based on the functional observer with an adaptive compensator. Then, a distributed fault-tolerant controller (DFTCr) is designed to compensate faults effect on the interconnected CPSs based on the integral sliding mode control (SMC) technique, which ensures that the closed-loop systems reach a given boundedness in a predefined finite time. Moreover, some sufficient conditions in the form of linear matrix inequalities are proposed to guarantee the finite-time boundedness with H ∞ performance (FTB- H ∞). Due to introducing more degrees of freedom of the functional observer, the designed finite-time distributed fault-tolerant controller is more flexible and less conservative. Finally, a numerical simulation on the three-machine power systems is acquired to show the validity of the proposed method. [ABSTRACT FROM AUTHOR]

• An efficient data-driven algorithm is proposed to identify the system dynamics. • The internal model of the exosystem is embedded in the adaptive fault-tolerant law for the first time. • The obtained stability criterion is less conservative than before. In this paper, the adaptive fault-tolerant output regulation for the system with unknown dynamics is considered. Firstly, a data-driven algorithm is proposed to identify the system dynamics by solving the Riccati equation. Due to unneeded to solve the optimal controller, the iterative process of the algorithm is reduced. Based on the identified model, an adaptive controller is designed to compensate for the actuator faults which include both outage and loss-of-effectiveness faults. Moreover, the internal model of the exosystem is embedded in the adaptive fault-tolerant controller which can stabilize the system whether the actuator faults hold or not. Finally, the numerical simulation result shows the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]