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In this research, we explore a finite horizon optimal stabilization and tracking control scheme for the dynamical model of a 6‐DOF Autonomous Underwater Vehicle (AUV). Dynamical equations of the AUV are represented in a Lie group (SE(3)$$ SE(3) $$) framework, encompassing both translational and rotational motions. Utilizing a left Lie group action on SE(3)$$ SE(3) $$, we define error function for velocities via a right transport map to effectively address optimal trajectory tracking. The optimal control objective is formulated as a trade‐off problem, aiming to minimize both errors and control effort simultaneously. Left action on SE(3)$$ SE(3) $$ yields the left trivialized Hamiltonian function from which the concomitant state and costate dynamical equations are derived using Pontryagin's Minimum Principle (PMP). Consequently, the resulting two‐point boundary value problem is solved to obtain optimal trajectories. We demonstrate the optimality of the resulting solution obtained from the derived control law. For ensuring boundedness in the presence of small disturbances, this study incorporates the effects of internal parametric uncertainties associated with added mass and inertia components, along with the influence of external disturbances induced by ocean currents. Through simulation validations, we confirm the alignment of our results with the theoretical developments, demonstrating that the proposed control law effectively mitigates both parametric uncertainties and ocean current disturbances. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach for linear quadratic optimal control design for a nonlinear control structure based on a feedback linearization method and applied over permanent magnet synchronous motor (PMSM). The design of the proposed approach is developed by considering rotational speed, direct and quadrature currents as state variables. To achieve accurate tracking of the desired rotational speed, an additional nonlinear controller with integral action is implemented, also employing the exact feedback linearization method, and since the reference for the quadrature current is selected as zero only regulation is required. Consequently, a multivariable nonlinear controller is achieved using exact feedback linearization, offering robustness against external disturbances like torque load. The proposed method is assessed through simulations on a PMSM motor, and the speed reference tracking performance is analyzed with and without integral action. An additional comparison is carried out by incorporating a pole placement technique into the controller design. The proposed exact feedback linearization approach with integral action and linear quadratic control, demonstrates superior performance over other methods in terms of disturbance rejection, control effort and speed tracking. [ABSTRACT FROM AUTHOR]

This article presents a nonlinear control strategy designed to address parametric uncertainties in an agricultural tractor system coupled to a towed implement. The controller ensures accurate tracking of lateral and yaw velocities relative to desired reference trajectories, even under the presence of parametric variations and external disturbances. The reference trajectories are derived from an "ideal" tractor model, excluding the effects of the towed implement. A High-Order Sliding Mode (HOSM) estimator is employed to provide an estimation of disturbances, which are subsequently mitigated by the controller to maintain system stability and precision. The effectiveness of the proposed control strategy is validated through Matlab-Simulink simulations, which include a double-step steer maneuver. This maneuver tests the system's ability to handle abrupt steering changes, providing insight into the controller's robustness and its capacity to ensure accurate trajectory tracking in demanding conditions. [ABSTRACT FROM AUTHOR]

To a non-minimum phase nonlinear system, it was supposed that, if there is an output feedback control that stabilizes the auxiliary system, then there is an output feedback that stabilizes the original system. The existing methods base designing output feedback for non-minimum phase nonlinear system on the hypothesis that there exists output feedback for auxiliary system. However, the auxiliary system could be unobservable. Alternatively, this study aims to create a way to design output feedback for auxiliary systems in unobservable situation. An output state is constructed in the last equation of auxiliary system, which artificially makes the internal dynamics of the auxiliary system observable. Then, a cascade high-gain observer is designed for the auxiliary system, consisting of an extended high-gain observer for external dynamics and a high-gain observer for internal dynamics of the auxiliary system. Therefore, the output feedback control for auxiliary system can be designed via the cascade high-gain observer and a state feedback. Finally, the proposed method is demonstrated by an academic example and an inverted pendulum on a cart in the simulation. [ABSTRACT FROM AUTHOR]

Reluctance actuators (RA) are a type of electromagnetic actuator that offers high forces for short-range motions. The RA takes advantage of the electromagnetic reluctance force property in air gaps between the stator core and mover parts. The stator generates a magnetic flux that produces a magnetic attraction force between the stator and the mover, where the output force is dependent on the air gap displacement nonlinearly. It is demonstrated that the RA can produce a force that is effective and suitable for millimeter-range high-acceleration applications. One application for the RA is the short-stroke stage of photolithography or lithography machines, for example. The RA is available in a wide variety of configurations, such as C-Core, E-Core, Maxwell, and Plunger-type designs. The RA requires precise dynamic models and control algorithms to help linearize the RA for better control and optimization. Some nonlinear dynamics include magnetic hysteresis, flux fringing, and eddy currents. The RA is shown to have a larger force density than any other traditional actuator designs, with the main disadvantage being the nonlinear and hysteresis nonlinearities, making it difficult to control precision motion applications without proper dynamic and control models in place. This review documents currently available knowledge of the RA such as available applications, configurations, dynamic models, measurement systems, and control systems for the RA. • Provides a consolidated overview of available applications, configurations, dynamic models, measurement systems, and control methodologies for RAs. • Explores the unique electromagnetic properties of RAs for high-force, short- range motions. • Discusses various RA configurations and their suitability for different applications. • Addresses challenges posed by nonlinearities such as magnetic hysteresis, flux fringing, and eddy currents. • Emphasizes the importance of precise dynamic models and control algorithms for linearizing and optimizing RA performance. [ABSTRACT FROM AUTHOR]

A drag sail is a propellantless device suitable for passive deorbiting of satellites after their end-of-life. It exploits atmospheric drag to gradually reduce the kinetic energy of the decommissioned satellite and cause it to lose altitude over time. It is well known that the braking effect of the atmosphere is greater the surface exposed to the flow of the atmospheric particles relative to the satellite. For this reason, a drag sail is essentially a large and lightweight membrane, which is deployed by the satellite when it is to begin orbital decay. For given environmental/initial conditions and inertial characteristics of the deployed system, the braking effect of a drag sail is more intense if its perpendicular axis is constantly aligned with the direction of the relative particle flow. For this purpose, a sliding mode control strategy is adopted. The reference to follow is obtained by propagating the spacecraft orbital dynamics along with its attitude dynamics. Various orbital perturbations and the disturbance torque due to atmospheric drag are implemented in the numerical code to verify the robustness of the proposed control law. It is also assumed that the spacecraft control torque vector is bounded in magnitude and always belongs to the plane of the braking device. The results show that the proposed strategy is effective in accurately tracking the reference attitude and that it is robust, being able to track a reference that varies unpredictably due to both orbital and attitude perturbations. • The paper analyzes the active attitude control problem of a drag sail. • The reference to follow is obtained by propagating the perturbed orbital dynamics. • A sliding mode control law is proposed to perform the attitude adjustments. • The control law is designed by imposing a limit on the magnitude of the input signal. • Numerical simulations indicate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

This work presents a novel approach for the optimization of dynamic systems on finite-dimensional Lie groups. We rephrase dynamic systems as so-called neural ordinary differential equations (neural ODEs), and formulate the optimization problem on Lie groups. A gradient descent optimization algorithm is presented to tackle the optimization numerically. Our algorithm is scalable, and applicable to any finite-dimensional Lie group, including matrix Lie groups. By representing the system at the Lie algebra level, we reduce the computational cost of the gradient computation. In an extensive example, optimal potential energy shaping for control of a rigid body is treated. The optimal control problem is phrased as an optimization of a neural ODE on the Lie group SE (3), and the controller is iteratively optimized. The final controller is validated on a state-regulation task. [ABSTRACT FROM AUTHOR]

This paper deals with the modelling and stabilization of a flexible clamped beam controlled with a piezoelectric actuator in the self-sensing configuration. We derive the model starting from general principles, using the general laws of piezoelectricity. The obtained model is composed by a PDE, describing the flexible deformations dynamics, interconnected with an ODE describing the electric charge dynamics. Firstly, we show that the derived linear model is well-posed and the origin is globally asymptotically stable when a voltage control law, containing the terms estimated in the self-sensing configuration, is applied. Secondly, we make the more realistic assumption of the presence of hysteresis in the electrical domain. Applying a passive control law, we show the well-posedness and the origin's global asymptotic stability of the nonlinear closed-loop system. [ABSTRACT FROM AUTHOR]

Model-Free Adaptive Control (MFAC) is a control strategy that eliminates the need for prior knowledge of the system model by leveraging online data to learn the system dynamics and design controllers. This paper offers a comprehensive exploration of the significance of control theory in unmanned surface vessels (USVs), with a particular focus on data-driven approaches. It provides a comprehensive overview of various MFAC algorithms proposed for USVs in diverse scenarios, including neural network-based MFAC, reinforcement learning-based MFAC, and fuzzy logic-based MFAC. The objective of this review is to provide a profound understanding of the latest advancements in MFAC technologies and serve as a guiding resource for further developments in the field. [ABSTRACT FROM AUTHOR]

Planar underactuated mechanical systems have been a popular research issue in the area of mechanical systems and nonlinear control. This paper reviews the current research status of control methods for a class of planar underactuated manipulator (PUM) systems containing a single passive joint. Firstly, the general dynamics model and kinematics model of the PUM are given, and its control characteristics are introduced; secondly, according to the distribution position characteristics of the passive joints, the PUM is classified into the passive first joint system, the passive last joint system, and the passive intermediate joint system, and the analysis and discussion are carried out in respect to the existing intelligent control methods. Finally, in response to the above discussion, we provide a brief theoretical analysis and summarize the challenges faced by PUM, i.e., uncertainty and robustness of the system, unified control methods and research on underactuated systems with uncontrollable multi-passive joints; at the same time, the practical applications have certain limitations that need to be implemented subsequently, i.e., anti-jamming, multi-planar underactuated robotic arm co-control and spatial underactuated robotic arm system development. Aiming at the above challenges and problems in the control of PUM systems, we elaborate on them in points, and put forward the research directions and related ideas for future work, taking into account the contributions of the current work. [ABSTRACT FROM AUTHOR]

One of several system classes that are frequently encountered in nonlinear and chaos control theory and its applications is the strict feedback form. The dynamics of many nonlinear and chaotic systems can be transformed into the strict feedback form via a change of variables as well. In this paper, a new discrete-time adaptive nonlinear controller is examined for a class of discrete-time high-order nonlinear systems in strict-feedback form. The proposed controller structure consists of a discrete-time controller built on a Lyapunov function, including a positive semi-definite function, and an adaptation mechanism that estimates unknown time-invariant parameters. The contributions of the proposed discrete-time method are twofold. One is that the discrete-time strict-feedback nonlinear systems are re-evaluated by a transformation, which enables us to design a flexible discrete-time controller. An elegant adaptive nonlinear controller is constructed without the complicated design steps, which is one of the main drawbacks encountered in controller design for general strict-feedback nonlinear systems. Owing to the mentioned transformation, computational complexity associated with other examples in the literature is effectively tackled and reduced. Another is that conventional least squares estimation is employed, demonstrating that the closed-loop error dynamics converge to the origin in an uncertain discrete-time internal model. Simulation results on two discrete-time nonlinear systems and a chaotic system verify the contributions of the proposed method. [ABSTRACT FROM AUTHOR]

Path following accuracy and lateral stability of autonomous vehicle are the direct embodiment of control quality in intelligent driving. To achieve the coordination of path following and lateral stability, a novel nonlinear concurrent control method for autonomous vehicle considering high-frequency interference and actuator saturation is proposed to solve the coupling problem of multi-objective control with single actuator input. The vehicle dynamics model and path following model are expressed as state equations with the same control input by model integration transformation. At the same time, the actuator saturation and high-frequency interference of AGV model is considered, which is incorporated into the integrated state equation. The Hamilton function for path following and lateral stability control are designed respectively, the existence condition of controller design based on vehicle characteristics is discussed and proved, and a nonlinear concurrent control method of AGV is presented with the control system stability being analyzed. The results show that the designed controller can ensure the path following effect and maintain the lateral stability of AGV simultaneously. [ABSTRACT FROM AUTHOR]

This paper addresses the trajectory tracking problem of differential-drive wheeled mobile robots with nonholonomic constraints. Contrary to other works that use a simplified kinematic model, we consider the configuration space of the mobile robot in the controller design; that is, the robot's motion evolves on the Cartesian space and the unit circle. Exploiting the cascade structure of the robot's kinematics, we propose a novel linear velocity-free trajectory-tracking controller that guarantees exponential convergence to the desired reference trajectory for almost all initial conditions. Almost global exponential stability of the closed-loop equilibrium point is proven using strict Lyapunov functions. We provide experimental results and a comparison study to validate the excellent performance and advantages of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

A three-dimensional active maglev (magnetic levitation) actuating system based on force imbalance is proposed. By combining the principle of force imbalance control with the control algorithm, the stable levitation and controllable levitating motion of the magnetic ball can be realized. The four electromagnetic actuating structures are used to stabilize the force of the controlled object, and the dual-hall sensor group and hardware differential method are used to improve control stability and accuracy. By combining the fine adjustment of the active maglev actuating system with the coarse adjustment of the mechanical arm, the three-dimensional levitation motion of the magnetic ball in curved pipes is realized. Experimental results show that the proposed control algorithm solves problems such as the increase of deviation between the controlled object and the steady-state operating point and the rapid deterioration of tracking performance in the model-based control method. In the vertical direction, the overshoot is within 0.418%, regardless of axis motion or non-axis motion. In the horizontal direction, the offset limits left and right of the axis are 4.590 mm and 3.536 mm, respectively. The fluctuation of vertical and horizontal motion is within the allowable range of ±0.2 mm. This can be applied to the non-destructive quality detection of the inner walls and the internal dredging of long and thin pipes in examinations and industrial fields. [ABSTRACT FROM AUTHOR]

We propose new results on input‐to‐state stability (ISS) subject to time delays in the input for compact, invariant sets that contain the origin. First, using nonlinear small‐gain theory, we prove a Razumikhin‐type theorem that ensures ISS for sets in the context of functional differential equations with delayed disturbances. Next we demonstrate that this theorem can be used to ensure set ISS for nonlinear systems with input delays and disturbances. In comparison to the existing research on robustness of set ISS with respect to time delays at the input, our results are more general, retain the ISS gain, and do not impose constraints on time delayed states. The advantages of the method are illustrated through two case‐studies on set‐stability for classes of nonlinear oscillators of practical interest. [ABSTRACT FROM AUTHOR]

In this study, a high robust control—second‐order sliding‐mode control (SOSMC) scheme is proposed to improve the DC‐link voltage dynamic performance of the grid‐side converter (GSC) for the doubly‐fed induction generator (DFIG) system under the wind turbine power disturbance and DC‐link capacitance parameter disturbance. In general, the wind speed is change with the environment and further has an effect on the power generation of the DFIG system. Besides, the capacitance of DC‐link capacitor may change with the working condition. To address this issue, a SOSMC scheme is proposed to replace the conventional proportional integral (PI) control for the DC‐link voltage controller of the GSC for the DFIG system in this study. By using the non‐linear SOSMC controller, the DFIG system is robust to the disturbance of the wind speed and the parameter of DC‐link capacitance. Compared with the conventional PI control scheme, the DFIG system with the proposed SOSMC scheme is much more robust, which has been verified in the MATLAB/Simulink platform. [ABSTRACT FROM AUTHOR]

In this paper, the adaptive control problem of pneumatic muscle (PM) joint systems with external disturbance, reconstruction error, and actuator dead-zone is researched. Compared with the existing results, the tracking performance of the PM joint system has been enhanced, and the system now guarantees the boundedness of the actuator output. First, an adaptive neural network is used to estimate the unknown dynamical behavior and the external disturbance of the system online, enabling real-time estimation of systematic errors. A static neural network is constructed to compensate for the unknown asymmetric dead-zone nonlinearity of the actuator. Second, an online robust update term is introduced to counteract reconstruction errors of the neural network and the external disturbance. Third, the Lyapunov theory is used to derive a smooth control law, ensuring the stability of the system and rigorously proving the uniform ultimate boundedness of the weight parameters of each neural network. Finally, the feasibility and effectiveness of the proposed scheme are demonstrated through simulations. [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 $ R 3 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]

Magnetic bearing (Magb) system is a modern and future electromagnetic device that has many advantages and applications. The open-loop dynamics of the Magb system has a nonlinear and unusable characteristic. In the present paper, a novel robust and advance terminal synergetic control (TSC) approach is developed to stabilize position of the Magb system. The controller is design based on the Magb model using the synergetic control associated with the terminal attractor method. The proposed control algorithm has the advantage of developing a control law which is continuous, chattering free, and allows for a more rapid system response. For further enhancement of the controller performance, a population-based algorithm named water strider optimizer (WSO) has been utilized to adjust the tunable coefficients of the control algorithm. In order to approve the ability and the performance of the proposed control approach, a simulation comparison results with the classic synergetic control (CSC) is conducted. Based on the simulation results, the TSC improves the settling time by 50% and the ITAE index by 45.3% as compared to the CSC. In addition, the recovery time under an external disturbance has been improved by 50% as compared to the CSC. These outcomes demonstrate that the proposed control algorithm allows for rapidly in the system response and more robustness. [ABSTRACT FROM AUTHOR]

Liquid level measurement is a vital task in industries such as food processing, chemical manufacturing, and petroleum. The findings show that FLC and SMC offer superior performance in terms of rapid response, precision, and stability, particularly in handling nonlinear processes. By implementing these sophisticated controllers, industries put up benefit from increased work stability, low material waste, and improved energy efficiency. The study's results directly contribute to improving industrial applications by optimizing production and minimizing costs. The primary feather objective of a liquid level control system of rules is to exert a predetermined changeable level using a storage tank, measurement system, controller, and pump. This paper compares quaternary controllers: Fuzzy logical system Controller (FLC), Proportional-Integral-Derivative (PID), Nonlinear PID, and Sliding Mode verify (SMC) applied to some I and connected tankful systems. The FLC is an intelligent controller that excels at managing non-linear and uncertain systems by interpreting influx and outflow rates and adjusting the system to maintain desired unstable levels. Its adaptability to undefined scenarios is a key innovation. The PID controller is used as a benchmark undefined to its simplicity simply struggles with non-linear systems and time-varying parameters. The Nonlinear PID controller improves upon the traditional PID by using wrongdoing saturation functions, providing better control in non-linear systems. The SMC is a robust control method that ensures system stableness in the front of disturbances and uncertainties, making it highly effective for heavy-duty applications. Simulation results show that FLC and SMC cater a faster response and better accuracy in reaching desired unstable levels compared to traditional PID controllers. Both systems demo robust stableness and efficient control. As seen in the provided data, the FLC reaches a steady-state level in as little as 8.34 seconds in Run 1 and 1.088 seconds in Run 2 for the single-tank system. Similarly, the SMC stabilizes the system in approximately 23.17 seconds in the coupled tank system, reflecting its robust control capabilities. [ABSTRACT FROM AUTHOR]

This research aims to propose a power management strategy (PMS) based on the flatness control method for a stand-alone DC microgrid system. The goal of the proposed strategy is to create an efficient PMS using nonlinear flatness theory in order to provide a constant DC bus voltage and the best possible power-sharing mechanism between the battery and the PV array. A maximum power point tracking (MPPT) technique based on an artificial neural network (ANN) to optimize the PV's power. Moreover, the suggested PMS technique was tested in a simulation environment based on MATLAB®/Simulink. The obtained results demonstrate that the proposed PMS method can stabilize the bus voltage under variations in load or solar radiation. Additionally, the PMS method reduced bus voltage spikes and guaranteed good power quality, which extended the battery's lifespan and increased its efficiency. Also, the proposed approach outperforms the standard PI approach in terms of tracking efficiency and has a lower rate of overshoot in the bus voltage under different load scenarios. Therefore, the method is effective when compared with the classical PI approach. The overshoot in the PI method is 58 V, while the overshoot in the DC voltage is 5 V in the proposed method. The tracking speed of the proposed system is very low, and the slower speed was observed in the classical method, and the rise time of PI was 7.9ms, while the proposed method equals 2.2ms. [ABSTRACT FROM AUTHOR]

A microreactor is a chemical reaction device that mixes liquids in a very narrow channel and continuously generates reactions. They are attracting attention as next-generation chemical reaction devices because of their ability to achieve small-scale and highly efficient reactions compared to the conventional badge method. However, the challenge is to design a control system that is tolerant of faults in some of the enormous number of sensors in order to achieve parallel production by numbering up. In a previous study, a simultaneous control system for two different temperatures was proposed in an experimental system that imitated the microreactor cooled by Peltier devices. In addition, a fault-tolerant control system for one area has also been proposed. However, the fault-tolerant control system could not be applied to the control system of two temperatures in the previous study. In this paper, we extend it to a two-input, two-output fault-tolerant control system. We also use a fault detection system that combines ChangeFinder, a time-series data analysis method, and One-Class SVM, an unsupervised learning method. Finally, the effectiveness of the proposed method is confirmed by experiments. [ABSTRACT FROM AUTHOR]

In recent years, vibration control utilizing smart materials has garnered considerable attention. In this paper, we aim to achieve vibration suppression of a plate structure with a tail-fin shape by employing piezoelectric actuators—one of the smart materials. The plate structure is rigorously modeled based on the Kirchhoff–Love plate theory, while the piezoelectric actuators are formulated in accordance with the Prandtl–Ishlinskii model. This research proposed a control system that addresses the interference effects arising during vibration control by dividing multiple piezoelectric elements into two groups and implementing MIMO control. The efficacy of the proposed control method was validated through simulations and experiments. [ABSTRACT FROM AUTHOR]

Mirror therapy is a standard technique of rehabilitation for recovering motor and vision abilities of stroke patients, especially in the case of asymmetric limb function. To enhance traditional mirror therapy, robotic mirror therapy (RMT) has been proposed over the past decade, allowing for assisted bimanual coordination of paretic (affected) and contralateral (healthy) limbs. However, state-of-the-art RMT platforms predominantly target mirrored motions of trajectories, largely limited to 2-D motions. In this paper, an RMT platform is proposed, which can facilitate the patient to practice virtual activities of daily living (ADL) and thus enhance their independence. Two similar (but mirrored) 3D virtual environments are created in which the patients operate robots with both their limbs to complete ADL (such as writing and eating) with the assistance of the therapist. The recovery level of the patient is continuously assessed by monitoring their ability to track assigned trajectories. The patient’s robots are programmed to assist the patient in following these trajectories based on this recovery level. In this paper, the framework to dynamically monitor recovery level and accordingly provide assistance is developed along with the nonlinear controller design to ensure position tracking, force control, and stability. Proof-of-concept studies are conducted with both 3D trajectory tracking and ADL. The results demonstrate the potential use of the proposed system to enhance the recovery of the patients.

Abstract In this study, a high robust control—second‐order sliding‐mode control (SOSMC) scheme is proposed to improve the DC‐link voltage dynamic performance of the grid‐side converter (GSC) for the doubly‐fed induction generator (DFIG) system under the wind turbine power disturbance and DC‐link capacitance parameter disturbance. In general, the wind speed is change with the environment and further has an effect on the power generation of the DFIG system. Besides, the capacitance of DC‐link capacitor may change with the working condition. To address this issue, a SOSMC scheme is proposed to replace the conventional proportional integral (PI) control for the DC‐link voltage controller of the GSC for the DFIG system in this study. By using the non‐linear SOSMC controller, the DFIG system is robust to the disturbance of the wind speed and the parameter of DC‐link capacitance. Compared with the conventional PI control scheme, the DFIG system with the proposed SOSMC scheme is much more robust, which has been verified in the MATLAB/Simulink platform.

This study reviews numerous control approaches utilized to address various issues encountered by unmanned aerial vehicles (UAVs). Specifically, focusing on the quadrotor system. Due to its versatility and compact size, quadrotors have gained popularity as UAVs in recent decades. Quadrotors face challenges such as ambient disturbances, impediments, non-parametric and parametric perturbations while performing tasks. Consequently, a robust and efficient control system is essential for such a system to ensure the stability and enhance their performance. It should be noted that, in this review, we have examined and analyzed the most recent highly cited papers selected from esteemed journals and magazines renowned for their exceptional quality and reputation.

The main goal of this proposal is to present a class of nonlinear controllers for regulation and set point changes in continuous chemical reactors. The proposed control law has in its mathematical structure a proportional term of the regulation error to provide closed‐loop stability and a sinusoidal term, which can compensate for the nonlinearities of the plant. The closed‐loop stability of the plant is demonstrated via Lyapunov analysis, which reveals an asymptotic convergence of the control output to the required set points. Furthermore, the analysis of the regulation error's dynamic under the considered assumptions leads us to conclude that exponential stability is also reached. The controller is implemented via numerical experiments in two examples to generalize the applicability of the proposed approach by considering continuous stirred‐tank reactors models. The first case considers autocatalytic chemical oscillatory reactions that induce chaotic behaviour. For the second case, a process of acetone, butanol, and ethanol (ABE) fermentation through Clostridium acetobutylicum is considered. The proposed strategy shows an adequate performance because it can reach the required set point without long time settings and overshoot. A comparison with a smooth sliding‐mode and a standard proportional‐integral (PI) controller indicates the advantages of the proposed control approach. [ABSTRACT FROM AUTHOR]

This article presents a nonlinear control strategy designed to address parametric uncertainties in an agricultural tractor system coupled to a towed implement. The controller ensures accurate tracking of lateral and yaw velocities relative to desired reference trajectories, even under the presence of parametric variations and external disturbances. The reference trajectories are derived from an “ideal” tractor model, excluding the effects of the towed implement. A High-Order Sliding Mode (HOSM) estimator is employed to provide an estimation of disturbances, which are subsequently mitigated by the controller to maintain system stability and precision. The effectiveness of the proposed control strategy is validated through Matlab-Simulink simulations, which include a double-step steer maneuver. This maneuver tests the system’s ability to handle abrupt steering changes, providing insight into the controller’s robustness and its capacity to ensure accurate trajectory tracking in demanding conditions.

Abstract A novel adaptive tracking controller for magnetic levitation systems (MLS) is developed. The controller is based on a special adaptive control scheme incorporating fuzzy model of electromagnetic acceleration enabling fast and accurate fuzzy inversion. The controller ensures accurate tracking of any smooth desired position signal, despite unknown MLS parameters. The closed-loop system stability, in the sense of uniform ultimate boundedness (UUB) of error trajectories, is proved using Lyapunov approach. The closed-loop system performance is investigated during numerical experiments. Finally the proposed controller is verified by successful implementation on a DSP board controlling a typical magnetic levitation ball system. Performed tests and experiments demonstrate that the proposed control technique is robust against discretization and unknown MLS model parameters, provides high tracking accuracy, is easily implementable, and simple to tune.

In this paper, a quick convergence adaptive structure is proposed for trajectory tracking of an articulated type robotic manipulator using the Hardware in the Loop (HIL) simulation technique. A novel Nonlinear Quick Convergence Adaptive Sliding Backstepping Control (QCASBC) algorithm is implemented on a C2000 real-time controller board. The performance of the proposed control algorithm is inspected concerning the sliding mode PID (SM-PID) control technique to estimate its correlation with the proposed algorithm. The experimental part of the HIL simulation tests has been carried out on a simulated model of a three-link serial robot manipulator. A dynamic model of the robotic manipulator has been developed using Matlab Simulink software and its performance is analyzed using the HIL technique via a C2000 real-time controller for tracking the desired trajectory. Results show that the speed of convergence while tracking the desired trajectory of the manipulator is better in the proposed algorithm. It is also estimated that the positional error of the QCASBC algorithm is superior to the SM-PID control algorithm. The observed average angle error is improved by 14% and the average response time error is improved by 11% by using the proposed QCASBC algorithm compared to the SM-PID approach.

Abstract During the trajectory tracking of robotic manipulators, many factors including dead zones, saturation, and uncertain dynamics, greatly increase the modeling and control difficulty. Aiming for this issue, a nonlinear active disturbance rejection control (NADRC)-based control strategy is proposed for robotic manipulators. In this controller, an extended state observer is introduced on basis of the dynamic model, to observe the extend state of model uncertainties and external disturbances. Then, in combination with the nonlinear feedback control structure, the robust trajectory tracking of robotic manipulators is achieved. Furthermore, to optimize the key parameters of the controller, an improved particle swarm optimization algorithm (IPSO) is designed using chaos theory, which improves the tracking accuracy of the proposed NDRC strategy effectively. Finally, using comparative studies, the effectiveness of the proposed control strategy is demonstrated by comparing with several commonly used controllers.

In this paper, an improved self-coupled PI control dual-loop control strategy is proposed for the vector control of permanent magnet synchronous electric speed control system, to improve the poor motor control effect caused by the dead zone of the inverter, the presence of harmonics in the motor magnetic field distribution, and the error in the sampling process of the current. In order to reduce the tracking error of the signal, an acceleration feed-forward method is adopted, and the self-coupled PI controller with an additional Levant differentiator is introduced into the speed loop of the permanent magnet synchronous motor to ensure the accurate derivation of the input signal containing noise to improve the robustness of the system. In addition, this strategy combines the proportional term of the autotuned PI control structure with the standard resonator to form a proportional resonant autotuned PI in the current loop, so that the permanent magnet synchronous motor can better compensate the current in the current loop control to achieve the effect of current harmonic suppression. Finally, the control mechanism of the servo system analyzed, and based on the mathematical model of the controlled object PMSM, the design method of the improved self-coupling PI control structure is given. The experimental results show that the proposed control strategy can reduce the impact of the motor's own parameter changes on the system performance and has a good current harmonic suppression in the low-speed domain, which verifies the effectiveness of the designed improved self-coupled PI controller.

Wave energy holds significant promise as a renewable energy source due to the consistent and predictable nature of ocean waves. However, optimizing wave energy devices is essential for achieving competitive viability in the energy market. This paper presents the application of a nonlinear model predictive controller (MPC) to enhance the energy extraction of a heaving point absorber. The wave energy converter (WEC) model accounts for the nonlinear dynamics and static Froude–Krylov forces, which are essential in accurately representing the system's behavior. The nonlinear MPC is tested under irregular wave conditions within the power production region, where constraints on displacement and the power take-off (PTO) force are enforced to ensure the WEC's safety while maximizing energy absorption. A comparison is made with a linear MPC, which uses a linear approximation of the Froude–Krylov forces. The study comprehensively compares power performance and computational costs between the linear and nonlinear MPC approaches. Both MPC variants determine the optimal PTO force to maximize energy absorption, utilizing (1) a linear WEC model (LMPC) for state predictions and (2) a nonlinear model (NLMPC) incorporating exact Froude–Krylov forces. Additionally, the study analyzes four controller configurations, varying the MPC prediction horizon and re-optimization time. The results indicate that, in general, the NLMPC achieves higher energy absorption than the LMPC. The nonlinear model also better adheres to system constraints, with the linear model showing some displacement violations. This paper further discusses the computational load and power generation implications of adjusting the prediction horizon and re-optimization time parameters in the NLMPC. [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]

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]

This work proposes a resource efficient robust control scheme for missile-target engagement scenarios subjected to external disturbances. The robustness is achieved by using an annular event-triggered artificial time-delayed control (ET-TDC) methodology with input saturation. The ET-TDC philosophy uses the TDC strategy through a dynamic predefined triggering mechanism which overcomes the requirement to update the control periodically for every sampling instant, unlike conventional TDC and other robust control schemes. Thus the proposed methodology can tackle uncertainties with minimal a-priori knowledge while significantly reducing the over-utilisation of system resources. In addition, the adopted event-triggered mechanism facilitates further conservation of energy which might be crucial for mid-to-long range engagement scenarios. The closed-loop stability is derived analytically and the simulation results illustrate the efficacy of the proposed guidance framework in comparison with other state-of-art robust control methodologies. [ABSTRACT FROM AUTHOR]

Autonomous vehicles that can reliably operate outside the stable handling limits would have access to a wider range of maneuvers in emergencies, improving overall safety. To that end, this paper presents a novel Nonlinear MPC approach for vehicle control with deeply saturated rear tires. Longitudinal slip management is elevated from the chassis control layer into the optimisation problem by using a coupled-slip tire model, and explicitly including wheelspeed dynamics. Terminal costs on sideslip stability help compensate for the finite horizon, while road bounds and static obstacles are encoded using slack constraints. Experiments on a racetrack with a modified Toyota GR Supra validate the controller's ability to smoothly transition from dynamic, non-equilibrium drifting to grip driving. Further experiments demonstrate robustness to significant longitudinal force and wheelspeed disturbances, and showcase the controller flexibly transitioning in and out of the sliding tire regime to balance slack constraints with tracking objectives. [ABSTRACT FROM AUTHOR]

This study reviews numerous control approaches utilized to address various issues encountered by unmanned aerial vehicles (UAVs). Specifically, focusing on the quadrotor system. Due to its versatility and compact size, quadrotors have gained popularity as UAVs in recent decades. Quadrotors face challenges such as ambient disturbances, impediments, non-parametric and parametric perturbations while performing tasks. Consequently, a robust and efficient control system is essential for such a system to ensure the stability and enhance their performance. It should be noted that, in this review, we have examined and analyzed the most recent highly cited papers selected from esteemed journals and magazines renowned for their exceptional quality and reputation. [ABSTRACT FROM AUTHOR]

Summary: This paper addresses the adaptive saturation prescribed performance control problem for air‐breathing hypersonic vehicles with parameter uncertainties and unknown external disturbances. First of all, different from the traditional performance function, a novel class of performance functions is presented without the initial state information, which does not require to reset parameters even if the initial velocity and altitude change. To ensure the successful design of the velocity controller and altitude controller, the constrained errors are transformed into the unconstrained errors by the projection technique. Secondly, the adaptive neural network and the sliding mode control techniques are combined to design the adaptive neural network sliding mode controllers, which guarantee that the velocity and altitude tracking errors can respectively approach the predetermined regions within the identical preset finite time. Finally, the effectiveness of the designed controllers is verified by an example with comparisons. [ABSTRACT FROM AUTHOR]

This article presents a trajectory‐tracking controller for multi‐rotor unmanned aerial vehicles (UAVs) in scenarios where only the desired position and heading are known without the higher‐order derivatives. The proposed solution modifies the state‐of‐the‐art geometric controller, effectively addressing challenges related to the non‐existence of the desired attitude and ensuring positive total thrust input for all time. We tackle the additional challenge of the non‐availability of the higher derivatives of the trajectory by introducing novel nonlinear filter structures. We formalize theoretically the effect of these filter structures on the system error dynamics. Subsequently, through a rigorous theoretical analysis, we demonstrate that the proposed controller leads to uniformly ultimately bounded system error dynamics. To demonstrate the controller's effectiveness and potential to enhance multi‐rotor performance and reliability in practical applications, we present a simulation study considering two examples with time‐varying trajectories. [ABSTRACT FROM AUTHOR]