Search

Traditional machining is transforming to digital and intelligent machining, in which adaptive machining cyber-physical system (CPS) provides a useful approach to control the machining quality of large thin-walled parts. And the running of adaptive machining CPS is a complex multi-processes execution flow, which can be regarded as a continuous–discrete hybrid system. To realise adaptive controlling of machining quality and adaptive managing of process flow, a unified model for continuous–discrete hybrid adaptive machining CPS is constructed. Firstly, an architecture of adaptive machining CPS is proposed. Next, the cutting process in adaptive machining CPS is modelled as a continuous-variable system (CVS), while the process flow in adaptive machining CPS is modelled as a discrete-events system (DES). Then, the finite state machine is adopted to integrate the CVS and DES to form the unified model of adaptive machining CPS. Finally, an adaptive machining CPS is developed based on the unified model, and the machining results demonstrate that machining quality is efficiently controlled, as well as the process flow is orderly managed. The built unified model has four features, respectively universality, integrability, scalability, and reconfigurability, which can be reconstructed to form a new instancing model according to the different machining requirements. [ABSTRACT FROM AUTHOR]

In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios. [ABSTRACT FROM AUTHOR]

• We propose a novel adaptive sliding mode based spacecraft attitude controller. • The boundary of the model uncertainty and external disturbance is not required. • Actuator failure and saturation problem is considered by using an RBF network. • A control gains reduction technique is applied to weaken chattering phenomenon. Taking the external disturbance, model uncertainty, actuator failure, and actuator saturation into consideration, this paper investigates the nonlinear fault-tolerant attitude control problem for the spacecraft. First, to deal with the disturbance and uncertainty with unknown boundaries, an adaptive sliding mode control method is proposed to stabilize the state variables of the spacecraft attitude control system. Then the actuator failure and saturation are further considered, and the second spacecraft fault-tolerant attitude controller is derived based on adaptive sliding mode control and radial basis function (RBF) neural networks. The adaptive control gains reduction technique is applied in the design process, which can weaken the chattering phenomenon of the controller to some extent, and the stability of the attitude control system is analyzed through Lyapunov theory. In the proposed controller, model information and external disturbance are not required and only the system states are needed. Furthermore, the boundaries of the model uncertainty, external disturbance, actuator fault and saturation are assumed to be existing but unknown by the proposed controllers. These features make the proposed attitude controllers need few modeling information of the spacecraft, or maintain strong robustness even if the model or external environment occurs significant changes. Finally, numerical simulations demonstrate the great performance of the proposed fault-tolerant attitude control method. [ABSTRACT FROM AUTHOR]

This article concentrates on the problem of adaptive event-triggered control with double-side event-triggering mechanisms for a family of switched nonlinear systems with measurement sensitivity. In order to circumvent the negative effect of intermittent transmission and sensor measurement sensitivity on the output, an extended system is constructed by introducing a first-order output filter. Then, an input-driven neural switched observer is designed to estimate unmeasurable system states. To deal with the mutual interaction between the triggering and the switching mechanisms and their negative effect on the positive lower bound of inter-execution intervals, an incremental compensation is incorporated in the event-triggering mechanism (ETM) at the output sensor side. At last, a novel event-triggered control scheme built on both sides of the controller and output is proposed, which exhibits superior efficacy compared to the one-side event-triggered control scheme. By using the methods of the average dwell time (ADT) and the backstepping design, it is guaranteed that all signals of the switched closed-loop system are semiglobally uniformly ultimately bounded (SGUUB), and the Zeno phenomenon is excluded. The efficacy of the proposed methodology is validated by using a numerical simulation and a one-link robot system. [ABSTRACT FROM AUTHOR]

This paper studies the non-singular practical fixed-time neural adaptive control issues for multi-input and multi-output (MIMO) nonlinear systems with non-strict feedback form. Neural networks (NN) are used to estimate the unknown nonlinearities and deal with the problem of an algebraic loop. Under the framework of the backstepping control design, a practical fixed-time adaptive NN control method is developed by using the adding power integration technology. According to the Lyapunov function theory, it is proved that the closed-loop system is practical fixed-time stable, and the system can track the desired reference signal within a fixed time. Finally, the proposed practical fixed-time control method is applied to a multi-motor control platform, which proves the effectiveness of the control method. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive cooperative formation controller is developed to force a swarm of nonholonomic mobile robots with limited sensing ranges to move along the desired reference trajectory in a predetermined formation, while maintaining communication connectivity among the initial user-specified connected robots and guaranteeing no collision between the robots. Both kinematic models and dynamic systems with parametric uncertainties are discussed. The presence of parametric uncertainties is handled by adaptive control technique. A novel artificial potential function, which is based on a 4 times differential pseudo bump function, is constructed to achieve collision avoidance and connectivity maintenance. The control design is based on a fusion of potential function, adaptive backstepping technique, and Lyapunov synthesis. The cooperative formation controller is proven to be stable and can guarantee that there is no collision between any robots and the initial connectivity of the communication network can be always maintained. The proposed formation control approach is decentralized in the sense that the control action on each robot depends only on information from its neighbours and the desired trajectory of the group. Comparative simulation and experiment studies are performed to show the effectiveness of the proposed formation controller. [ABSTRACT FROM AUTHOR]

In order to improve the intelligent perception and adaptability of the 6G network, drones joined this challenge. For large-scale long-range Unmanned Aerial Vehicle (UAV), most of the time during normal flight belongs to fixed altitude flight. It is required to sail along the planned optimal path. Whether it can fly along the optimal path is mainly attributed to the tracking problem of horizontal flight trajectory. In order to minimize the UAV horizontal plane tracking error, it is necessary to consider the influence of many factors (such as strong winds, heavy rain, obstacles, etc.). Due to the complexity of High-Altitude environment, these disturbances are uncertain. In addition, there are some dynamic errors in the model of UAV control system, and these errors also have uncertainties. And, due to the change of global planning path coordinates, the control system needs to adjust the set value in real time during AUV horizontal trajectory tracking, and the conventional control algorithm is difficult to meet the requirements. Therefore, firstly, the influence of prediction uncertainty of grey prediction on AUV horizontal track tracking control is used; Then the grey prediction is improved according to the practical application; Ultimately, the control law is designed by combining the grey prediction with the control method. Finally, the grey prediction fuzzy adaptive PID method of UAV flight control is applied to the planned path simulation, and good control results are obtained. [ABSTRACT FROM AUTHOR]

This paper is devoted to adaptive trajectory tracking of quadrotor systems with full-state constraints and random disturbances. The command-filtering technology combined with error compensation mechanisms is proposed to deal with the "explosion of complexity" problem in traditional backstepping design and reduction of the filtering errors. The Barrier Lyapunov functions (BLFs) are constructed to ensure that all system states do not violate the boundary of its constraints. The command-filtered adaptive fuzzy controller is designed such that the state constraints are not breached almost surely, all signals in the closed-loop system are bounded almost surely, and the first-order moment of the tracking error converges to an arbitrarily small neighborhood of zero by parameters tuning. Finally, the effectiveness of the proposed control method is illustrated by simulation results. [ABSTRACT FROM AUTHOR]

Proportional pressure-reducing valve (PPRV) is widely used in brake circuits and pilot supply lines for directional control valves. The performance of PPRV can be degraded because of the effect of magnetic hysteresis, frictions, and other disturbances, which worsens the accuracy of the entire hydraulic system. This paper presents a high-performance pressure controller of a PPRV considering the model nonlinearities. A nonlinear phenomenological model based on the Hammerstein modeling method is first developed to describe the dynamics of a PPRV. A pressure-dependent damping ratio is carried out to handle the asymmetric nonlinearity at the starting process of pressure adjustments, and a series of experiments are conducted to verify the effectiveness of the model. A second-order adaptive robust controller is developed based on the Lyapunov theorem to guarantee the tracking performance in the presence of parameter uncertainties and uncertain nonlinearities. Comparative experiments show that the proposed second-order adaptive robust control algorithm together with the phenomenological model achieves a significant reduction in pressure-tracking error, compared with the one without the proposed plant model, or other existing controllers such as the feedforward proportional–integral–derivative (PID) controller and the first-order adaptive robust controller. [ABSTRACT FROM AUTHOR]

An adaptive image-based visual servoing (IBVS) controller is designed for a quadrotor unmanned aerial vehicle (UAV) to achieve robust tracking for moving targets, under underactuation and tight coupling constraints of UAV kinematics. Specifically, image features are selected from perspective image moments of a planar target to obtain virtual feature dynamics regarding UAV kinematics and dynamics. By constructing an auxiliary variable, a translational velocity observer for moving target is constructed by using virtual image features. An IBVS tracking controller is designed without target geometric information by combining UAV and visual feature dynamics. Designed controller and observer make the UAV robustly reach desired height and track the moving target, despite uncertainty of target movement. The controller has asymptotical convergence performance, and the target velocity is observed according to Lyapunov stability analysis. Simulation and experimental results show that the proposed method has smoother and more accurate performance in motion tracking and target velocity prediction under system uncertainty. [ABSTRACT FROM AUTHOR]

This paper presents an innovative adaptive fractional-order (FO) terminal sliding mode (TSM) controller designed for a 5-degree-of-freedom (5-DOF) upper-limb exoskeleton robot. The primary focus is on addressing the challenges posed by nonlinearities and uncertainties in parameter values. The proposed approach integrates several key elements, including a novel fractional-order non-singular terminal sliding mode (FONSTSM) surface, an exponential reaching law, and the utilization of the extreme learning machine (ELM). This comprehensive strategy guarantees not only finite-time convergence but also robust stability, effectively alleviating the well-known chattering phenomenon. Furthermore, it successfully overcomes the singularity issues typically observed in conventional TSM controllers. The incorporation of the ELM with rectified linear unit (ReLU) activation function enhances robustness by facilitating the estimation of parameters related to the exponential control law. Numerical simulations provide compelling evidence of improved tracking, increased robustness against uncertainties, achievement of finite-time convergence, and notable reductions in control signal oscillations and singularity problems. [ABSTRACT FROM AUTHOR]

Formation control is a fundamental task in the realm of autonomous multiagent systems. To drive a group of agents to maneuver continuously with the desired formation, this paper studies the finite‐time affine formation control problem with disturbances, input constraints and safety guarantee. A non‐singular terminal sliding mode control (NTSMC) is implemented to achieve finite‐time convergence of all followers to their desired positions. Additionally, an auxiliary system is deployed to address input constraints resulting from the physical properties of the affine formation system. To mitigate the impact of lumped disturbances, a finite‐time disturbance observer (FTDO) is employed to estimate the disturbances and compensate for their effects. Based on FTDO, the auxiliary system and the above NTSMC, a finite‐time robust controller is developed as the nominal controller. By modifying the nominal controllers to comply with safety constraints, control barrier functions are employed to ensure the safety of the formation system in obstacle‐filled environment. Finally, the effectiveness and feasibility of this method are validated through simulations and real‐world experiments. [ABSTRACT FROM AUTHOR]

In response to the problem of disturbance in the imaging equipment of stratospheric airships, this study designs a vibration isolation and stability system for carrying imaging equipment. The system mainly consists of microprocessor, gimbal, voice coil motor (VCM) and rubber ring. By using adaptive control law based on characteristic model to control the double closed control loop of the motor composed of position loop and speed loop, the camera deflection caused by disturbance is effectively eliminated. Furthermore, in vertical vibration suppression, the adaptive control law based on the characteristic model is also applied to the double closed control loop of the voice coil motor, which removes most of the vertical vibration and realizes active vibration isolation. The passive isolation of the system is completed by rubber rings. The experimental results show that the vibration isolation and stabilization system have good performance in complex disturbance environments, effectively stabilizing the imaging equipment. [ABSTRACT FROM AUTHOR]

The group‐weighted containment (GWC) problem is studied for swarms of robots, where the information flow among agents is heterogeneous (weighted) cooperative‐competitive and the whole networked systems are composed of multiple different groups. Each group is formed by multiple harmonic oscillator leaders and multiple robot followers governed by Euler‐Lagrange (EL) equations. After introducing the definition of group‐weighted containment to the networked robot systems, the control algorithms for the agents containing followers and leaders are formulated over newly weighted cooperative‐competitive network. Some necessary conditions for solving the weighted containment control problem are established. It is shown that the followers in every group can achieve a kind of novel coordinated behaviors. Specifically, the followers can converge to the dynamic convex hull spanned by the corresponding leaders' weighted coordinates under some conditions. Simulation results are provided to illustrate the effectiveness of the proposed control schemes. [ABSTRACT FROM AUTHOR]

This work presents a variable step Champernowne Adaptive Filter (VS-CAF) based control architecture for a grid-integrated solar photovoltaic system. The control structure is implemented to successfully synchronize the two-stage solar photovoltaic at the point of common coupling where the source and domestic loads are connected. The control architecture ensures solar power injection and improvised power quality at the unity power factor. Moreover, the control structure provides only the balanced positive sequence fundamental sinusoidal source currents at solar irradiation alteration and load disturbances. The VS-CAF is exploited to estimate the peak of the fundamental component out of the harmonics-rich domestic load currents. To examine the efficacy of the suggested control technique, a 40 kW solar photovoltaic is simulated using MATLAB/Simulink. The performance assessment of the grid-tied solar generation system is carried out at solar irradiation alteration, zero solar irradiation, and detachment of one phase of the three-phase load. Various simulation results are carried out to verify the successful integration of solar photovoltaics into the three-phase grid following the IEEE-519 standard and satisfactory performance during various working conditions. Moreover, the simulation results are also verified with real-time results taken from the Opal-RT simulator. [ABSTRACT FROM AUTHOR]

Aiming at the security consensus control problem of leader‐following multi‐agent systems (MASs) under hybrid random cyber attack, this article proposes a novel sampled information related adaptive event‐triggered control mechanism (SIRAETCM). While ensuring the safety performance of the MASs, the mechanism adaptively and dynamically adjusts the trigger threshold of every agent to achieve discontinuous communication by using only the current and latest sampled signals. According to the MASs communication mode and Bernoulli attack model, a security consensus control protocol is constructed, and a bilateral sampled‐interval Lyapunov functional (BSILF) method is introduced to obtain more sampling interval information and establish sufficient conditions for the leader‐following state error system to stabilize asymptotically under hybrid random cyber attacks. Meanwhile, under a large sampling interval, the controller gain and adaptive event‐triggered parameters are designed and obtained. The simulation of the tunnel diode circuit system shows that the SIRAETCM can reduce the number of communications between agents to improve bandwidth utilization, and the adopted safety cooperative control protocol can improve the safety and effectiveness of the MASs. [ABSTRACT FROM AUTHOR]

In this paper, the problem of sampled-data adaptive tracking control for a class of switched nonlinear systems with prescribed performance is considered. In order to guarantee the system is stable and achieves the prescribed performance in sampled-data control, a coordinate transformation satisfying the prescribed performance is introduced. In addition, the neural networks (NNs) used to approximate the unknown nonlinear functions and the backstepping technique are applied to design the sampled-data controller and the adaptive laws. An upper bound on the sampling period is obtained to maintain the stability of the systems. It is confirmed that the designed sampled-data scheme ensures that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error is limited to the prescribed performance function. The effectiveness of the designed control scheme is demonstrated by two simulation examples. [ABSTRACT FROM AUTHOR]

This paper proposes a novel control methodology to achieve fixed-time stabilisation for a class of three-order nonlinear systems based on fast nonsingular terminal sliding mode control. In this research, based on the combination of integral fast nonsingular terminal sliding mode (IFNTSM) surface and fixed-time control theory, a novel backstepping fast nonsingular terminal sliding mode (FNTSM) controller is being studied. The interests of this method are that the presented controller can not only maintain the characteristics of integral fast nonsingular terminal sliding mode control (IFNTSMC) but also has the advantages of fixed time convergence and fast transient response. Piecewise function is introduced to solve the singularity problem caused by negative exponential term. Our control strategy achieves the stabilisation performance within finite convergent time being independent of initial condition. The control scheme is applied to the gyros system with chaotic state and suppress its chaotic phenomenon. The theoretical results are supported by simulation results. [ABSTRACT FROM AUTHOR]

This paper focuses on finite-time adaptive practical tracking control for a class of high-order nonlinear systems with full-state constraints and input saturation. The state constraints are handled by applying nonlinear transformed functions (NTFs) and the input saturation is estimated by an auxiliary hyperbolic tangent function. On the basis of adding a power integrator technique and adaptive control method, an adaptive state feedback controller is designed for the closed-loop system. With the aid of finite-time stability theory, the tracking error converges to a bounded neighbourhood of the origin in a finite time, and all the signals in the closed-loop system are bounded. At last, a simulation example and a practical example are presented to show the effectiveness of the proposed control procedure. [ABSTRACT FROM AUTHOR]

In this paper, for strict-feedback nonlinear systems with positive odd rational powers, the problem of adaptive fixed-time tracking control (FTTC) is considered. With the support of fixed-time theorem and adaptive backstepping method, this paper proposes a new globally adaptive FTTC strategy, which can overcome the singular problems caused by the derivation of virtual control signal. In addition, the proposed control scheme is a universal approach that can be applied to other types of nonlinear systems. Furthermore, the designed adaptive fixed-time tracking controller ensures the boundedness of all signals in the controlled system, and it guarantees the tracking error converges to a small neighbourhood near equilibrium in fixed-time. Finally, the simulation result further verifies the feasibility of the presented control scheme. [ABSTRACT FROM AUTHOR]

Summary: In order to solve the problem of inconsistency between cells in lithium‐ion battery packs, a hybrid equalization topology based on a three‐winding transformer and a group adaptive interleaved control strategy are proposed. The scheme not only has two equalization types, pack to cell (P2C) and cell to pack (C2P), but also adaptively adjusts the equalization type according to the state of the battery pack, so that the equalization circuit always works in the best state and realizes the fast equalization of the battery pack. Through the analysis of speed, efficiency, and cost, it is concluded that the scheme has the characteristics of fast balancing speed, high balancing efficiency, and low cost. Then the experimental analysis was carried out under three working conditions of charging, shelving, and discharging to verify the feasibility of the novel scheme in practical applications. [ABSTRACT FROM AUTHOR]

Software-defined perimeters (SDP) revolutionize network security by offering dynamic and adaptive access controls, focusing on user and device authentication to substantially reduce the attack surface. Despite their potential, traditional SDP models grapple with challenges in scalability and component-level security, limiting their effectiveness in complex digital environments. To overcome these limitations, this article introduces SecureSDP, a sophisticated evolution of the SDP framework designed to enhance scalability and bolster security for each network component. SecureSDP stands out for its seamless integration into varied organizational structures, delivering a robust and comprehensive security solution that strengthens the network's defenses across all layers. The key advancement of SecureSDP is evidenced by rigorous experimental evaluations, which demonstrate its superior performance in improving network security and scalability. Specifically, SecureSDP achieved substantial increases in the hardening scores across various tools: 65% in Lynis, 78% in Chef Inspec, and 30% in OpenSCAP for the SDP controller. These enhancements underscore SecureSDP's significant contributions to the field, marking a pivotal step forward in the development of more secure, scalable network infrastructures. [ABSTRACT FROM AUTHOR]

In this paper, we deal with the global approximation of solutions of stochastic differential equations (SDEs) driven by countably dimensional Wiener process. Under certain regularity conditions imposed on the coefficients, we show lower bounds for exact asymptotic error behaviour. For that reason, we analyse separately two classes of admissible algorithms: based on equidistant, and possibly not equidistant meshes. Our results indicate that in both cases, decrease of any method error requires significant increase of the cost term, which is illustrated by the product of cost and error diverging to infinity. This is, however, not visible in the finite-dimensional case. In addition, we propose an implementable, path-independent Euler algorithm with adaptive step-size control, which is asymptotically optimal among algorithms using specified truncation levels of the underlying Wiener process. Our theoretical findings are supported by numerical simulation in Python language. [ABSTRACT FROM AUTHOR]

The purpose of this research is to address the problem of synchronization between two identical biological hyperchaotic snap oscillator systems with unknown parameters at a fixed time, as well as to design a new theory for synchronizing two different chaotic systems. Firstly, we designed an adaptive controller using Lyapunov stability and fixed-time stability theory to achieve synchronization between two identical biological hyperchaotic snap oscillator in fixed time under unknown parameters. Among the results obtained, we found that the synchronization time for system states occurred in a very short time compared to results in previous research. Secondly, we extended and generalized synchronization between non-identical chaotic systems by creating a theory for achieving synchronization in which adaptive control and fixed-time stability are combined. Through the new theory, the unknown parameters in chaotic systems were estimated, and the settling time was determined, which turned out to be very short and independent of the initial conditions of the system states. One of what makes the scheme important is that it can be easily applied to most chaotic and even hyperchaotic systems in the shortest possible time. Finally, we gave examples of different systems to test the feasibility and effectiveness of the scheme that was designed. [ABSTRACT FROM AUTHOR]

Summary: This article investigates the adaptive finite‐time control design with performance assurance for nonlinear Markov jumping systems. First, the radial basis function neural networks are applied to tackle unknown nonlinear terms. Subsequently, within the framework of the command‐filtered backstepping control, the new error compensation signals are devised to remove the effect caused by filter error. Additionally, an adaptive finite‐time prescribed performance control law with an event‐triggered mechanism is developed to achieve a balance between tracking performance and bandwidth consumption, which ensures that the closed‐loop system is practically finite‐time stable in mean square and guarantees that the tracking error adjusts to the predetermined area. Finally, two simulation examples are provided to verify the validity and superiority of the devised scheme. [ABSTRACT FROM AUTHOR]

This article investigates the finite‐time recoil control problem of deepwater drilling riser systems with nonlinear friction force, tension force and saturation input. For the friction force, a new approximation model based on radial basis function neural networks is presented, which not only can ensure a better approximation effect than the sine‐function type and exponential‐polynomial‐function type computational models, but also can be easily used for control design. Different from the existing linear optimal control methods, a neural‐network‐based adaptive backstepping control method is proposed to deal with the nonlinear friction and tension forces, which can achieve better recoil control responses. An auxiliary system combining with the change of coordinates is employed to compensate the saturation input effect. To prolong the average release interval of control input while preserving satisfied control performance, a new switched event‐triggered control (ETC) scheme is developed, in which the triggering conditions are switched between the fixed and relative thresholds based on the strength of control signal. With the event‐triggered controller, the practical finite‐time stability condition of recoil control system is derived and the Zeno behavior is avoided. Numerical results are given to show the advantages of the proposed methods in handling the model nonlinearities, finite‐time stability and ETC performance of riser‐tension systems. [ABSTRACT FROM AUTHOR]

The problem of adaptive event‐triggered security tracking controller design is studied for interval type‐2 (IT2) Takagi‐Sugeno (T‐S) fuzzy‐approximation‐based nonlinear networked systems with deception attacks, privacy protection, and dynamic quantization in this paper. To reduce the network burden, the adaptive event‐triggered schemes (AETSs) and dynamic quantization are introduced to reduce unnecessary transmission and the number of network packets, respectively. Under the framework of network security, a novel security co‐design scheme with the tracking controller, AETSs, and the quantizers is developed, in which the privacy protection of the reference model and the deception attacks of the controller are taken into consideration simultaneously. Sufficient conditions for the results system to be mean‐square asymptotically stable with a H∞$$ {H}_{\infty } $$ tracking performance are established. Finally, two practical simulation examples demonstrate the effectiveness and novelty of the proposed design strategy. [ABSTRACT FROM AUTHOR]

In this article, we study the leader‐following formation problem for high‐order nonlinear multi‐agent systems with an uncertain leader system over switching networks. We first divide the uncertain leader system into two types and then design adaptive distributed observers for them respectively. Then, based on our designed observers, we synthesize two adaptive distributed control laws respectively to solve our problem, forcing the errors between the states of the followers and that of the leader to the prescribed time‐varying desired formation vectors. Finally, our main result is illustrated by two examples. [ABSTRACT FROM AUTHOR]

A novel full state‐constrained integrated guidance and control (IGC) schema for aerial interceptors under input saturation with tunnel‐prescribed performance is proposed. To achieve an appointed‐time engagement with less overshoot phenomenon, the tunnel‐prescribed performance control (TPPC) technique is applied to generate virtual guidance laws, where the tracking of desired line of sight (LOS) angles possesses predefined‐time convergent property. For the sake of the flight safety of interceptors in a practical flight environment, the physical limitations on the flight angles and the angular rates of attitude systems are taken into consideration. The integral barrier Lyapunov function (iBLF) technique is adopted to ensure all the attitude states within a user‐defined domain. The nominal virtual commands are generated adaptively by the backstepping method combined with some novel dynamic surfaces. To further eliminate the possible input saturation, a novel one‐order auxiliary system is constructed to compensate for the discrepancy of the virtual input commands. All the signals in the closed‐loop system are strictly proven to be bounded by Lyapunov theory. The simulation results show the effectiveness of the proposed IGC schema by comparison with other IGC laws. [ABSTRACT FROM AUTHOR]

In this paper, the problem of decentralized adaptive proportional‐integral (PI) tracking control is investigated for a class of strong interconnected nonlinear systems in presence of unmodeled dynamics and uncertain input delays. A novel compensation mechanism is proposed to deal with the considered strong interconnection functions by applying a smooth switching function to the design algorithm, and the difficulty generated by unmodeled dynamics is dominated by using a dynamic auxiliary signal. By utilizing the suitable error transformations and selecting the appropriate Lyapunov‐Krasovskii function, the effects of uncertain input delays could be surmounted. The novelty of this study is that, for the first time, a new decentralized adaptive PI tracking control scheme including a switching compensation mechanism is developed for the considered strong interconnected nonlinear systems. It is proved that all the signals in the closed‐loop systems are uniformly ultimately bounded (UUB) and the tracking errors converge to a bounded compact set. Finally, a simulation example is carried out to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this technical article, the trajectory‐tracking problem of event‐based adaptive prescribed performance control for underactuated autonomous underwater vehicles (AUVs) is considered. The primary innovation of this article is the proposal of a segmented event‐triggered mechanism (SETM) that incorporates preselected convergence time. This mechanism allows for the regulation of communication frequency in the control channel (controller‐to‐actuator) according to the dynamic characteristics of the AUV system at different stages. In addition to presenting new design scheme based on SETM, an enhanced vision known as segmented hybrid event‐triggered mechanism (SHETM) is introduced. Notably, the minimum and maximum triggering intervals (MITI and MATI) for these two ETMs can be calculated from the corresponding resettable dynamic variables presented in the trigger conditions. Subsequently, by utilizing the proposed asymmetrical prescribed performance control (APPC) strategy, the system's output tracking error behaviors in both transient and steady‐state stages can be qualitatively predetermined through design parameters within the boundary function. Moreover, the minimum learning parameter (MLP) based RBFNN adaptive control law is developed to counteract the effects of model uncertainties and ocean current perturbations. Finally, rigorous theoretical analysis and simulation results confirm the viability of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper investigates a distributed adaptive finite‐time containment control scheme for multiple unmanned aerial vehicles subject to external disturbances and input saturation. Combined with a novel indicator of the saturation degree designed by the hyperbolic tangent function, an adaptive method is proposed to deal with the input saturation issue, which considers both symmetry and asymmetry saturation. Moreover, to address the problem of the "explosion of terms" inherent in the traditional backstepping controller design, a fixed‐time sliding mode differentiator is utilized to approximate the derivative of the virtual signal in the command‐filtered backstepping method. Finally, the convergence of the errors and the practicability of the control law are verified by Lyapunov stability analysis and numerical simulations. [ABSTRACT FROM AUTHOR]

Considering the complexity of communication environment in reality, this paper investigates the adaptive output consensus problem for heterogeneous nonlinear multi‐agent system (MAS) under random link failures, in which connection of each link may suffer from link failure. The major challenge lies in dealing with the coupling among different nonlinearities and integrator orders of heterogeneous agents while the distributed communication may fail randomly. Hence, a two‐level distributed adaptive control scheme based on the virtual model‐reference strategy will be presented. In the first level, virtual reference models are constructed to deal with the uncertainties caused by the random link failures, and a distributed consensus control strategy is designed based on the established communication observer of each agent. In the second level, an adaptive backstepping tracking controller drives each agent's output to follow its virtual reference model and compensate for the agent's uncertainties. The mean square stability of the controlled MAS has been rigorously proved. An illustrative example is presented to demonstrate the effectiveness of the given control scheme. [ABSTRACT FROM AUTHOR]

This article presents a novel adaptive composite learning (ACL) control strategy combining reinforcement learning and a disturbance observer (DOB) to address vibration issues in a flexible two‐link manipulator (FTLM) system affected by unknown spatiotemporally varying disturbances. Based on the assumed mode method, the FTLM system is initially transformed into an ordinary differential equation model, while effectively capturing the elastic deformation and vibration characteristics of the flexible link. A composite learning controller, based on the actor‐critic algorithm and DOB, is then developed to achieve trajectory tracking and vibration suppression in the FTLM system. The DOB in the controller compensates for unknown disturbances resulting in reduced system error. It is noting that the proposed optimal control strategy is continuously gathering system experience and evaluating the current policy's effectiveness. The stability and robustness of the closed‐loop system incorporating the composite controller are analyzed using Lyapunov's direct method, and the semi‐global uniform ultimate boundedness of the tracking and vibration errors are also demonstrated. To validate the effectiveness and superiority of the proposed ACL controller, comparative simulations and experiments are conducted on the Quanser experimental platform. [ABSTRACT FROM AUTHOR]

This article considers the adaptive tracking control problem of a class of strict feedback nonlinear systems with unknown time‐varying parameters. Note that the recent adaptive method, that is, congelation of variables, is built upon the assumption that the known basis functions are zeros as zero states. To remove this assumption, a novel monotonically increasing function is designed to transform the output tracking error and the backstepping tracking errors into increasing forms, which is integrated into the congelation of variables to design the σ$$ \sigma $$‐modification adaptive tracking control law. It is noted that the proposed form of monotonically increasing function is general, which includes positive proportional functions, exponential functions, and logarithmic functions and so on. To yield the boundedness of increasing tracking errors, a barrier Lyapunov function is designed. The asymptotic convergence of the resulting adaptive tracking system is analyzed in detail. Simulations demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Aerodynamic forces acting on a racing car will impact its handling, stability, and steering characteristics. Oversteering typically occurs in racing cars with a significant front-end downforce. In the process of racing, the car's attitude will change, causing a shift in the distribution of front and rear downforce. This, in turn, will impact the car's handling performance. Therefore, in this study, a set of aerodynamic devices with attitude-adaptive function linked to the suspension is designed to reduce aerodynamic attitude sensitivity. The range of the car's attitude changes, the adjustment ability of the front and rear flaps, and the reasonable matching relationship between different operating conditions and the attack angle of the front and rear flaps are confirmed. In this work, the matching relationship is achieved through the use of multiple groups of linkage mechanisms. The aerodynamic characteristics of the entire car are analyzed and simulated in the lap speed simulation. Results showed that the installation of the device reduces the center of pressure (CoP) movement during braking by 52%, the aerodynamic resistance of the entire racing car during acceleration by 19.5%, and the single lap time by 1.5%, while also inhibiting the generation of aerodynamic torque during roll. [ABSTRACT FROM AUTHOR]

As the simplest type of multi‐phase induction motor, the five‐phase induction motor is suitable for applications that require high power and reliability due to its advantages such as low noise, low torque ripple, and strong load capacity. To address the problem that the speed encoder is easily affected by external environmental interference, a speed sensorless vector control strategy combining linear active disturbance rejection control and adaptive full‐order observer is proposed. Compared with the traditional speed sensorless vector control strategy, this paper's proposed method designs three first‐order linear active disturbance rejection controllers instead of traditional proportional‐integral controllers for speed control. Experimental results show that the proposed strategy exhibits stronger anti‐interference ability under load disturbance, improving the overall robustness of the speed sensorless control system. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In aspects of its simple configuration and tunability, piezoelectric-based metasurface has benefited over its mechanical counterpart in adaptive wavefront manipulation. By tuning the circuitry elements in the shunting circuits properly, the equivalent material properties of the metasurface can be modified to attain a complete 2 π phase shift and to maintain high transmission at desired working frequencies. In this paper, a piezoelectric-based elastic metasurface with hybrid shunting circuits ( NC – LC – NC shunts) are proposed to adaptively control the propagation of flexural waves. Through tuning of negative capacitance and inductance simultaneously, the proposed elastic metasurface can cover a phase shift ranging from 0 − 2 π while having a high transmission ( ≥ 0.7). It is discovered that any similar metasurface structural design with solely single shunting circuit presently available could not achieve the same results as the proposed elastic metasurface. In addition, analytical modeling based on equivalent Young's modulus is developed and a finite element model is built to study the transmission and phase shift of the proposed metasurface. It is demonstrated numerically that the proposed piezoelectric-based elastic metasurface is capable of performing switchable functionalities, such as wave refraction and focusing, at different working frequencies (3500 Hz, 5000 Hz, etc.). Utilization of hybrid shunting circuits in designing a more compact metasurface design. Establish an analytical model based on equivalent Young's modulus to predict effective range of circuitry elements. Build a finite element model to study the transmission and phase shift of the piezoelectric-based metasurface. Cover a full 2 π phase shift and maintain high transmission through tuning negative capacitance and inductance simultaneously. Perform switchable functionalities at different working frequencies. [ABSTRACT FROM AUTHOR]

To alleviate the performance degeneration of the cooperative adaptive cruising control (CACC) of connected and automated vehicles (CAVs) with low market penetration rates (MPRs), it is necessary to resolve the performance degeneration of CAVs operating at weak mixed-platoon intensities for any-MPR CAVs. A car following model (PMCC) for CAVs is proposed, accounting for human reaction time, communication delay, traffic information memory, and vehicle-to-vehicle (V2V) communication. Linear stability analysis was conducted to validate the stability of mixed platoons at weak platoon intensities for different CAV following models. Numerical simulations were conducted to simulate weak-intensity mixed platoons for different CAV following models operating at high and low equilibrium velocities. The results suggest that PMCC exhibits wider stability equilibrium intervals under different theoretical time headway scenariosand performs well at dissipating the speed fluctuation propagation and minimizing the speed fluctuation amplitude. [ABSTRACT FROM AUTHOR]

The failures of high-consequence systems can cause serious harm to humans, including loss of human health, life security, finance, and even social chaos. To protect high-consequence systems, both optimal system design and maintenance activities contribute to improving system reliability and social safety. The existing works generally optimize these two problems sequentially and assume that the degradation process of components is precisely known. However, sequential optimization often results in significant losses due to redundancies, and such a presumption usually cannot be guaranteed in practice, due to limited historical data or a lack of expert knowledge, referred to as epistemic uncertainty. To fill this gap, in this article, we consider an integrated optimization of system design and maintenance scheduling for multi-state high-consequence systems in which the component's degradation is known with limited distributional information. To address this issue, we utilize the framework of distributionally robust optimization to provide a risk-averse decision to decision-makers even under the worst realizations of random parameters, and develop a two-stage integer distributionally robust model with moment-based ambiguity set to determine the system design and maintenance scheduling simultaneously. The proposed model can be converted to a tractable approximation as an integer linear stochastic programming problem. In order to solve large-scale problems, we develop a sample-based adaptive large neighborhood search algorithm to find the optimal system designs. In the numerical experiments, we present a case study on feedwater heating systems in nuclear power plants and demonstrate that an integrated optimization consideration creates significant benefits in profitability. We also present the out-of-sample performance of the distributionally robust design to avoid extreme risk. [ABSTRACT FROM AUTHOR]

This article studies the passive tracking problem of a wearable exoskeleton for lower limb rehabilitation therapy in the face of unmodeled dynamics, interactive friction, disturbance, prescribed performance constraints, and actuator faults. Adaptive neural networks and a smooth performance function are incorporated to establish a novel fault-tolerant tracking scheme, which can not only compensate for the nonlinear uncertainties and disturbance, but also handle the actuator fault with guaranteed tracking performance. A state feedback controller is presented by using the full state information and an output feedback controller is developed when the angular velocity is unavailable. The differential explosion issue of the backstepping technique is resolved by constructing a first-order filter and the unmeasurable velocity is estimated by a nonlinear observer. Semiglobal uniform boundedness stabilities of the exoskeleton system are proved via the Lyapunov direct method. The tracking performances of the designed control approaches are tested by comparative simulations. [ABSTRACT FROM AUTHOR]

This paper focuses on the output-feedback control for path-following of underactuated autonomous underwater vehicles subject to multiple uncertainties and unmeasured velocities. First, a novel extended state observer is proposed to estimate the mismatched lumped disturbance and recover the unmeasured velocities. Based on this premise, to overcome the limitation of relying solely on the accurate kinematic model, a disturbance observer-based stabilizing controller is developed. The difference in bandwidths between the observer and the vehicle dynamics allows for a mathematical setup amenable to standard singular perturbation theory. In the fast mode, a kinematic observer is designed to reject system uncertainty caused by unknown attack angular velocity and prohibitive path-tangential angular velocity, using a novel physical perspective. In the slow mode, an interconnected-system control law is proposed by integrating the backstepping technique with the time scale decomposition method. Furthermore, the stability of the overall closed-loop system is established. Finally, simulation results are presented to demonstrate the effectiveness of the proposed method for path-following of underactuated autonomous underwater vehicles in the vertical plane. • A novel ESO is developed to estimate the mismatched lumped disturbances and recover the unmeasured velocities by combining high-gain and singular perturbation techniques, leading to reduced complexity in stability analysis. • A DO is designed to estimate model uncertainties by utilizing the difference in bandwidths between the observer and state dynamics. The resulting singular perturbation analysis provides a new perspective on designing a DO in a straightforward manner. • An interconnected-system control law is proposed based on a time scale decomposition method to address the problem of the "explosion of terms" inherent in conventional backstepping. • The stability analysis enables the derivation of mathematical bounds on the control gains, offering guidance for selecting control gains to prevent controller ill-conditioning and/or closed-loop instability. [ABSTRACT FROM AUTHOR]

In this study, the problem of non-overshooting tracking control (NOTC) for a class of strict-feedback systems with prescribed finite-time (FT) is studied. In order to obtain a simple closed-loop system (CLS), we first propose a criterion lemma for prescribed FT stable control. A prescribed FT controller is designed by using backstepping and the proposed criterion lemma. According to the CLS, many conditions of NOTC are analyzed. Compared with the related results, the NOTC conditions obtained in this paper are relatively extensive, which reduces conservatism. The algorithm makes the system overshoot zero, so this result increases the accuracy. The final simulation results show that this algorithm is effective. • In the related research results of no overshoot control, the closed-loop system obtained by the existing prescribed finite-time control algorithm is very complicated. This leads to the failure to calculate the expression of tracking error through the closed-loop system, and then the control condition with non-overshooting cannot be obtained. Then, a new criterion lemma of prescribed finite-time control is proposed to design the control in this paper. Obviously, our closed-loop system is relatively simple. • In the related research results of non-overshooting control, the non-overshooting tracking control conditions obtained in this paper are relatively extensive, which reduces the conservatism of the existing algorithms. • Compared with mean-nonovershooting tracking control, the algorithm in this paper can make the overshoot of tracking error zero. Therefore, this result increases accuracy. [ABSTRACT FROM AUTHOR]

Uncertainty can lead to jitter or overshoot in mechanical systems, necessitating the design of multiple constraints to stabilize them. This paper proposes a control structure based on the generalized Udwadia–Kalaba equation to address these constraints simultaneously. An uncertain dynamical model is developed, incorporating both equality and inequality constraints. By integrating diffeomorphism theory, a robust control strategy is designed to ensure compliance with these constraints. Utilizing the Lyapunov approach, the uniform boundedness and uniform ultimate boundedness of the dynamical system are demonstrated. Finally, the feasibility of the proposed control method is validated through its application to a belt conveyor system. • Equality constraints and inequality constraints are simultaneously considered in dynamical system based on the generalized Udwadia–Kalaba approach. • A robust control for handling inequality constraints that does not affect equality constraints is designed. • The robust control can render the uncertain system uniformly bounded and uniformly ultimately bounded. • The method is proposed of applying inequality constraints to belt conveyors to avoid belt breakage and folding faults in engineering. [ABSTRACT FROM AUTHOR]

This research article details the design and implementation of a nonlinear adaptive filtering (NAF) technique using an exponential functional link network (EFLN) for a shunt hybrid active power filter (SHAPF) control to solve the current-associated power quality issues on the utility side at the distribution level of electrical power systems. Separation of the fundamental component from the harmonics, achieving unity power factor operation, reducing the reactive power drawn from the source, balancing the currents during transients, and reduction of total harmonic distortion (THD) of the source current are the issues considered to resolve. The proposed technique solves these issues by generating the sinusoidal reference current and separating the fundamental current from the harmonics. When compared to conventional and existing adaptive filtering techniques such as least mean square (LMS), least mean fourth (LMF), and variable step size LMS (VSS-LMS), the proposed EFLN-NAF method excels in terms of speedy convergence, adaptability in noise-specific environments and reduced steady-state coefficient error. MATLAB/Simulink software is utilized to perform the simulations to examine the suggested strategy for the chosen SHAPF topology both in static and dynamic scenarios. For a 15 kW and 3kVAr requirement of the nonlinear load, simulation results proved that the designed PPF for 2kVAr is able to share the reactive power with the APF, thereby reducing its rating and cost. The proposed method of filtering has been proven to be fast converging with 0.049 s, and the THD in steady state is brought to 1.32 % in steady-state and to 3.77 % during transient conditions, which are under standard limits. A hardware prototype of the experimental setup is constructed at the laboratory scale with OPAL-RT (OP4510) as the controller. With an active and reactive power demand of 1.1 kW and 210VAr, the designed PPF supplies 110 VAr, whereas the rest is supplied by the APF. The practical THD in source current is observed to be 2.081 %, which meets the standards. The results from both simulations and experiments are validated, and the efficacy of the proposed technique in mitigating the aforementioned power quality issues is proved. [Display omitted] • A passive power filter design to share the reactive power requirement in addition to mitigating the predominant harmonics of the 5th and 7th order. • A robust nonlinear adaptive filter implementation based on exponential functional link network (EFLN-NAF) algorithm to the shunt hybrid active power filter (SHAPF) control for reference current generation and fundamental component separation from harmonics. • Solution for current-associated power quality issues such as reducing the reactive power burden, achieving unity power factor operation, and mitigating the harmonics, thereby reducing the source current THD value. • Simulation of the proposed technique for the control of shunt hybrid active power filter and evaluation of the outcomes for resolving the power quality issues in both steady-state and dynamic conditions. • Development of a hardware prototype at a laboratory scale using OPAL-RT (OP4510) real-time simulator as a controller for the proposed technique for the control of SHAPF and evaluation of the outcomes. [ABSTRACT FROM AUTHOR]

This paper describes a new approach to control stall and surge instabilities in the compressor system by using of finite time backstepping-based adaptive sliding mode method. The most important innovation of this study is to provide a finite time adaptive control method to simultaneously prevent the stall and surge instabilities in a compressor system in the presence of disturbance and uncertainty in the compressor characteristic curve as well as the throttle valve. The disturbance and uncertainty issues are covered by a robust sliding mode control and the gain coefficients of this controller as well as the estimation of uncertain terms are obtained by using the adaptive method. The Lyapunov stability criterion is used to evaluate the finite-time stability of the closed-loop system. The performance of the proposed method is compared with other literature methods through simulation in Matlab. The simulation results show that the proposed controller is better than the existing methods in terms of surge preventing and robustness against uncertainty and disturbance. [ABSTRACT FROM AUTHOR]

At present, the controllable parameters of micro turbojet engines in engineering applications are mainly speed-fuel flow (hereinafter referred to as flow) control, in which closed-loop proportional–integral–derivative (PID) control is mostly used to achieve a stable control of engine speed under slow engine conditions. For the optimal adjustment of PID parameters, this paper designs an improved evolutionary strategy for the self-tuning of control parameters in the engine speed and flow control system and formulates an improved PI controller based on a neural network. The simulation experimental results show that the method can realistically achieve stable and fast control of the engine under above slow conditions. [ABSTRACT FROM AUTHOR]

The system performance of grid-connected photovoltaic (PV) has a serious impact on the grid stability. To improve the control performance and shorten the convergence time, a predefined-time controller based on backstepping technology and dynamic surface control is formulated for the inverter in the grid-connected photovoltaic. The time-varying tuning functions are introduced into state-tracking errors to realize the predefined-time control effect. To address the “computational explosion problem” in the design process of backstepping control, dynamic surface control is adopted to avoid the analytical calculations of virtual control. The disturbances of the PV system are estimated and compensated by adaptive laws. The control parameters are chosen and the global stability of the closed-loop is ensured by Lyapunov conditions. Simulation results confirm the effectiveness of the proposed controller and ensure the predefined time control in the photovoltaic inverter. [ABSTRACT FROM AUTHOR]