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This article introduces a novel strategy for devising an optimal Static Synchronous Compensator (STATCOM) controller via Hamiltonian function method in mitigating the transient stability of a multimachine power system. The STATCOM, a second generation shunt type FACTS device, is popularly employed for power system control. To test the applicability of the Hamiltonian function approach, an IEEE Type WSCC 9-bus system is taken under study. An appropriate Hamiltonian functional has been framed using the parameters of the test system, which is applied to optimize the preferred performance index. The performance of the proposed nonlinear controller is judged against a regular state feedback based STATCOM controller. The parameters of this traditional controller are computed via dynamical Games of the Nash Equilibrium method. The proposed method is beneficial in terms of mathematical complexity as needed in estimating relative degree and coordinate transformation in the feedback linearization method. A detailed investigation of the results reveals that the proposed controller is effective and efficient to a greater degree than the traditional STATCOM controller in a multimachine system, even at some point in serve eventualities like earth fault scenarios. [ABSTRACT FROM AUTHOR]

This article is concerned with the stability analysis of the static output‐feedback polynomial fuzzy‐model‐based (SOF PFMB) control systems through designing a novel membership grade integration (MGI) approach. The nonconvex problems of the SOF PFMB control systems are convexificated into the convex conditions by introducing block diagonal positive‐definite Lyapunov matrix and nonsingular transformation matrix. We proposed new approximate membership functions, that is, Lagrange membership functions (LMFs), which can be introduced into the stabilization process to relieve the conservativeness of stability results. The LMFs are general representations of piecewise‐linear membership functions, which makes the number of stability conditions not limited by the number of sample points. In a fixed subdomain, arbitrary sample points can be employed by the LMFs method and achieve higher approximation capability by increasing more sample points so that membership grades can be incorporated into the system analysis. Furthermore, a novel MGI approach, including the information of premise variables and LMFs, is proposed making the stability conditions more relaxed. Finally, two simulation examples show the merits of the developed techniques. [ABSTRACT FROM AUTHOR]

Platooning is an effective way to reduce air resistance and fuel consumption in vehicular transportation. However, stochastically generated disturbances can significantly impact the string stability of platoons. This article proposes a novel control law, based on sliding mode control and leader‐predecessor communications, designed to improve the exponential mean‐square string stability of platoons with Ito‐type stochastic disturbances that consider friction force. Specifically, our approach employs a third‐order nonlinear dynamic model to capture the relevant spatiotemporal correlations present in vehicle platoons. The proposed longitudinal control strategy effectively stabilizes the platoons with time delay and was verified through simulation experimentation. In this study, the stability of sliding mode motion is thoroughly investigated by means of sub‐reachable and practical stability analysis with sliding mode control. The findings of this study provide a theoretical foundation for further research on vehicle platoons with increasingly complicated interference and time delays. Overall, our results demonstrate that our approach can achieve significant improvements in both fuel economy and exhaust emissions while maintaining high levels of string stability, further contributing to the development of efficient and sustainable transportation systems. [ABSTRACT FROM AUTHOR]

This paper proposes a nonlinear controller strategy for the frequency regulation of a hydraulic turbine regulating system (HTRS). An immersion and invariance (I&I) technique is utilised to develop the desired control law. The derived control method is used to guarantee that the equilibrium point is asymptotically stable. Furthermore, it can ensure that all overall closed-loop system trajectories are bounded. The feasibility and effectiveness of the technique are demonstrated using a nonlinear dynamical system of an HTRS connected to a single-machine infinite bus (SMIB) power system. The simulation results demonstrate that the technique is capable of regulating the frequency and improving dynamic performance despite large disturbances. It is capable of rapidly reducing oscillations and surpasses two known nonlinear controllers, namely the synergetic control and the backstepping control techniques. Additionally, despite the fact that the HTRS's parameters vary, the proposed technique is capable of providing consistent control performance. As a result, the presented controller is insensitive to variations in the system's parameters. [ABSTRACT FROM AUTHOR]

Reinforcement learning is a compelling area of research within machine learning because it enables the improvement of control strategies for future manipulation of dynamic systems, leveraging previous data even without a precise model of the system. It usually makes complex, model-free predictions from data alone, which is actually consistent with the purpose of control in that they both aim to design systems using richly structured perceptions to execute planning and control strategies that adequately adapt to changing environments. The robust trajectory tracking control of intricate mechanical systems presents a challenging problem that necessitates effective control methods. In this paper, we propose a novel nonlinear control strategy based on deep reinforcement learning to solve the trajectory tracking problem of a 3-degree-of-freedom (3-DOF) control moment gyroscope (CMG). First, dynamic modeling of the 3-DOF CMG is used as a policy solver for the reinforcement learning training environment, and transfer learning is employed to bridge the reality gap. Then, the hyperparameters and reward functions of the neural network are optimized using the asynchronous successive halving algorithm. Ultimately, the twin delay depth determination policy gradient algorithm is trained in simulation to yield an agent capable of tracking user-defined trajectory routes as a nonlinear controller for the system. Both simulation and experimental results show that the proposed method works well for both high-frequency and low-frequency varying trajectory tracking control, and that the proposed method has better response speed and robustness than classic linear parameter-varying control methods and the state-of-the-art nonlinear parameter-varying method and the neural network-based feedback linearization adaptive control method. [ABSTRACT FROM AUTHOR]

The large flow rate proportional poppet valve (PPV) finds widespread use in high‐power hydraulic systems. However, the indispensable dead‐zone nonlinearity that guarantees the safe shut‐off of the PPV will cause a tracking lag when a command goes outside the dead‐zone. The lag should be properly solved in a controller, which is a highlight of this study. Simultaneously, achieving high tracking precision in a PPV is necessary to meet the demands of advanced hydraulic systems. In this study, a practical nonlinear controller based on an integral separated disturbance observer is proposed to improve the performance of a PPV. In particular, the lag could be alleviated and the high tracking precision achieved simultaneously by enabling or disabling a disturbance observer in the proposed controller. A separation coefficient is proposed for the disturbance observer to detach the integral action from the controller and avert the deep input saturation of the pilot stage. Additionally, the command filtering technology is applied to the nonlinear controller to improve its interference resisting capacity in the industrial environment. The stability and effectiveness of the proposed controller are proved in theory and verified by experiments. [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]

This paper presents a joint synthesis algorithm of trajectory and controlled invariant funnel (CIF) for locally Lipschitz nonlinear systems subject to bounded disturbances. The CIF synthesis refers to a procedure of computing controlled invariance sets and corresponding feedback gains. In contrast to existing CIF synthesis methods that compute the CIF with a predefined nominal trajectory, our work aims to optimize the nominal trajectory and the CIF jointly to satisfy feasibility conditions without the relaxation of constraints and obtain a more cost‐optimal nominal trajectory. The proposed work has a recursive scheme that mainly optimize trajectory update and funnel update. The trajectory update step optimizes the nominal trajectory while ensuring the feasibility of the CIF. Then, the funnel update step computes the funnel around the nominal trajectory so that the CIF guarantees an invariance property. As a result, with the optimized trajectory and CIF, any resulting trajectory propagated from an initial set by the control law with the computed feedback gain remains within the feasible region around the nominal trajectory under the presence of bounded disturbances. We validate the proposed method via two applications from robotics. [ABSTRACT FROM AUTHOR]

Summary: In this article, we introduce a novel family of Lyapunov‐based adaptive kinematic control laws developed to solve the trajectory tracking problem for a differential‐drive mobile robot under the influence of both longitudinal and lateral wheel slip. Each adaptive controller in this family is constructed by augmenting a nonadaptive nominal controller, originally designed for the slip‐free case, with an update rule capable of estimating the longitudinal slip. In the absence of lateral slip and under constant longitudinal slip, we establish the convergence of the trajectory tracking error to zero and, assuming a persistent excitation condition, we also demonstrate the convergence of the slip estimate error to zero. When lateral slip is present, we analyse a particular control law from our family of adaptive controllers. This law ensures the trajectory tracking error is uniformly ultimately bounded around the origin, demonstrating the robustness of our adaptive control scheme in dealing with time‐varying longitudinal and lateral slip. The validity of our approach is assessed through comprehensive numerical simulations. [ABSTRACT FROM AUTHOR]

The paper presents a new internal model control (IMC) based control technique for lateral trajectory tracking of autonomous vehicles. The controller's proposed structure employs a robust, fault-tolerant nonlinear internal servo control with optimal reference generation concerning vehicle yaw stability and physical limitations. The presented inscription of the reference generation creates a convex optimization task that can be used in real-time applications. Improvements in yaw-rate stability of vehicle motion control are first shown through simulation results performed in a Simulink environment. The controller structure was also implemented in a real-time model and was examined in a Mercedes C-Class vehicle. In this article, the simulation results and the real-time measurements are presented. The results show that the proposed controller has high efficiency in disturbance rejection and lower sensitivity towards parameter changes compared to a model predictive control (MPC) structure. [ABSTRACT FROM AUTHOR]

Active tuned mass damper (ATMD) devices are recommended in various structures to reduce vibrations. The performance of the ATMD system is closely tied to the control design utilized, according to research in the literature. The designed control input will take into account as much system dynamics as possible, making it possible to use it as a generalized controller in all similar systems. Nonlinear behavior is the natural behavior of engineering structures, and in order to obtain a more realistic and high-performance ATMD system, it can be considered as an appropriate approach to design the controller by considering the structural nonlinearities. In addition, unexpected external influences and parameter uncertainties must be taken into account during control design to ensure that control systems perform successfully in similar systems in all conditions. Therefore, in this study, the nonlinear model of the multi-story building was reconstructed by adding nonlinear disturbance to represent unknown external effects. Band-limited white noise is used as a disturbance function and Gaussian white noise is added to measured states in this study. To obtain a robust controller, unknown structural parameters are compensated for by using adaptive compensation terms. With the controller design supported by the Lyapunov-based stability analysis, the stability of the vibrating structure featuring an ATMD is theoretically guaranteed while achieving the main control goal. Performance analyses of the designed controllers are carried out with simulation studies. The efficiency of the developed Lyapunov-based controller in dampening the unwanted vibrations that occurred on the building is seen in simulation results. [ABSTRACT FROM AUTHOR]

Malicious attacks are often inevitable in cyber-physical systems (CPS). Accuracy in Cyber physical system for position tracking of servos is the major concern now a days. In high precision industrial automation, it is very hard to achieve accuracy in tracking especially under malicious cyber-attacks, control saturations, parametric perturbations and external disturbances. In this paper, we have designed a novel predefined time (PDT) convergence sliding mode adaptive controller (PTCSMAC) for such kind of cyber physical control system. Main key feature of our control is to cope these challenges that are posed by CPS systems such as parameter perturbation, control saturation, and cyber-attacks and the whole system then upgrade to a third-order system to facilitate adaptive control law. Then, we present an adaptive controller based on the novel PDT convergent sliding mode surface (SMS) combined with a modified weight updated Extreme Learning Machine (ELM) which is used to approximate the uncertain part of the system. Another significant advantage of our proposed control approach is that it does not require detailed model information, guaranteeing robust performance even when the system model is uncertain. Additionally, our proposed PTCSMAC controller is nonsingular regardless of initial conditions, and is capable of eradicating the possibility of singularity problems, which are frequently a concern in numerous CPS control systems. Finally, we have verified our designed PTCSMAC control law through rigorous simulations on CPS seeker servo positioning system and compared the robustness and performance of different existing techniques. [ABSTRACT FROM AUTHOR]

This study introduces a novel framework for optimizing energy efficiency and computational load in safety-critical robotic systems operating in nonlinear domains. Leveraging Graph Attention Networks for state awareness and decision-making, the framework employs adaptive sensor and filter toggling strategies to dynamically manage system resources through real-time inferential processes. Our framework maintains continuous robot operation in the presence of sensor noise and environmental disturbances by activating additional sensors, thus preventing system shutdowns or stalls. Few-shot meta-learning techniques further augment the model's adaptability, allowing it to generalize and make real-time decisions across varying operational conditions. An extensive evaluation reveals a reduced average energy consumption, compared to 'always-on' configurations, by 13.71% and CPU utilization by 29.07%, without compromising system performance and safety. We also introduce Matching Networks and Siamese Networks with different loss functions to assess the system's capability to adapt to different levels of criticality. Our experiments demonstrate that the system prioritizes performance and safety in high-critical scenarios while maximizing energy efficiency in less critical situations. The framework's real-time decision-making capability is particularly crucial in human–robot environments and holds significant implications for future applications in nonlinear control systems and resilient robotic systems. [ABSTRACT FROM AUTHOR]

Most applications of automatic differentiation concern the field of optimization in the broadest sense. This means that many applications only need first and second order derivatives. An exception are control engineering problems, where higher order derivatives are required. This contribution addresses a control engineering problem, namely the estimation of variables that are not measured directly. This problem can be solved with high gain observers and high gain differentiators. They are typically calculated symbolically. We show how automatic differentiation can be used for the implementation of high gain differentiators. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach for regulating the pose of a free-flying dual-arm anthropomorphic space manipulator system (SMS) using a finite-time state-dependent Riccati equation (SDRE) controller. The proposed system finds applications in on-orbit satellite inspection, servicing, space structure assembly, and debris manipulation. The dual-arm SMS presented in this work consists of two 7 degrees of freedom (DoF) robotic arms mounted on a free-flying spacecraft, resulting in a complex 20-DoF system. Due to the high number of DoFs, advanced controller design and efficient computations are necessary. The finite-time SDRE controller relies on the state-dependent coefficient (SDC) parameterization matrices, which are nonlinear apparent linearizations of the dynamics. Conventionally, the computation of SDC matrices is offline and relies on the a priori derivation of the analytical equations governing the dynamics of the system. However, this strategy becomes computationally impractical for high DoF plants. To overcome this issue and deliver a more viable solution, a numerical method to construct and update the SDC matrices at each time step is presented. This approach relies on a screw-theory-based recursive Newton–Euler algorithm designed to reconstruct the manipulator inertia and Coriolis matrices. These quantities are the building blocks of the SDC parameters used in the synthesis of the SDRE controller. Simulation results demonstrate the performances of the finite-time SDRE controller augmented with the online update of the state-dependent coefficients. • Automatic derivation of the dynamics of free-flying robot with multiple open chains. • Implementation of a Newton-Euler approach for updating state-dependent coefficients. • Finite-time SDRE to control a 20 DoFs, anthropomorphic dual-arm space manipulator. [ABSTRACT FROM AUTHOR]

The paper addresses the exact linearisation of flat nonlinear discrete-time systems by generalised static or dynamic feedbacks which may also depend on forward-shifts of the new input. We first investigate the question which forward-shifts of a given flat output can be chosen in principle as a new input, and subsequently how to actually introduce the new input by a suitable feedback. With respect to the choice of a feasible input, easily verifiable conditions are derived. Introducing such a new input requires a feedback which may in general depend not only on this new input itself but also on its forward-shifts. This is similar to the continuous-time case, where feedbacks which depend on time derivatives of the closed-loop input – and in particular quasi-static ones – have already been used successfully for the exact linearisation of flat systems since the nineties of the last century. For systems with a flat output that does not depend on forward-shifts of the input, it is shown how to systematically construct a new input such that the total number of the corresponding forward-shifts of the flat output is minimal. Furthermore, it is shown that in this case the calculation of a linearising feedback is particularly simple, and the subsequent design of a discrete-time flatness-based tracking control is discussed. The presented theory is illustrated by the discretised models of a wheeled mobile robot and a 3DOF helicopter. [ABSTRACT FROM AUTHOR]

This study focuses primarily on sulfur dioxide (SO2) emissions control problem in a wet flue gas desulfurization (WFGD) process, and our objective is to design an intelligent control system so that the outlet SO2 concentration satisfies the SO2 emission standard. In our approach, a multimodel control framework, which is made up of a linear robust controller and a neural controller, is integrated with the invasive weed optimization (IWO) algorithm in an elegant fashion and used for SO2 emissions control purposes. A case study is carried out based on operation data from a 600 MW coal-fired unit, and simulation results show that IWO-based automatic clustering can identify different operating modes in the WFGD process with high accuracy. Further, the established multimodel control system can remove SO2 emissions effectively. Experimental results show that SO2 emissions can be removed effectively with the proposed method, and this could provide engineering guidance to design a WFGD control system. [ABSTRACT FROM AUTHOR]

For the speed-tracking control of permanent magnet synchronous motor (PMSM) systems, fast dynamic response and high reference speed require a large transient current to provide sufficient electromagnetic torque. However, the excessive transient current may damage the drive circuit and threaten the system safety. Besides, it is also important to pay attention to the influence of multiple disturbances including system parameter uncertainties and unknown load torque variation. To solve these problems, we propose a nonlinear speed-tracking control approach for uncertain PMSM systems. More specifically, based on the cascade control structure and by introducing auxiliary smooth function, we first develop a nonlinear current-constrained controller (CCC) to guarantee the speed tracking, disturbance rejection, and overcurrent protection simultaneously. In order to improve the robustness of the desired performances, we further implement extended state observer (ESO) techniques to propose an ESO-based CCC (ESO-CCC). Finally, comparative experiments are implemented in a 5.5 kW PMSM platform to verify the performance of the proposed two controllers. [ABSTRACT FROM AUTHOR]

This paper presents a hierarchical critic learning optimal control (H‐CLOC) strategy for a lower limb exoskeleton system with prescribed state constraints. The prescribed state constraints of the exoskeleton are mathematically modeled by means of a state error transition function, which transforms the constrained state into an equivalent new unconstrained state. A hierarchical framework including a high‐level motion trajectory planner and a low‐level critic learning (CL) controller is proposed for optimal control of the exoskeleton. The estimation of human motion intentions is achieved using dynamic movement primitives (DMPs), which are capable of accurately replicating the original training trajectories during motion. The CL algorithm is implemented on the transformed unconstrained system while enhancing the learning capability of the proposed algorithm for the exoskeleton. The optimal control with prescribed constraints is analyzed for stability using the Lyapunov theorem. Finally, simulation results validate the effectiveness of the proposed H‐CLOC strategy for lower limb exoskeletons. [ABSTRACT FROM AUTHOR]

The adaptive predefined settling time performance tracking control for a class of uncertain nonlinear network systems with fast time-varying or even abrupt reference signals is studied. In this paper, an improved performance function with time-varying boundary (following the change of reference signal) is designed to overcome the problem that the traditional prescribed performance control (PPC) can only converge to a constant in steady state. Compared with the existing adaptive finite time prescribed performance congestion control for tracking fixed value reference signals, an adaptive predefined settling time prescribed performance congestion control strategy is proposed by means of some new recursive construction (introducing nonautonomous differential equations (NDE)) and analysis innovation. In addition, the network system considered in this paper is more general. Under the framework of backstepping, NDE is used iteratively to control the approximation error with boundary inequality. It is proved theoretically that all signals of the closed-loop system are predefined settling time bounded. Finally, the effectiveness of the proposed control strategy is verified by simulations. [ABSTRACT FROM AUTHOR]

Fractional calculus is defined by expanded integer order integration and differentiation. In this paper, multiple mathematical models of a nonlinear dual-tank device are precisely formulated by fractional calculus. Using the accurate model, a multivariable fractional-order controller is designed for nonlinear devices. The merits of the fractional-order design include: (1) control of multivariable nonlinearities, (2) compensation of uncertainties, and (3) elimination of coupling effects. Simulations and experiments are conducted to verify the precision of the fractional order models and the effectiveness of the multivariable fractional-order control system design. [ABSTRACT FROM AUTHOR]

Anti-disturbance vibration control is a crucial component in a hydraulic suspension system. However, random input excitation and prolonged service can cause hydraulic suspension system parameters to drift, leading to system vibration with suppression failure. The resulting states of nonlinearity and disturbance will lead to a gradual deterioration of pressure control. Therefore, designing a viable controller for a hydraulic suspension system that considers system nonlinearity, computing capacity, and sensor configuration is essential. To address this need, we present a double-layer control strategy in this work. A hybrid sliding mode control algorithm based on the reference skyhook and groundhook model is proposed to regulate the expected force of reverse compensation. An output controller is then applied based on the expected force observer to mitigate low-frequency vibrations to realize a steady state. A logic rule is designed to ensure that the two controllers work to suppress sprung mass vibration, and a comprehensive system model is derived to help characterize system nonlinearities and design the hybrid sliding model controller. Numerical and physical validations are then carried out to demonstrate the feasibility of the strategy and test the performance of the controller. The experimental results show that the hybrid sliding mode controller can suppress vibration under disturbance excitation and reduce the vibration acceleration to a 2.3 m/s2 random response when system parameters vary. [ABSTRACT FROM AUTHOR]

This article proposes a control method for underactuated cartpole systems using semi-implicit cascaded proportional-derivative (PD) controller. The proposed controller is composed of two conventional PD controllers, which stabilizes the pole and the cart second-order dynamics respectively. The first PD controller is realized by transforming the pole dynamics into a virtual PD controller, with the coupling term exploited as the internal tracking target for the cart dynamics. Then, the second PD controller manipulates the cart dynamics to track that internal target. The solution to the internal tracking target relies on an equation set and features a semi-implicit process, which exploits the internal dynamics of the system. Besides, the design of second PD controller relies on the parameters of the first PD controller in a cascaded manner. A stability analysis approach based on Jacobian matrix is proposed and implemented for this fourth-order system. The proposed method is simple in design and intuitive to comprehend. The simulation results illustrate the superiority of proposed method compared with conventional double-loop PD controller in terms of convergence, with the theoretical conclusion of at least locally asymptotic stability. [ABSTRACT FROM AUTHOR]

The main focus of this study is the minimization of Permanent Magnet Synchronous Motors (PMSM) steady-state speed error. In order to do this, a Lyapunov candidate function that contained the speed error is defined and a Based Lyapunov Theory (BLT) speed controller is designed. The novelty of this paper is the smoother pre-filter applied to the reference speed guarantees the stable operation of the nonlinear controller at step change in reference signal. The pre-filter design is carried out in a way that does not have a negative effect on the settling time, which is one of the step response characteristics. A proportional-integral (PI) speed controller is designed for comparison. FOC technique is used for inverter control. As the speed controller of the system, PI and BLT controllers are designed separately. Simulation studies are run in MATLAB/Simulink. PI speed controller coefficients are determined using the pole assignment method. For this purpose, PI coefficients for operating the controller at the selected frequency and the desired damping ratio are calculated. Stability analyses are carried out for PI and BLT speed controllers. A low pass filter that allows the system to apply a smoothed reference speed is designed in order to eliminate the range in which the derivative of the reference speed used in the BLT speed controller is undefined. Three different simulations are modeled. In the first one, the reference speed is changed in both directions by step function, under constant load torque. The speed and torque performances of both speed controllers are compared with the performance criteria including settling time, overshoot, peak value, peak time, root mean squared error (RMSE), and integral of time weighed absolute error (ITAE), and the results of the comparison are shown in figures and tables. In addition, a second simulation including reference load changes is made to model load torque disturbance as a robustness test, and a third simulation containing resistance changes is made to model parameter uncertainty are carried out. Both transient response and steady state response of controllers against parameter changes are examined in simulation 2 and 3. With the proposed BLT controller, the transient and steady-state response of the speed is improved both at the time of torque change and at the time of winding resistance change. The results are given in figures and tables. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive controller is presented to control a quadrotor, whose parameters are extracted from the genetic algorithm optimization method. The advantage of this method is that based on the system states, the control coefficients are calculated online. For this purpose, a function between system states-space and control coefficients is obtained. From the database collected from the genetic algorithm optimization method, the parameters of the control coefficient function are obtained using the least squares method. The stability of the proposed controller is proved by the Lyapunov method. Finally, the performance of the proposed controller is compared with the PID controller, which is widely used in the literature. The results show that the proposed approach is promising. [ABSTRACT FROM AUTHOR]

This paper introduces a method to navigate the tower crane movement and suppress the payload swing synchronously. Special error signals are introduced, which bring the coupling of dynamics among various states of the crane and enable the control to meet the synchronous operation in practice. The special angle-dependent energy functions are designed as the candidate sub-Lyapunov functions for decoupling the states. The controller is then stepwise designed with the help of the dynamics model. The stability of the control is proven in the Lyapunov sense. Extensive simulations and experiments have been carried out to demonstrate the effectiveness of the proposed nonlinear coupling control. A popular control approach in the literature is chosen to compare with the current work. It is found that the proposed control is quite effective in suppressing the payload swing while tracking the pre-determined path at the same time. [ABSTRACT FROM AUTHOR]

This article designs a novel controller for heterogeneous connected vehicles (CVs) platoon subject to communication delay. Firstly, third-order vehicle dynamics is used to capture the heterogeneity of vehicles. A new nonlinear controller for the CV platoon is proposed in the presence of car-following interactions, the acceleration difference and communication delays. Then, the internal stability of the CV platoon and the upper bound of communication delay are deduced by using the Lyapunov theorem. Also, the string stability of the linearized CV platoon system is proved by using the infinite-norm method. Additionally, a hierarchical control strategy suitable for co-simulation is designed to overcome the nonlinearity of vehicles and achieve consistency between the desired and actual acceleration. Finally, the superiority and effectiveness of the developed controller are verified by extensive simulation and cosimulation. [ABSTRACT FROM AUTHOR]

A reinforcement learning‐based adaptive consensus control method has been proposed for the non‐affine nonlinear multiagent systems with semi‐Markov switching topographies in this paper. The considered system contains the nonlinear features, multiple source disturbances and non‐affine inputs, which makes it difficult to design the consensus controller. Firstly, to overcome the adverse influence caused by the multiple disturbances existing in the nonlinear system, a reinforcement learning based adaptive disturbance observer has been designed. Secondly, to handle the unknown nonlinear terms and the non‐affine features of the control inputs, an auxiliary loop has been introduced and a reinforcement learning based adaptive control law has been designed. Finally, aiming at the semi‐Markov switching topographies possessed by the multiagent systems, a novel adaptive consensus controller integrating the reinforcement learning approximator, the adaptive disturbance observer and the consensus control law, has been proposed. Through the Lyapunov direct method, it has been proven that the tracking errors are ultimately uniformly bounded. Moreover, within an acceptable margin of error, the state of all the followers can proved to be consistent with the leader. Several numerical experiments are conducted to illustrate the feasibility and effectiveness of the proposed reinforcement learning‐based leader‐following consensus control law. [ABSTRACT FROM AUTHOR]

In a photovoltaic permanent magnet synchronous motor pumping system (PVPMSM), both photovoltaic modules and switching-mode converters present nonlinear and time-variant characteristics, which result in a difficult control problem. This paper presents an in-depth analysis of the operating point dynamics. A potential trade-off exists between maximum power and stability of the system operating point. Analysis of parametric singularities based on bifurcation theory permits to optimize the maximum power-stability trade-off. Tracing the bifurcation structures related to the parameter set (T, G), we can determine the maximum power point(MPP) in midway and far enough from the bifurcation points from these structures. An algorithm aiming to determine the MPP within the range of stability through power bifurcation analysis is proposed in this paper. Our methodology was validated with the simulation that was carried out on MATCONT/MATLAB, and the results are demonstrated. [ABSTRACT FROM AUTHOR]

Hybrid quad‐plane unmanned aerial vehicles (UAVs), which combine the advantages of multicopters and fixed‐wing UAVs, are gaining increasing attention. However, quad‐planes are characterized by complex structures, high nonlinearity, strong coupling, and three flight regimes (hover, transition, and fixed‐wing flight), which bring great challenges to the research of their control laws. This article aims to design control laws for a quad‐plane in fixed‐wing and hover flight regimes based on a robust nonlinear control method, incremental nonlinear dynamic inversion (INDI), so that the quad‐plane can follow a given path autonomously. Firstly, a mathematical model of the quad‐plane is established on the basis of kinematics and dynamics. Subsequently, cascade control structures are proposed and divided into inner and outer loops. A control law is designed for each control loop based on INDI. To improve the performance of the designed control law, reference models are added to the inner loops to shape the input commands and provide feedforward inputs. Finally, simulation results corroborate the performance and robustness of the proposed control law. Compared with the control law designed by active disturbance rejection control and proportional‐integral‐derivative control methods, the INDI‐based control law is more robust. [ABSTRACT FROM AUTHOR]

This paper presents a control solution for the problem of slung load transportation, with simultaneous damping of oscillations, using an underactuated autonomous quadrotor vehicle in the presence of external disturbances. The strategy put forward is divided into two parts: (i) resorting to an error definition that encompasses the pendular motion of the suspended load, a controller inspired in sliding‐mode theory is developed to compute a vectored thrust actuation that actively damps out the system's oscillations; (ii) two different approaches are illustrated for the stage of attitude tracking: one stemming from the conventional backstepping technique, which controls the vehicle in angular velocity commands; and another, also based on sliding‐mode theory, and built intrinsically in SO(3)$$ \mathsf{SO}(3) $$, that produces torque commands. The overall control scheme is proved to be robust and stable, with the load oscillations shown to be damped out in the process. Simulation and experimental results are presented in a trajectory tracking scenario to validate and assess the robustness and efficiency of the proposed technique. [ABSTRACT FROM AUTHOR]

A multirotor unmanned aerial vehicle (UAV) slung load system (SLS) is a nonlinear dynamics with eight degrees of freedom and four inputs that can be used for load transportation. The suspended payload can be modelled as a two degree-of-freedom pendulum attached to the UAV. This paper presents a path-following control (PFC) for an SLS. The PFC renders motions along any smooth Jordan curve in $ {\mathbb R}^3 $ R3 for payload position controlled-invariant. This property has practical benefits over traditional time-based trajectory tracking. Furthermore, the PFC prescribes UAV yaw and a desired payload speed profiles along the path. The PFC adopts dynamic extension and input-output state feedback linearisation. The closed-loop has a 1-dimensional zero-dynamics which is shown to be bounded. Hence, the PFC error dynamics is exponentially stable. Simulations are provided to validate the design. [ABSTRACT FROM AUTHOR]

Synchronization of hypernetworks has been extensively researched due to its potential applications in various contexts, such as secure communications and power grid engineering. However, the existing works thus far have primarily been devoted to inner synchronization or complete outer synchronization with identical node dynamics and topology structures. To investigate harmonious coexistence between two networks with nonidentical node dynamics and reduce control costs as well, this paper focuses on generalized outer synchronization (GOS) and parameters identification of uncertain delayed hypernetworks with stochastic noises. Regardless of whether the node parameters are known or not, based on Lyapunov stability and the LaSalle‐type invariance principle for stochastic differential equations with multiple delays, some sufficient conditions are exhibited to reach GOS almost surely via adaptive control schemes. Moreover, the unknown node parameter vectors are identified by the designed updating laws. In addition, some corollaries are deduced and indicate that our proposed methods contain single‐layer networks and complete synchronization methods as special cases. Furthermore, numerical simulations are provided to verify the effectiveness of our approaches. In particular, it is revealed that network parameters, including time delays, coupling strengths, and noise intensities, have an impact on the performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

High-speed rotors on gas foil bearings (GFBs) are applications of increasing interest due to their potential to increase the power-toweight ratio in machines and also formulate oil-free design solutions. The gas lubrication principles render lower (compared to oil) power loss and increase the threshold speed of instability in rotating systems. However, self-excited oscillations may still occur at circumferential speeds similar to those in oil-lubricated journal bearings. These oscillations are usually triggered through Hopf bifurcation of a fixed-point equilibrium (balanced rotor) or secondary Hopf bifurcation of periodic limit cycles (unbalanced rotor). In this work, an active gas foil bearing (AGFB) is presented as a novel configuration including several piezoelectric actuators that shape the foil through feedback control. A finite element model for the thin foil mounted in some piezoelectric actuators (PZTs), is developed. Second, the gas-structure interaction is modelled through the Reynolds equation for compressible flow. A simple physical model of a rotating system consisting of a rigid rotor and two identical gas foil bearings is then defined, and the dynamic system is composed with its unique source of nonlinearity to be the impedance forces from the gas to the rotor and the foil. The third milestone includes a linear feedback control scheme to stabilize (pole placement) the dynamic system, linearized around a speed-dependent equilibrium (balanced rotor). Further to that, linear feedback control is applied in the dynamic system utilizing polynomial feedback functions in order to overcome the problem of instability. [ABSTRACT FROM AUTHOR]

This paper proposes a novel distributed controller that solves the leader-follower and the leaderless consensus problems in the task space for networks composed of robots that can be kinematically and dynamically different (heterogeneous). In the leader-follower scenario, the controller ensures that all the robots in the network asymptotically reach a given leader pose (position and orientation), provided that at least one follower robot has access to the leader pose. In the leaderless problem, the robots asymptotically reach an agreement pose. The proposed controller is robust to variable time-delays in the communication channel and does not rely on velocity measurements. The controller is dynamic, it cancels-out the gravity effects and it incorporates a proportional to the error term between the robot and the controller virtual position. The controller dynamics consists of a simple proportional scheme plus damping injection through a second-order (virtual) system. The proposed approach employs the singularity free unit-quaternions to represent the orientation of the end-effectors, and the network is represented by an undirected and connected interconnection graph. The application to the control of bilateral teleoperators is described as a special case of the leaderless consensus solution. The paper presents numerical simulations with a network composed of four 6-Degrees-of-Freedom (DoF) and one 7-DoF robot manipulators. Moreover, we also report some experiments with a 6-DoF industrial robot and two 3-DoF haptic devices. [ABSTRACT FROM AUTHOR]

We consider the problem of tracking arbitrary free nutating trajectories of the Lagrange top using linear feedback. The equations of motion of the top are linearised about the desired trajectories. Due to the inherent symmetries, this yields a system of linear equations with periodically varying coefficients governing the error dynamics. It is shown that the higher-order dynamics of the Lagrange top leads to nuances in the implementation of the control. Two different control strategies are implemented in the present work. These are applicable for impulsive and short-duration disturbances, respectively. The control effort is in the form of a body-fixed torque input about the symmetry axis and a vertical space-fixed force input. In both the proposed control strategies, the iterative application of the control effort over multiple periods is shown to stabilise the error. These strategies are shown to work for significantly large errors. [ABSTRACT FROM AUTHOR]

In this paper, a dc–dc boost converter with continuous input is investigated. In addition to its input current, the converter offers the advantage of using a reduced number of electronic components. The objective is to design an appropriate controller for the nonlinear model taking into account the system nonlinearities, the uncertainty of the resistance load, the constrained fuel cell current, and the saturation of the control input signal (duty ratio).The point is that the converter presents a no minimum phase feature, and the duty ratio must constrain between 0 and 1. Then, a saturated nonlinear controller is elaborated. Detailed analysis and simulation show that the proposed controller meets all control objectives, namely: tight dc-bus voltage regulation and asymptotic stability of the closed-loop system. Experimental results are also given, which show the effectiveness of the controller. [ABSTRACT FROM AUTHOR]

In this paper we present a novel VTOL aircraft design which evolves from our previous work on passively coupled systems. This can be seen as an improvement over our previous drone topology since the present one allows the main hub of the drone to assume any arbitrary orientation, while the center of mass of the main hub is stabilized at a desired point. This design manages to decouple the movement of the center of mass by the movement of the orientation. Therefore the reference for the center of mass of the main hub is independent by the reference for the orientation of the main hub at any point of the trajectory. We derive in detail the full nonlinear model using D'Alembert's principle and propose a fully nonlinear control techniques composed of two cascaded controllers. The inner loop controller performs an additional optimization step to assign commands to eight rotors such that six variables are fully controlled. The outer loop controller upon solving a nonlinear algebraic equation provides the required references to the inner loop controller such that a six degrees of freedom reference (trajectory of the c.o.m and attitude of main body) is followed with vanishing error. Simulations of the mathematical model as well the proposed control law for different types of trajectories are also presented. [ABSTRACT FROM AUTHOR]

Photovoltaic panels present an economical and environmentally friendly renewable energy solution, with advantages such as emission-free operation, low maintenance, and noiseless performance. However, their nonlinear power-voltage curves necessitate efficient operation at the Maximum Power Point (MPP). Various techniques, including Hill Climb algorithms, are commonly employed in the industry due to their simplicity and ease of implementation. Nonetheless, intelligent approaches like Particle Swarm Optimization (PSO) offer enhanced accuracy in tracking efficiency with reduced oscillations. The PSO algorithm, inspired by collective intelligence and animal swarm behavior, stands out as a promising solution due to its efficiency and ease of integration, relying only on standard current and voltage sensors commonly found in these systems, not like most intelligent techniques, which require additional modeling or sensoring, significantly increasing the cost of the installation. The primary contribution of this study lies in the implementation and validation of an advanced control system based on the PSO algorithm for real-time Maximum Power Point Tracking (MPPT) in a commercial photovoltaic system to assess its viability by testing it against the industry-standard controller, Perturbation and Observation (P&O), to highlight its advantages and limitations. Through rigorous experiments and comparisons with other methods, the proposed PSO-based control system's performance and feasibility have been thoroughly evaluated. A sensitivity analysis of the algorithm's search dynamics parameters has been conducted to identify the most effective combination for optimal real-time tracking. Notably, experimental comparisons with the P&O algorithm have revealed the PSO algorithm's remarkable ability to significantly reduce settling time up to threefold under similar conditions, resulting in a substantial decrease in energy losses during transient states from 31.96% with P&O to 9.72% with PSO. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive observer for an active leader and designed a distributed observer‐based control law for the formation control of networked uncertain offshore vessels under the switching topologies. The design of the observer, only depending on the output of the leader system, is featured with the ability of accurately estimating the output of the leader system with an unknown input over the time‐varying communication network, satisfying the periodic switching condition. Then based on the output‐based observer, the formation problem of multiple offshore vessels is converted into the stabilization problem of a multi‐input multi‐output augmented system by further combining the internal model technique and performing a coordinate and input transformation. The original problem is finally solved through constructing a stabilizer for the time‐varying uncertain augmented system, and the efficiency of our design is validated by the formation control of a group of offshore vessels. [ABSTRACT FROM AUTHOR]

A methodology is presented for the design and implementation of robust controllers that optimise inter-sample performance for a broad range of nonlinear systems operated within a sampled-data environment. The methodology applies to nonlinear continuous-time systems described by state equations, and it allows for modelling uncertainties and constraints on maximal control effort. It is shown that there exist optimal robust state-feedback controllers that minimise inter-sample tracking errors for such systems, as long as an appropriate controllability requirement is met. A relatively simple design and implementation procedure for such controllers is described. [ABSTRACT FROM AUTHOR]

The present paper introduces the formulation and development of a bilinear quadratic control algorithm for Modular Multilevel Converter (MMCs), with a specific emphasis on achieving internal energy stabilization and balance within the converter. A bilinear average model of the MMC is employed, enabling the separation between the DC voltage and the voltage generated by submodules. The algorithm proposed in this study is formulated using bilinear theory and is founded on quadratic feedback control principles. The stability of the suggested controller is scrutinized using a meticulous mathematical approach based on Lyapunov theory. Subsequently, the theoretical findings are assessed using a comprehensive MMC switching model implemented in Matlab Simscape Electrical. The utilization of a phase-shift PWM technique, accompanied by a sorting algorithm, is considered in the study. Additionally, a comparison between the proposed bilinear controller and a standard PI controller is conducted. The outcomes demonstrate that the proposed controller effectively facilitates the regulation of circulating and AC currents, along with managing the internal energy of MMCs. Consequently, this achievement makes a noteworthy contribution to the field, as it introduces an innovative bilinear control approach capable of stabilizing all the state variables of MMCs converters using a single control law. [ABSTRACT FROM AUTHOR]

This paper addresses the design of a robust nonlinear dynamic controller for a wind turbine. The turbine is equipped with a permanent magnet synchronous generator. The control problem involves tracking a suitable reference value for the turbine's angular velocity, which corresponds to the wind speed. This issue is tackled by compensating for variations in the electrical and mechanical parameters present in the mathematical model. Additionally, the problem is approached under the assumption that wind speed cannot be directly measured, a fact verified in practical scenarios. This situation is particularly relevant for real-world applications, where only nominal parameter values are accessible and accurate wind speed measurement is challenging due to disturbances caused by the turbine or other factors, despite the use of appropriate sensors. To achieve precise tracking of the angular velocity reference, effective compensation of perturbation terms arising from parameter uncertainties and errors in wind estimation becomes crucial. To address this problem, a wind velocity estimator is employed in conjunction with high-order sliding mode parameter estimators, ensuring the turbine's operation attains a high level of performance. [ABSTRACT FROM AUTHOR]

This paper introduces a simple decentralized sliding-mode (SM) approach to control active power sharing by regulating the local frequency in inverter-based islanded microgrids (MGs). Its sliding surface arises from the frequency correction term introduced in the droop-free technique; it relates local active power to neighboring MGs' active power by considering available communications among voltage source inverters. Then, this schema allows one to avoid hierarchical control just as the droop-free method does, and the benefits associated are twofold. First, it reduces the steady-state frequency error while providing accurate active power distribution. Second, the system stays reliable, withstands uncertainties, and provides a fast transient response. A Lyapunov analysis confirms stability, and simulations on a realistic four-inverter MG platform substantiate the control scheme's effectiveness. Its performance regards frequency regulation while achieving active power sharing, stability, and robustness against clock drifts and load steps. [ABSTRACT FROM AUTHOR]

In airworthiness verification flight test on fire smoke detection systems in aircraft cargo compartments, simulated smoke from a smoke generator that can replicate the characteristics of actual fire smoke should be used. In current studies, most of the boundary conditions of smoke generators are adjusted by open-loop control to fulfill the equivalence of the actual fire smoke. However, this method consumes a large amount of resources and has difficulty achieving optimal results from the complex turbulent flow field of smoke in an aircraft cargo compartment. To solve this problem, a computational fluid dynamics (CFD) model was first established to simulate smoke in the full-scale cargo compartment mock-up. Then, a state-space model with the exit parameters of the smoke generator as the input and the smoke concentration in the full-scale cargo compartment mock-up as the state variable was constructed using the data generated by the CFD model. Subsequently, a closed-loop simulated smoke concentration control strategy is proposed. In this strategy, the sensor in the full-scale cargo compartment mock-up collects the simulated smoke concentration signal and feeds it back to the controller. The controller processes the control target and feedback signal in real time. It realizes the automatic closed-loop control of the simulated smoke concentration by automatically adjusting the boundary condition parameters of the smoke generator. In the control law design, the control input constraint and the error between the linear state-space model and the real flow are considered, making the linear state-space model a nonlinear model. Finally, we prove the stability of the control system. The simulation shows that the designed control law can realize the closed-loop control of smoke concentration. The findings of this study can expand the control of simulated smoke flow field in airworthiness verification flight test from open loop to closed loop, and offer a new theoretical approach for smoke simulation technology. [ABSTRACT FROM AUTHOR]

Position control algorithms can be classified into two groups: point-to-point control and continuous path control. For point-to-point control implemented in programmable logic controllers, the speed setpoint is mostly the only setpoint transmitted to the industrial converter. Incorrect settings of the position controller in PLC may lead to position overshoot or oscillations, which are unacceptable in position control applications. The speed control structure in the industrial converter usually has a fixed structure which does not allow the implementation of advanced speed controller. Moreover, standard library blocks for position control encounter difficulties in diagnostics and tuning. To address these limitations, this paper proposes a novel solution for position control that achieves time-optimal speed trajectory during acceleration and enhanced capabilities during deceleration. The proposed controller was verified by simulations of positioning of zinc ingot feeder unit drive and compared with a standard P-controller. Experimental results confirmed the performance of the proposed controller with the industrial application of a feeder unit. [ABSTRACT FROM AUTHOR]

Nowadays, integrating renewable energy sources, such as tidal power, into the existing power grids of turbines is crucial for sustainable energy generation. However, tidal turbine energy transforms the potential energy of moving water into electrical energy. When both nonlinear load and dynamic load harmonics are present, the tide speed variance causes serious power quality issues such as low power factor, unstable voltage, harmonic distortions, frequency fluctuations, and voltage sags. The integration of an LCL-filter-based connection scheme can address these challenges by improving power quality and the overall performance of the tidal current turbine grid system. This study shifts LCL filter research from its conventional wind energy emphasis to the emerging field of tidal stream generation systems. The LCL filter analysed in this paper is modelled to exhibit adequate mechanical, electrical, and hydrodynamic characteristics. This model accounts for tidal current variations, turbine speed control, and power extraction dynamics. The LCL filter is evaluated for its effectiveness in reducing harmonic distortions, voltage fluctuations, and reactive power fluctuations. This system is composed of a 1.5 MW/C, a 1.2 MW three-level inverter with a nominal voltage of 600 V, and an inductance (LCL) filter. The results show that the inverter produces a harmonic distortion of less than 0.5%, which demonstrates the effectiveness of the filter in improving total harmonic distortion, reactive power consumption, and voltage control. [ABSTRACT FROM AUTHOR]

A finite‐time suboptimal control strategy named θ−D$$ \theta -D $$ technique is proposed for the control of a class of control‐affine nonlinear dynamic systems in this study. The nonlinear dynamic is expressed as a pseudo‐linear form without linearization. By adding vanishing perturbation terms into the quadratic cost functional and using a power series to represent the co‐state, an approximate solution to the Hamilton–Jacobi–Bellman (HJB) equation can be obtained through solving a differential Riccati equation offline and a series of linear Lyapunov equations with analytical solutions. The obtained suboptimal controller is in a state feedback closed‐form. By tuning the parameters in the perturbation terms, semi‐global stability can be guaranteed. In contrast to the finite‐time state‐dependent Riccati equation technique, the proposed method does not need intensive and iterative numerical computations, which facilitates real‐time implementation. Two examples are utilized to demonstrate the effectiveness and efficiency of this proposed technique. [ABSTRACT FROM AUTHOR]

The Enhanced Model Reference Adaptive Control (EMRAC) algorithm, augmenting the MRAC strategy with adaptive integral and adaptive switching control actions, is an effective solution to impose reference dynamics to plants affected by parameter uncertainties, unmodeled dynamics and disturbances. However, the design of the EMRAC solutions has so far been limited to single‐input systems. To cover the gap, this paper presents two extensions of EMRAC to multi‐input systems. The adaptive mechanism of both solutions includes the σ$$ \sigma $$‐modification strategy to assure the boundedness of the adaptive gains also in presence of persistent disturbances. The closed‐loop system is analytically studied, and conditions for the asymptotic convergence of the tracking error are presented. Furthermore, when the plant is subjected to unmatched disturbances, the ultimate boundedness of the closed‐loop dynamics, which are made discontinuous by the adaptive switching control actions, is systematically proven by using Lyapunov theory for Filippov systems. The problem of trajectory tracking for space robotic arms in presence of unknown and noncooperative targets is used to test the effectiveness of the novel multi‐input EMRAC algorithms for taming uncertain systems. Four EMRAC solutions are designed for this engineering application, and tested within a high fidelity simulation framework based on the Robot Operating System. Finally, the tracking performance of the EMRAC implementations is quantitatively evaluated via a set of key performance indicators in the joint space and operational space, and compared with that of four benchmarking controllers. [ABSTRACT FROM AUTHOR]