Showing papers in "Iet Control Theory and Applications in 2016"
TL;DR: This study is concerned with the event-based security control problem for a class of discrete-time stochastic systems with multiplicative noises subject to both randomly occurring denial-of-service attacks and randomly occurring deception attacks.
Abstract: This study is concerned with the event-based security control problem for a class of discrete-time stochastic systems with multiplicative noises subject to both randomly occurring denial-of-service (DoS) attacks and randomly occurring deception attacks. An event-triggered mechanism is adopted with hope to reduce the communication burden, where the measurement signal is transmitted only when a certain triggering condition is violated. A novel attack model is proposed to reflect the randomly occurring behaviours of the DoS attacks as well as the deception attacks within a unified framework via two sets of Bernoulli distributed white sequences with known conditional probabilities. A new concept of mean-square security domain is put forward to quantify the security degree. The authors aim to design an output feedback controller such that the closed-loop system achieves the desired security. By using the stochastic analysis techniques, some sufficient conditions are established to guarantee the desired security requirement and the control gain is obtained by solving some linear matrix inequalities with non-linear constraints. A simulation example is utilised to illustrate the usefulness of the proposed controller design scheme.
178 citations
TL;DR: In this article, a sufficient criterion is provided for interconnected impulsive switched systems to cope with the problem of finite-time stability by resorting to the average dwell time approach, and a decentralised switched control scheme based on state-feedback controller and a class of switching signals are constructed to ensure stabilisability of the system.
Abstract: In this study, the finite-time stability problem is addressed concerning interconnected impulsive switched systems. By resorting to the average dwell time approach, a sufficient criterion is provided for interconnected impulsive switched systems to cope with the problem of finite-time stability. Then, the decentralised switched control scheme based on state-feedback controller and a class of switching signals are constructed to ensure stabilisability of the system. Finally, an application example is presented to demonstrate the effectiveness of the main results.
138 citations
TL;DR: In this paper, a generalised projection identification algorithm (or a finite data window stochastic gradient identification algorithm) for time-varying systems is presented and its convergence is analyzed by using the Stochastic Process Theory.
Abstract: The least mean square methods include two typical parameter estimation algorithms, which are the projection algorithm and the stochastic gradient algorithm, the former is sensitive to noise and the latter is not capable of tracking the time-varying parameters. On the basis of these two typical algorithms, this study presents a generalised projection identification algorithm (or a finite data window stochastic gradient identification algorithm) for time-varying systems and studies its convergence by using the stochastic process theory. The analysis indicates that the generalised projection algorithm can track the time-varying parameters and requires less computational effort compared with the forgetting factor recursive least squares algorithm. The way of choosing the data window length is stated so that the minimum parameter estimation error upper bound can be obtained. The numerical examples are provided.
120 citations
TL;DR: This study investigates the problem of unexpected cyber attack and its automatic recovery by exploring detectability of attacks based on linear system theory and the effectiveness of the proposed adaptive schemes.
Abstract: Timely and automatic detection and reconstruction of cyber attack is crucial in maintaining safe operation of cyber-physical systems. This study investigates the problem of unexpected cyber attack and its automatic recovery. First, detectability of attacks based on linear system theory is explored and some sufficient conditions of detecting state attacks and sensor attacks, respectively, are established. Subsequently two adaptive sliding mode observers with on line parameter estimation are designed to estimate state attacks and sensor attacks separately. Second, appropriate residual signals are constructed and it is shown that they approach to the attacks with ultimately uniformly bounded errors. Finally, as an illustration of attack detection and reconstruction, the results are applied to an IEEE 39 bus power system with 10 generators and 39 buses, which shows the effectiveness of the proposed adaptive schemes.
115 citations
TL;DR: In this article, an adaptive fractional-order terminal sliding mode controller is proposed for controlling robot manipulators with uncertainties and external disturbances, which is used to deal with uncertainties which upper bounds are unknown in practical cases.
Abstract: In this study, an adaptive fractional-order terminal sliding mode controller is proposed for controlling robot manipulators with uncertainties and external disturbances. An adaptive tuning method is utilised to deal with uncertainties which upper bounds are unknown in practical cases. Fast convergence is achieved using non-singular fast terminal sliding mode control. Also, fractional-order controller is used to improve tracking performance of controller. After proposing a new stable fractional-order non-singular and non-linear switching manifold, a sliding mode control law is designed. The stability of the closed-loop system is proved by Lyapunov stability theorem. Simulation results demonstrate the effectiveness and high-precision tracking performance of this controller in comparison with integer-order terminal sliding mode controllers.
112 citations
TL;DR: In this paper, an adaptive boundary control is presented for vibration suppression of an axially moving belt system, including the dynamics of high acceleration/deceleration and distributed disturbance by utilising the extended Hamilton's principle.
Abstract: In this study, an adaptive boundary control is presented for vibration suppression of an axially moving belt system. First, the infinite-dimensional model of the belt system including the dynamics of high acceleration/deceleration and distributed disturbance is derived by utilising the extended Hamilton's principle. Subsequently, by using Lyapunov's synthesis method and an adaptive technique, an adaptive boundary control is developed to suppress the belt's vibration and compensate for the system parametric uncertainties. With the proposed control, the stability of the closed-loop system and the uniform boundedness of all closed-loop signals are both ensured. Besides, the S-curve acceleration/deceleration method is adopted to plan the belt's axial speed and the disturbance observer is used to mitigate the effects of unknown boundary disturbance. Finally, the control performance of the closed-loop system is successfully demonstrated through simulations.
103 citations
TL;DR: In this article, an adaptive neural network (NN) state feedback control and robust observation for an active suspension system that considers parametric uncertainties, road disturbances and actuator saturation is investigated.
Abstract: This study investigates adaptive neural network (NN) state feedback control and robust observation for an active suspension system that considers parametric uncertainties, road disturbances and actuator saturation. An adaptive radial basis function neural network is adopted to approximate uncertain non-linear functions in the dynamic system. An auxiliary system is designed and presented to deal with the effects of actuator saturation. In addition, since it is difficult to obtain accurate states in practice, an NN observer is developed to provide state estimation using the measured input and output data of the system. The state observer-based feedback control parameters with saturated inputs are optimised by the particle swarm optimisation scheme. Furthermore, the uniformly ultimately boundedness of all the closed-loop signals is guaranteed through rigorous Lyapunov analysis. The simulation results further demonstrate that the proposed controller can effectively suppress car body vibrations and offers superior control performance despite the existence of non-linear dynamics and control input constraints.
101 citations
TL;DR: In this article, a distributed consensus tracking problem for non-linear multi-agent systems under a fixed directed graph is considered and the dynamics of the followers are taken as strict feedback structures with unknown nonlinearities and input saturation.
Abstract: This study deals with the distributed consensus tracking problem for non-linear multi-agent systems under a fixed directed graph. The dynamics of the followers are taken as strict-feedback structures with unknown non-linearities and input saturation. Neural networks are utilised to identify a certain scalar related to the unknown non-linear functions, and an auxiliary system is introduced into the control design to compensate the effect of input saturation. By incorporating the command filtered technique into the backstepping design framework, a distributed consensus control scheme is constructed recursively. Using the Lyapunov stability theory, it is proved that all signals in the closed-loop systems are cooperatively semi-globally uniformly ultimately bounded and the consensus tracking errors converge to a small neighbourhood of origin by tuning the design parameters. Finally, simulation result demonstrates the effectiveness of the proposed control approach.
96 citations
TL;DR: The authors present a hierarchical gradient-based iterative (HGI) algorithm by using the hierarchical identification principle to solve the difficulty that the identification model contains the unmeasurable variables and noise terms in the information matrix.
Abstract: This study applies the filtering technique to system identification to study the data filtering-based parameter estimation methods for multivariable systems, which are corrupted by correlated noise – an autoregressive moving average process. To solve the difficulty that the identification model contains the unmeasurable variables and noise terms in the information matrix, the authors present a hierarchical gradient-based iterative (HGI) algorithm by using the hierarchical identification principle. To improve the convergence rate, they apply the filtering technique to derive a filtering-based HGI algorithm and a filtering-based hierarchical least squares-based iterative (HLSI) algorithm. The simulation examples indicate that the filtering-based HLSI algorithm has the highest computational efficiency among these three algorithms.
90 citations
TL;DR: In this article, a physically motivated Lyapunov function is employed to design boundary control law to ensure the vibration suppression and guarantee the stability of the closed-loop system with input backlash.
Abstract: In this study, the authors are concerned with the active vibration control of a flexible string system with input backlash. For vibration suppression, active control is applied at the right boundary of the flexible string. To deal with the input backlash, a novel ‘disturbance-like’ term is proposed in the control design. A physically motivated Lyapunov function is employed to design boundary control law to ensure the vibration suppression and guarantee the stability of the closed-loop system. Numerical simulations illustrate the effectiveness of the proposed control method.
88 citations
TL;DR: In this paper, an active disturbance rejection and predictive control strategy is presented to solve the trajectory tracking problem for an unmanned quadrotor helicopter with disturbances, where effects of wind gusts are considered as additive disturbances on six degrees of freedom.
Abstract: In this study, an active disturbance rejection and predictive control strategy is presented to solve the trajectory tracking problem for an unmanned quadrotor helicopter with disturbances. The proposed control scheme is based on the quadrotor's dynamic model, where effects of wind gust are considered as additive disturbances on six degrees of freedom. The predictive controller solves the path following problem with extended state observers to estimate and compensate disturbances. The active disturbance rejection control scheme is used for the stabilisation of rotational movements. The suggested control structure is verified in simulation studies with the presence of external disturbances and parametric uncertainties. The proposed method improves the robustness for the modelling error and disturbances while performing a smooth tracking of the reference trajectory.
TL;DR: To reduce the amount of data transfer in sensor networks, the authors propose a KCF with an event-triggered communication protocol and using the Lyapunov-based approach a sufficient condition is presented for ensuring the stochastic stability of the suboptimal KCF.
Abstract: Kalman consensus filter (KCF) has been developed for distributed state estimation over sensor networks where local estimates are exchanged with time-triggered transmission mechanism. To reduce the amount of data transfer in sensor networks, the authors propose a KCF with an event-triggered communication protocol. The triggering decision is based on the send-on-delta data transmission mechanism: each sensor transmits its local estimates to its neighbours only if the difference between the most recent transmitted estimate and the current estimate exceeds a tolerable threshold. On the basis of the event-triggered communication protocol, an optimal Kalman gain matrix is derived by minimising the mean squared errors for each sensor and a suboptimal KCF is developed for scalable considerations. By using the Lyapunov-based approach, a sufficient condition is presented for ensuring the stochastic stability of the suboptimal KCF. A numerical example is provided to verify the effectiveness of the proposed filter.
TL;DR: In this paper, the stabilisation problem of switched positive systems with actuator saturation was studied and sufficient conditions for stabilisation of the system were proposed under the state feedback controllers under multiple linear co-positive Lyapunov functions.
Abstract: This study focuses on the stabilisation problem of switched positive systems with actuator saturation. Through multiple linear co-positive Lyapunov functions, the two cases of time-dependent switching and state-dependent switching are investigated for the first time. Sufficient conditions for stabilisation of the system are proposed under the state feedback controllers. In addition, the convex hull technique is employed to deal with actuator saturation. Finally, an application of the obtained results to the control of aero engines is proposed to demonstrate the validity.
TL;DR: In this paper, an interval observer is designed to estimate the states of non-linear switched systems with the average dwell time scheme, and sufficient conditions for state estimation are presented in terms of an LMI formulation.
Abstract: The authors address control system design based on an interval observer for non-linear switched systems with non-linear vector functions that are assumed to satisfy Lipschitz conditions. First, the observer gain satisfying a Metzler matrix can be solved by optimisations of linear matrix inequalities (LMIs). Second, an interval observer is designed to estimate the states of non-linear switched systems with the average dwell time scheme, and sufficient conditions for state estimation are presented in terms of an LMI formulation. Third, based on an interval observer, state feedback matrices are designed to construct an asymptotically stabilising switching controller. Finally, a numerical example is provided to demonstrate the efficiency of the approach.
TL;DR: The authors propose the distributed dynamic adaptive state feedback and adaptive output feedback protocols for driving followers into the moving convex hull spanned by leaders, which are independent of any global information, and hence are fully distributed.
Abstract: Output regulation is a general framework, for it not only can achieve closed-loop stability, but also can realise asymptotic tracking and disturbance rejection. Within this framework, the authors consider the containment problem of heterogeneous linear multi-agent systems with directed graphs. Via dynamic compensator techniques, the containment problem can be converted into cooperative output regulation problem. Moreover, they artfully construct regulation equations, whose solutions are also given. Adaptive protocols are proposed here by assigning a time-varying coupling weight to each node. Unlike most existing protocols that depend on certain global information, protocols presented in this paper are independent of any global information, and hence are fully distributed. By combining the compensator technique with adaptive control, they propose the distributed dynamic adaptive state feedback and adaptive output feedback protocols for driving followers into the moving convex hull spanned by leaders. The obtained results are applied to the containment control of a network of heterogeneous agents, where the followers are described by mass-damper spring systems, and the leaders are specified by harmonic oscillators.
TL;DR: In this article, a novel time-optimal off-line trajectory planning method, together with a tracking controller, is proposed for a two-dimensional (2D) underactuated overhead crane, whose trajectory is parameterized to be a B-spline curve with unknown parameters when considering the continuity and smoothness requirements.
Abstract: In this study, a novel time-optimal off-line trajectory planning method, together with a tracking controller, is proposed for a two-dimensional (2D) underactuated overhead crane. Specifically, based on the differential flatness technique, a flat output of the system is firstly defined to deal with the coupling between the payload swing and trolley motion, whose trajectory is parameterised to be a B-spline curve with unknown parameters when considering the continuity and smoothness requirements. Various constraints, including swing bound, allowable trolley acceleration, and so on, are then taken into consideration to convert the parameters determination task into an optimisation problem, with the solution employed to construct a high-efficient trolley trajectory with an analytical expression. To enhance tracking performance, a non-linear tracking control law is subsequently designed based on the feedback linearisation technique, whose performance is ensured with theoretical analysis. Finally, some simulation and experimental results are included to demonstrate that the proposed trajectory planning/tracking scheme achieves satisfactory performance for underactuated cranes.
TL;DR: A model-free adaptive optimal tracking algorithm based on the framework of reinforcement learning and adaptive dynamic programming is proposed in this study which learns the optimal solution online in real time without any information of the system dynamics.
Abstract: The optimal tracking of non-linear systems without knowing system dynamics is an important and intractable problem. Based on the framework of reinforcement learning (RL) and adaptive dynamic programming, a model-free adaptive optimal tracking algorithm is proposed in this study. After constructing an augmented system with the tracking errors and the reference states, the tracking problem is converted to a regulation problem with respect to the new system. Several RL techniques are synthesised to form a novel algorithm which learns the optimal solution online in real time without any information of the system dynamics. Continuous adaptation laws are defined by the current observations and the past experience. The convergence is guaranteed by Lyapunov analysis. Two simulations on a linear and a non-linear systems demonstrate the performance of the proposed approach.
TL;DR: In this article, a finite-time convergent distributed continuous-time algorithm is proposed to solve a network optimisation problem where the global cost function is the sum of strictly convex local cost functions under an undirected network with fixed topologies.
Abstract: In this study, a finite-time convergent distributed continuous-time algorithm is proposed to solve a network optimisation problem where the global cost function is the sum of strictly convex local cost functions under an undirected network with fixed topologies. The algorithm is inspired by finite-time consensus protocols and continuous-time zero-gradient-sum algorithms. Instead of the exponential convergence in existing works, the finite-time convergence is guaranteed based on the Lyapunov method. A numerical simulation example is provided to illustrate the effectiveness of the developed algorithm.
TL;DR: In this article, the authors considered the fault-tolerant containment control problem for linear multi-agent systems with external disturbances, non-identical matching non-linear functions and actuator faults containing stuck, outage and loss of effectiveness.
Abstract: This study considers the fault-tolerant containment control problem for linear multi-agent systems with external disturbances, non-identical matching non-linear functions and actuator faults containing stuck, outage and loss of effectiveness. A novel method is proposed to estimate the norm of weight vector in fuzzy logic systems rather than the weight vector by using the traditional method. So the difficulty that the actuator with outage or stuck fault cannot work to compensate the unknown non-linear function is solved. Furthermore, different from the traditional fault-tolerant control method to estimate the feedback gain matrix related on the fault, only the ratio of coupling weight to the failure rate is estimated. The merit of the proposed controller is that the number of adaptive parameters is only related to the number of agents, which reduces the adaptive parameters and computational burden considerably. In addition, it is proved that the proposed controller guarantees all the signals in the closed-loop systems are bounded and all followers converge asymptotically to the convex hull formed by the leaders. Finally, a simulation example is given to illustrate the effectiveness of the proposed control scheme.
TL;DR: In this paper, a finite-time convergence control strategy based on adaptive non-singular fast terminal sliding mode is proposed for spacecraft attitude tracking subject to actuator faults, actuator saturations, external disturbances and inertia uncertainties.
Abstract: Finite-time convergence control strategies based on adaptive non-singular fast terminal sliding mode are proposed for spacecraft attitude tracking subject to actuator faults, actuator saturations, external disturbances and inertia uncertainties. The designed non-singular fast terminal sliding mode control law can converge in a finite time and avoid singularity, hence it can be used to develop a finite-time fault-tolerant attitude tracking controller that meets multiple constraints. It is demonstrated that the controller is independent of inertia uncertainties and external disturbances with adaptive parameters. The controller designed considers the actuator output torque saturation amplitude requirements and makes the spacecraft accomplish certain operations within the saturation magnitude and without the need for on-line fault estimate. The Lyapunov stability analysis shows that the controller can guarantee the fast convergence of a closed-loop system and has a good fault-tolerant performance on actuator faults and saturations under the multiple constraints on actuator faults, actuator saturations, external disturbances and inertia uncertainties. Numerical simulation verified the good performance of the controller in the attitude tracking control.
TL;DR: In this paper, the problem of distributed output feedback consensus tracking control for leader-following non-linear multi-agent systems in strict feedback form under a directed graph topology with prescribed performance requirement is studied.
Abstract: This paper studies the problem of distributed output feedback consensus tracking control for leader–following non-linear multi-agent systems in strict-feedback form under a directed graph topology with prescribed performance requirement. The unknown external disturbances are considered in the followers. First, the authors design reduced-order observers to estimate the unmeasured state variables of the followers online. Then, the novel controllers are designed with prescribed performance control based on backstepping method. The dynamic surface control technique is used to deal with the calculating explosion problem. It is strictly proved that the resulting whole system is stable in the sense of semi-globally uniformly ultimately boundedness and both transient and steady-state performance of consensus tracking errors are preserved based on Lyapunov stability theory. Finally, a simulation example is presented to verify the effectiveness of the proposed techniques.
TL;DR: In this paper, the adaptive finite-time tracking problem for uncertain non-linear n-order systems subjected to unmatched uncertainties is studied and a robust controller is obtained to drive the tracking error to origin in finite time in spite of the unmatched uncertainties.
Abstract: This study focuses on the adaptive finite-time tracking problem for uncertain non-linear n-order systems subjected to unmatched uncertainties. Using a novel form of fast terminal sliding mode (FTSM) control method with self-tuning algorithm, a robust controller is obtained to drive the tracking error to origin in finite time in spite of the unmatched uncertainties. Indeed, the adaptive FTSM is combined with a global SMC approach to eliminate the reaching phase which improves the performance and robustness of the system. To alleviate chattering phenomenon and get rid of knowing the exact value of upper bound of the uncertainties, a bipolar sigmoid function with adjustable gains is presented to replace signum function. The Lyapunov stability theory is utilised to establish the stability and robustness features of the suggested law. The proposed controller provides an appropriate performance as well as finite-time convergence of tracking error to zero and this issue is verified through simulation results.
TL;DR: In this paper, a distributed adaptive control scheme is developed to compensate the effect of fault, multiple delayed state perturbations, mismatched parameter uncertainties and external disturbances on leader-follower multi-agent systems.
Abstract: This study considers the distributed fault-tolerant consensus problem for uncertain multi-agent systems using adaptive protocol. A more general time-varying actuator fault model is given, which includes loss of effectiveness, stuck, bias and outage fault. A new distributed adaptive control scheme is developed to compensate the effect of fault, multiple delayed state perturbations, mismatched parameter uncertainties and external disturbances on leader-follower multiagent systems. Based on the local state information of neighbouring agents, the adaptive updating protocol gains are adjusted online, which remove the assumption that the upper bounds of unknown uncertainty, delayed state perturbation and external disturbances should be known. Moreover, the consensus errors of leader-follower systems can asymptotically converge to zero. Finally, a simulation example is given to show the effectiveness of the theoretical analysis. c The Institution of Engineering and Technology 2016.
TL;DR: In this paper, a multi-objective formulation of the FDI problem is presented based on linear matrix inequalities (LMIs) and extended LMIs are used to eliminate the couplings of Lyapunov matrices with the system state space matrices.
Abstract: In this study, the problem of event-triggered fault detection and isolation (FDI) for discrete-time linear time-invariant systems is considered. Using a Leunberger observer as the residual generator, a multi-objective formulation of the FDI problem is presented based on l
1
, H
_ and H
∞
performance indices. For each performance index, sufficient conditions for the design of FDI observer are presented based on linear matrix inequalities (LMIs). To reduce the conservativeness of the multi-objective problem, extended LMIs are used to eliminate the couplings of Lyapunov matrices with the system state space matrices. It is shown that through an event-triggered data transmission mechanism, the amount of data that is sent to the FDI module is significantly decreased. Simulation results corresponding to a remotely operated vehicle demonstrate the effectiveness and capabilities of the proposed design methodology.
TL;DR: In this paper, data-driven model-free adaptive control (MFAC), model free control (MFC) and virtual reference feedback tuning (VRFT) techniques are applied to the control of a representative non-linear multi-input-multi-output (MIMO) system represented by the twin rotor aerodynamic system (TRAS).
Abstract: This study proposes data-driven model-free adaptive control (MFAC), model-free control (MFC) and virtual reference feedback tuning (VRFT) techniques applied to the control of a representative non-linear multi-input-multi-output (MIMO) system represented by the twin rotor aerodynamic system (TRAS). These data-driven techniques are implemented for both a single MIMO controller and two separately designed single-input-single-output controllers running in parallel for azimuth and pitch control. The three techniques are implemented as MFAC and MFC algorithms and as linear controllers tuned by VRFT. The performance of the three data-driven MIMO control system structures is compared systematically on the basis of the experimental results in terms of the values of the sum of mean squared control errors measured on TRAS equipment.
TL;DR: In this article, the free-matrix-based summation inequality is proposed for discrete-time systems with time-varying delays, which further extends existing summation inequalities in the literature.
Abstract: This study proposes a new summation inequality, called the free-matrix-based summation inequality, which further extends certain existing summation inequalities in the literature. Less conservative stability criteria are proposed for discrete-time systems with time-varying delays. Numerical examples are provided to demonstrate the improvement of the proposed approach.
TL;DR: In this paper, a fractional-order control scheme was proposed to enforce finite-time convergence of the sliding manifold to guarantee local exponential tracking of a light-weight UAV.
Abstract: Light weight quadrotors are highly manoeuvrable autonomous aerial robots (UAV) that outperform most UAVs; however, quadrotors are prone to a wide class of aerodynamic disturbances, vibrations, and uncertainties that demand not only robust but fast attitude control structures. These arguments are compelling enough to motivate the design of a novel fractional-order control scheme that enforces finite-time convergence of the sliding manifold to guarantee local exponential tracking. The controller does not exhibit chattering and does not require the knowledge of the dynamic model. The stability analysis is based on a proposed resetting memory principle to deal with memory effects of the differintegral operator, which allows the controller to tackle also robustness against continuous disturbances that are not necessarily differentiable in the conventional sense such as some aerodynamic phenomena. Experimental evidence is presented and discussed to expose the enforcement of the sliding manifold based on a fractional-order reaching phase that demonstrates the feasibility of the proposed control scheme.
TL;DR: In this article, a fractional-order model of the PMSM velocity servo system is obtained theoretically for an improved modelling precision, and two H676 ∞ stabilising output feedback controllers are designed using a simple scheme according to the identified fractionalorder model and the traditional integer order one, respectively.
Abstract: This study presents fractional-order system modelling and control for a permanent magnet synchronous motor (PMSM) velocity servo system. Fractional-order model of the PMSM velocity servo system is obtained theoretically for an improved modelling precision. To identify the parameters of the proposed fractional-order model, an enhancement of the classic Levy identification method with weights is applied. In a real-time PMSM velocity servo plant, the fractional-order model is identified according to the experimental tests using the presented algorithm. The fact that the fractional model is more accurate than traditional integer-order model is substantiated using by the mean square error performance index. Two H
∞
stabilising output feedback controllers are designed for velocity servo using a simple scheme according to the identified fractional-order model and the traditional integer order one, respectively. The experimental test performance using these two designed H
∞
controllers is compared to demonstrate the advantage of the proposed fractional-order model of the PMSM velocity system.
TL;DR: In this article, a hybrid driven communication scheme is proposed, which can improve the system performance and reduce the network transmission, and a Bernoulli distributed stochastic variable is introduced to describe the switch law of the communication.
Abstract: This study investigates controller design for networked control systems under hybrid driven scheme. A hybrid driven communication scheme is proposed, which can improve the system performance and reduce the network transmission. A Bernoulli distributed stochastic variable is introduced to describe the switch law of the communication scheme. A general system model under hybrid driven scheme is then constructed. Based on this model, sufficient conditions are derived to guarantee the desired system performance. Furthermore, criteria for co-designing both the feedback gain and the trigger parameters are established. Finally, simulation results show the usefulness of the proposed method.
TL;DR: In this paper, an asynchronous finite-time dynamic output feedback control problem is concerned for switched time-delay systems with non-linear disturbances, and all the conditions are formulated in forms of a set of linear matrix inequalities which can be easily solved by using the interior point method.
Abstract: The asynchronous finite-time dynamic output feedback control problem is concerned for switched time-delay systems with non-linear disturbances. By constructing multiple Lyapunov functions and resorting to the average dwell-time approach, an asynchronous dynamic output feedback controller is designed to ensure the finite-time stability of the resulting closed-loop system, where asynchronous means that there is a lag between switching of controllers and subsystems. It should be pointed out that the Lyapunov function energy is allowed to increase during the running intervals of the active subsystems. Furthermore, all the conditions are formulated in forms of a set of linear matrix inequalities which can be easily solved by using the recently developed interior point method. Finally, two examples are provided to show the potential of the main results.