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Maximum power point tracking (MPPT) controller is the main element in photovoltaic (PV) systems, which is used to ensure maximum power extraction under different meteorological conditions. A MPPT controller can guarantee good performance criteria even in the presence of climatic changes. To achieve this goal, several techniques have been proposed in the literature to improve robustness of the PV system control, such as artificial intelligence and multiswarm particle swarm optimization (MSPSO) algorithm. Previous research on classical MSPSO has shown that the algorithm search behavior cannot find the optimal solution for certain problems. In this context, we investigate the design of a new MPPT controller based on a modified version of heterogeneous multiswarm particle swarm optimization algorithm using an adaptive factor selection strategy (FMSPSO) for PV systems. The proposed FMSPSO can improve the tracking capability with high accuracy, less oscillations, and high robustness. To validate the proposed solution, a simulation and experimental benchmarking of a PV system are presented and analyzed. The obtained results show the effectiveness of the proposed solution compared with the classical MSPSO, fuzzy logic, and perturb and observe (P&O) control presented in other recent works. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for designing a decentralized control law for higher-order systems using the H ∞ complementary sensitivity function (CSF) framework. Higher-order systems often exhibit complex dynamics and interactions between the variables, and hence, sophisticated control strategies are required to attain the desired performance. The proposed method exploits the robustness properties of the H ∞ CSF to achieve effective decentralized control for higher-order systems. The CSF approach focuses on shaping the sensitivity of the system to disturbances, thereby minimizing the impact on system performance. The decentralized nature of the control law allows for independent control of each subsystem, reducing the complexity associated with higher-order systems. Furthermore, the controller parameters are determined graphically by enforcing the H ∞ robust criterion. The effectiveness of the proposed methodology is demonstrated through simulations on higher-order systems from various domains, including process control and other systems. Comparative evaluations against existing control methods highlight the superiority of the H ∞ CSF-based decentralized control law in terms of robustness and performance. [ABSTRACT FROM AUTHOR]

In this paper, a LuGre model–based robust adaptive control (RAC) approach is presented for a pump-controlled hydraulic actuator. We first decompose the LuGre friction model into its steady-state model and a lumped dynamic part applying the mean value theorem, which are compensated by a feedforward term and a robust adaptive term, respectively. The robust adaptive term also plays a part in mismatched disturbance attenuation. In addition, parametric uncertainties and matched disturbances are handled by σ -modified adaptation laws and a robust control law, respectively. The stability of the closed-loop system is proved via the Lyapunov analysis. The efficacy and robustness of the proposed approach are validated by comparative experiments. Compared with common adaptive friction compensation methods, the proposed method has a simpler structure, less computational burden, better control performance, and stronger robustness. Moreover, since the available information is separated from the LuGre model and acts as a model-based compensation term, the design conservativeness of RAC is effectively reduced. [ABSTRACT FROM AUTHOR]

Motivated by the fully actuated system (FAS) approach, this paper proposes a direct robust control method for a type of uncertain multi‐order sub‐fully actuated systems (MOSFASs). Unlike numerous previous results, this paper broadens to a more general multi‐order model and the more challenging sub‐fully actuated case with the presence of singular problems. Firstly, a general uncertain MOSFAS model is presented, where the uncertainty merely needs to satisfy a common assumption. Secondly, a direct robust control method is proposed, giving a robust controller which only needs to satisfy very loose and basic requirements to ensure that the states ultimately converge into an arbitrarily small region. Simultaneously, by constraining the initial values of the states, it is perfectly guaranteed that the states always remain in a “safe” zone free of singular points, thus preserving the realizability of the controller. Finally, under certain conditions, a less conservative robust control scheme is introduced, which can relax the constraint of initial values easily. A simulation for a coarse‐fine angle system demonstrates the validity and value of the proposed robust control method. [ABSTRACT FROM AUTHOR]

The aging brain undergoes major changes in its topology. The mechanisms by which the brain mitigates age-associated changes in topology to maintain robust control of brain networks are unknown. Here we use diffusion MRI data from cognitively intact participants (n = 480, ages 40–90) to study age-associated differences in the average controllability of structural brain networks, topological features that could mitigate these differences, and the overall effect on cognitive function. We find age-associated declines in average controllability in control hubs and large-scale networks, particularly within the frontoparietal control and default mode networks. Further, we find that redundancy, a hypothesized mechanism of reserve, quantified via the assessment of multi-step paths within networks, mitigates the effects of topological differences on average network controllability. Lastly, we discover that average network controllability, redundancy, and grey matter volume, each uniquely contribute to predictive models of cognitive function. In sum, our results highlight the importance of redundancy for robust control of brain networks and in cognitive function in healthy-aging. A diffusion MRI study suggests that redundancy could mitigate the effects of age-associated changes in brain topology to support the average controllability of brain networks middle and old age. [ABSTRACT FROM AUTHOR]

Summary: This article studies robust adaptive control for a class of autonomous vehicle platoons. In particular, two innovative adaptive control laws are proposed to address both position and velocity tracking for a vehicle platoon. In addition, it is shown that robust asymptotic string stability can be delivered by the underlying adaptive control laws for the vehicle platoon, in the sense that these adaptive control laws are capable of mitigating parameter uncertainties involved in the nonlinear vehicular dynamics and achieving truly cooperative adaptive cruise control while ensuring the required safety spacing between each neighboring vehicle pair asymptotically. It is also shown that the control performance of the vehicle platoon can be further improved if the operating equilibrium points of all vehicles can be adaptively estimated, leading to two linear time‐invariant control laws for individual vehicles under both position and velocity controls and for the vehicle platoon. Simulation studies illustrate the effectiveness of the proposed control method, validating the results obtained for the class of vehicle platoons. [ABSTRACT FROM AUTHOR]

During the epoch of sustainable development, leveraging cellular systems for production of diverse chemicals via fermentation has garnered attention. Industrial fermentation, extending beyond strain efficiency and optimal conditions, necessitates a profound understanding of microorganism growth characteristics. Specific growth rate (SGR) is designated as a key variable due to its influence on cellular physiology, product synthesis rates and end-product quality. Despite its significance, the lack of real-time measurements and robust control systems hampers SGR control strategy implementation. The narrative in this contribution delves into the challenges associated with the SGR control and presents perspectives on various control strategies, integration of soft-sensors for real-time measurement and control of SGR. The discussion highlights practical and simple SGR control schemes, suggesting their seamless integration into industrial fermenters. Recommendations provided aim to propose new algorithms accommodating mechanistic and data-driven modelling for enhanced progress in industrial fermentation in the context of sustainable bioprocessing. [ABSTRACT FROM AUTHOR]

In this paper, we develop an improved data-based integral policy iteration method to address the robust control issue for nonlinear systems. Combining multi-step neural networks with pre-training, the condition of selecting the initial admissible control policy is relaxed even though the information of system dynamics is unknown. Based on adaptive critic learning, the established algorithm is conducted to attain the optimal controller. Then, the robust control strategy is derived by adding the feedback gain. Furthermore, the computing error is considered during the process of implementing matrix inverse operation. Finally, two examples are presented to verify the effectiveness of the constructed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose the design of a robust control strategy for the trajectory tracking problem in perturbed unicycle mobile robots. The proposed strategy comprises the design of a robust control law, which is based on an Integral Sliding‐Mode Control (ISMC) approach together with an interval predictor‐based state‐feedback controller through a Model Predictive Control (MPC) scheme. The robust controller deals with some perturbations in the kinematic model, which represent slipping effects, and with state and input constraints that are related to restrictions on the workspace and saturated actuators, respectively. The proposed approach guarantees the exponential convergence to zero of the tracking error. The performance of the proposed approach is validated through some simulations tracking a lemniscate and a circumference curve. [ABSTRACT FROM AUTHOR]

We consider the design of fast and reliable neural network‐based approximations of traditional stabilizing controllers for linear systems with polytopic uncertainty, including control laws with variable structure and those based on a (minimal) selection policy. Building upon recent approaches for the design of reliable control surrogates with guaranteed structural properties, we develop a systematic procedure to certify the closed‐loop stability and performance of a linear uncertain system when a trained rectified linear unit (ReLU)‐based approximation replaces such traditional controllers. First, we provide a sufficient condition, which involves the worst‐case approximation error between ReLU‐based and traditional controller‐based state‐to‐input mappings, ensuring that the system is ultimately bounded within a set with adjustable size and convergence rate. Then, we develop an offline, mixed‐integer optimization‐based method that allows us to compute that quantity exactly. [ABSTRACT FROM AUTHOR]

This paper concerns the problem of asymptotic attitude stabilization for uncertain spacecraft subject to actuator constraints and bounded external disturbances. A simple model‐free saturated robust PD control is proposed within the framework of PD design methodology combining sliding mode control strategy. Asymptotic stabilization stability is proved in terms of Lyapunov's direct method and Barbalat's lemma. Advantages of the proposed control include the easy‐going implementation with simple and intuitive structure and explicit tuning procedure and abilities to guarantee the asymptotic attitude stabilization and bounded disturbance rejection and ensure the actuator constraint is not violated by selecting the control gains a priori. Simulation comparisons demonstrate the improved performance of the proposed approach. [ABSTRACT FROM AUTHOR]

The model parameter uncertainty and controller gain disturbance of the factory servo system are challenges that affect the robustness and control performance of the system. In this paper, a class of factory servo systems with non‐integer order is studied. The stable boundary trajectory method of the fractional order system is used to determine the parameter stability domain that makes the control system stable. An optimal gain trade‐off design method for time‐varying parameter fractional order PID controller (TPPIλDμ$$ \mathrm{TP}{PI}^{\lambda }{D}^{\mu } $$) is proposed. The time function is introduced as the adjustment formula to realize the adaptive adjustment of the controller gain. The Lyapunov theorem analyzes the stability of the method. At the same time, an ameliorated gazelle optimization algorithm (AGOA) is proposed to optimize the parameters of the TPPIλDμ$$ \mathrm{TP}{PI}^{\lambda }{D}^{\mu } $$ controller, and the weight relationship is changed to set the objective function to obtain the optimal performance combination after optimization. The benchmark function optimization test is completed. Statistical analysis shows that AGOA can enhance the global search ability, prevent the acquisition of local optimum, and have faster convergence speed. The final simulation results show that the proposed scheme is a promising alternative to improve the system control performance. [ABSTRACT FROM AUTHOR]

The recursive integral terminal sliding mode control with combined extended state observer (ESO) and adaptive Kalman filter (AKF) is proposed in this article for micromechanical system gyroscopes. To accurately estimate the unmeasured system states in the presence of measurement noises, external disturbances and system uncertainties, the special combination of ESO and AKF is proposed. The AKF is employed to deal with measurement noises and prepare necessary signals for the ESO, while the ESO constantly provides the updated estimate of the lumped disturbance for the AKF. Furthermore, a robust control scheme is designed by using the recursive integral terminal sliding mode variable. Simulation results verify that more accurate unmeasured state estimation and higher tracking accuracy are achieved under the proposed method. [ABSTRACT FROM AUTHOR]

Floating production storage and offloading systems (FPSOs) are gaining prominence in the offshore industry. FPSOs are generally designed to weathervane, necessitating surge vibration control for station keeping. Since the natural period of surge vibration is far higher than the dominant period of the input wave load, instead of supplemental damping, a high inertial device, such as the tuned mass damper inerter (TMDI), would be effective. This concept has hitherto not been investigated for the FPSO. A frequency domain formulation of the FPSO-TMDI system under wave force, considering interaction of the liquid cargo is presented. Utilizing Froude-Krylov theory, suitably modified to account for diffraction effects, wave force on the FPSO is obtained using field data from North Sea. TMDI parameters are optimized using Genetic Algorithm under different tank-fill conditions. The results demonstrate that the TMDI holds potential in providing an effective and robust performance in controlling the surge motion of FPSOs. [ABSTRACT FROM AUTHOR]

The steer-by-wire (SbW) system is a promising system in the realm of automotive engineering. It substitutes the mechanical connection between the steering wheel and the front road wheels with an electronic signal-based functional connection. The SbW system offers several advantages over conventional steering systems, including weight reduction, reduced vibration, and enhanced steering functionality configuration. However, the absence of a mechanical linkage in the SbW system gives rise to certain challenges. The SbW system requires endowing adequate steering feel such as damping and reaction force using feedback motor, and the road wheel needs robust control of pinion motor for normal load variation by passengers and self-aligning torque as external disturbance. The SbW system is composed of the steering feedback module (SFM) and the road wheel module (RWM). This paper proposes a control approach to generate steering feel for SFM, in which steering feel is generated using an admittance model based on velocity control. A disturbance observer is applied to ensure robustness of velocity control. The steering wheel torque versus steering wheel angle (T–A) curve is used to analyze steering feel characteristic and evaluate steering feel. The proposed steering system is validated through experiments that confirm its ability to provide satisfactory steering feel for vehicles. This work may offer a novel solution for the design of advanced steering systems in the field for the future mobility such as an autonomous driving. [ABSTRACT FROM AUTHOR]

This paper compares various angle-tracking algorithms to balance the performance and noise for a steering-by-wire (SBW) system. Direct and quiet steering experiences can improve drivers' acceptance of the SBW system. Linear quadratic regulator (LQR) control, robust control, and conventional cascade proportional–integral (PI) control have been developed and compared both theoretically and experimentally. To avoid the risky and time-consuming parameter-tuning process, a high-fidelity steering resistance model, which comprises a linear two-degree-of-freedom vehicle model and a dynamic LuGre friction model is established. Step and sine wave tests are simulated in a Matlab/Simulink environment to determine the reasonable parameter region for various methods. Then, the three types of algorithms are implemented on a prototype SBW vehicle and compared under the same scenarios. Finally, the simulated and experimental results are illustrated in detail. According to the indicators of control bandwidths, steady-state errors, cockpit sounds, and current waveforms, it is clear that LQR and robust control can achieve faster response and more acceptable noise, with uncertain and relatively larger tracking errors. Cascade PI control, in comparison, can realize smaller steady-state errors and gentler current waveforms, with slight noise and slower response. [ABSTRACT FROM AUTHOR]

This article aims at designing a robust wide-area damping controller (WADC) to address the problems associated with communication failures. The proposed controller is a state feedback-based controller, which uses generators' states as the controller inputs. The structure of the proposed controller's feedback gain matrix is a combination of two feedback gain matrices to achieve adequate robust performance over different disturbances and communication losses. These two feedback gain matrices are; full-scale feedback gain matrix and decentralized scale feedback gain matrix. Both models are designed by considering all generators' states are available at the controller input side. However, both matrices' structures are different from each other. The conventional LQR state feedback control technique is used to design the full-scale matrix. On the other hand, the decentralized scale matrix is computed using a structurally constrained H 2 -norm optimization technique to acquire the required structure. The full-scale model gives robust performance under different faults. Whereas, the decentralized scale matrix will result robust performance against communication failures. Therefore, to achieve superior performance under all conditions, the proposed controller can be used. To show the efficacy of the proposed controller, it is compared with different existing controllers and the results are illustrated. Simulation studies are conducted on well-known IEEE 39-bus and 68-bus test systems to validate the robustness of the proposed controller considering different faults and communication failures. [ABSTRACT FROM AUTHOR]

The stability of each train, high control accuracy, and minimum safe separation distance are important indexes to measure the performance of the cooperative control system of multiple trains. In this article, aiming at the problem of low accuracy of multiple trains cooperative control with nonlinear running resistance and external disturbance, the distributed cooperative robust adaptive control scheme for multiple trains with RBFNN position output constraints based on train running curve tracking is proposed. Multiple different control techniques are offered for different trains, and that they are based on local knowledge of position, speed, and acceleration. The leading train's speed and position precisely match the planned operation curve, while the following train keeps the tracking interval at the minimum safe distance between two trains. In order to reduce the influence of the uncertainty of basic resistance parameters and external interference on the cooperative control of multiple trains, the parameter uncertainties are compensated by adding a robust adaptive law to the multiple trains control based on position output constraints. The lumped exogenous disturbances (additional resistance, external interference, measurement noise, etc.) are estimated using an RBFNN approximator for the unknown term of the cooperative system. The stability of the cooperative operation of multiple trains is confirmed using the Lyapunov stability theorem. The performance of the proposed scheme was evaluated by the cooperative control system of multiple trains in predecessor following (PF) and bidirectional control (BC) modes. [ABSTRACT FROM AUTHOR]

This paper proposes observer based controls for a MIMO Timoshenko beam system with disturbances and references from an exosystem, and by further limiting the references and disturbances, also gives reduced-order controls. At first, we propose state feedback controls to guarantee the output regulation problem of a nominal Timoshenko beam system, which is obtained by specially choosing known disturbances and references. This also makes the PDE observer easily designed based on tracking errors only. Then, exosystem observers and their reduced-order forms are proposed in case of different geometric multiplicities and limited conditions of disturbances, references and system uncertainties. This gives observer based robust controls and reduced-order observer based controls. Robust output regulation is proved for the Timoshenko beam under observer based controls. Simulation examples are provided for a Timoshenko beam system with different references and system uncertainties. [ABSTRACT FROM AUTHOR]

This paper investigates the finite-time time-varying formation-containment control problem for satellite formation flying under discontinuous control protocols based on nonsmooth analysis. The desired consequence is that the follower satellites can converge into a dynamic convex hull in finite time, which is spanned by leader satellites' time-varying formation according to the reference signal. Firstly, to accomplish this objective, a finite-time time-varying formation-containment control strategy is proposed for satellite formation system in present of the bounded disturbances and satellites' accelerations, which are known for each satellite. Then, considering the case that the information of disturbances may not be measured accurately and the accelerations of satellites may not be obtained globally in some practice application scenarios, a fully distributed adaptive control strategy is proposed by introducing the dynamic variables. The adaptive variables can compensate the unknown items and adjust with the evolution of neighbour satellites' states, which makes the controller more flexible. Moreover, the proposed control strategies are able to guarantee a fast dynamic response and also a suppression of disturbance. Finally, the performances of the proposed strategies are demonstrated by numerical simulations. [ABSTRACT FROM AUTHOR]

• We construct a multidimensional poverty index for chinese counties. • We establish a staggered DID model that controls for selection bias. • Highways significantly reduce county poverty. • The poverty-reduction effect of highways is conditional. • The poverty-reduction effect of highways diminishes with increasing altitude. This paper establishes a staggered difference-in-differences (DID) model to estimate the impact of highways on regional poverty using county-level panel data from China. We construct a multidimensional poverty index and use satellite-monitored night light brightness as a proxy indicator. The results demonstrate that highways significantly reduce county poverty and that the poverty reduction effect becomes increasingly pronounced over time. This result remains robust after controlling for non-random highway route selection. Furthermore, the poverty reduction effect of highways is conditional, with a significant poverty reduction effect in the less economically-developed western regions and non-municipal counties, and no significant poverty reduction effect in the economically-developed eastern and central regions and municipal districts. Moreover, the poverty reduction effect of highways gradually decreases as the average altitude of counties increases. Our tests provide empirical evidence for effective road investments in developing countries that incorporate poverty alleviation targets. [ABSTRACT FROM AUTHOR]

Statistical quality control is concerned with the analysis of production and manufacturing processes. Control charts are process control techniques, commonly applied to observe and control deviations. Shewhart control charts are very sensitive and used for large shifts based on the basic assumption of normality. Cumulative Sum (CUSUM) control charts are effective for identifying that may have special causes, such as outliers or excessive variability in subgroup means. This study uses a CUSUM control chart problems structure to evaluate the performance of robust dispersion parameters. We investigated the design structure features of various control charts, based on currently defined estimators and some new robust scale estimators using trimming and winsorization in different scenarios. The Median Absolute Deviation based on trimming and winsorization is introduced. The effectiveness of CUSUM control charts based on these estimators is evaluated in terms of average run length (ARL) and Standard Deviation of the Run Length (SDRL) using a simulation study. The results show the robustness of the CUSUM chart in observing small changes in magnitude for both normal and contaminated data. In general, robust estimators MADTM and MADWM based on CUSUM charts outperform in all environments. [ABSTRACT FROM AUTHOR]

In this article an optimal control scheme is proposed to solve robust control problem for matched and unmatched system. In the proposed optimal approach the value functions are designed such that the obtained optimal control law guarantees asymptotic stability of the uncertain nonlinear system. Since the proposed robust optimal control problem is not straightforward to solve, an off‐policy reinforcement‐learning algorithm based on neural networks approximation is developed to obtain robust optimal control law iteratively. The robust control law for matched uncertain systems can be achieved via proposed off‐policy learning algorithm without requiring exact knowledge of system's dynamics. The advantages of the proposed robust optimal controller are verified by comparative simulations on an uncertain model of a car suspension system and a mathematical nonlinear model. [ABSTRACT FROM AUTHOR]

In this article, a dissipativity based discrete time sliding mode controller is proposed for bilateral tele‐operation in presence of communication delays and packet losses. The controllers for both master and slave arm are designed to follow a predefined impedance dynamics with dissipative characteristics. The slave arm controller is designed as a two layered structure. The first layer uses the tracking error between master and slave to create a target velocity profile based on the user defined impedance dynamics. The second layer uses this target velocity profile, slave motion and the contact forces to design a reaching law based discrete time sliding mode controller. A model following reaching law approach is used to design the sliding mode control which alleviates the chattering in the input by removing the impact of the accumulated effects of the past disturbance from the system. Moreover, an adaptive tuning method is used for the switching gain of the sliding mode control so that the controller can be designed even when exact information on the uncertainty bounds are unknown. Numerical simulations are presented for Phantom Omni arm to show the efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

During the last two decades, parallel robots have become more ubiquitous, employed in a great variety of sectors, from food to aerospace industries. In fact, they are much more efficient than their serial counterparts in terms of performing fast motions and consuming less energy. However, due to their mechanical complexity, they present a highly complex non-linear dynamics, which makes the modelling and control tasks difficult. Aiming to improve the performance and robustness of the control laws already used to control this type of mechanisms, previously, the authors proposed two novel laws of hybrid control, implemented in the joint space, in order to improve the dynamic behavior of parallel robots when performing fast motion tasks. Among the goals of the current work, one can mention to adapt the two laws of hybrid control, proposed in the previous work, by implementing them in the task space. Additionally, the peculiarities related to the dynamic formulation and the tuning of controller gains are also shown. Furthermore, a comparison of the performances of the pure and hybrid control techniques, implemented in both joint and task spaces, is presented as well, by executing the same paths and using adequate metrics. In the selected paths, experiments revealed that the hybridization process of pure control laws in the task space provides a significant reduction of the path-tracking and steady-state errors. [ABSTRACT FROM AUTHOR]

In this study, piezoelectric patches are used as actuators to dampen structural oscillations. Damping oscillations is a significant engineering challenge, and the use of piezoelectric patches in smart structures allows for a reduction in oscillations through sophisticated control methods. This analysis involved H-infinity (H∞) robust analysis. H∞ (H-infinity) control formulation is a robust control design method used to ensure system stability and performance under disturbances. When applied to piezoelectric actuators in smart structures, H∞ control aims to design controllers that are robust to variations in system dynamics, external disturbances, and modeling uncertainties, while meeting specified performance criteria. This study outlines the piezoelectric effects and advanced control strategies. A structural model was created using finite elements, and a smart structural model was analyzed. Subsequently, dynamic loads were applied and oscillation damping was successfully achieved by employing advanced control techniques. [ABSTRACT FROM AUTHOR]

The stabilization problem for uncertain discrete‐time singular Markovian jump systems (DSMJSs) with time‐varying delays is comprehensively covered in this paper. An updated Lyapunov–Krasovskii functional is presented via a discrete state decomposition method. With the help of this constructed Lyapunov–Krasovskii functional, some delay‐ and mode‐dependent sufficient conditions for the open‐loop DSMJSs are derived. Based on these circumstances, a memory mode‐dependent state feedback control is used to create a closed‐loop DSMJS with parameter uncertainties that is regular and causal. And then, the stochastically admissible conditions are attained. Through the exact calculation of each decomposition component for the designed memory state feedback controller, the intended memory state feedback controller settings are determined. It should be mentioned that the algorithm suggested in this article expands the controller design's feasibility and flexibility. The numerical results show how the approach is superior to previous ones, and the given results are less conservative. [ABSTRACT FROM AUTHOR]

This article addresses the problem of robust output regulation for uncertain switched systems. A general result is first proposed for the case of uncertain and nonlinear systems. In order to cope with model uncertainties, the proposed approach implements the internal model principle. Local asymptotic stability of the closed‐loop system as well as zero steady state error on the controlled output are proven using Lur'e Lyapunov functions. Then, this result is specialized to the linear case. Sufficient conditions ensuring global or local stability of the closed loop system are provided. Furthermore, a constructive method based on LMI is presented. When only local stability is achieved, outcomes of this procedure are not only the controller gains, but also an estimation of the robust domain of attraction. Finally, illustrative examples are proposed, showing the efficiency of the proposed methods. [ABSTRACT FROM AUTHOR]

The robustness of a linear system in the view of parametric variations requires a stability analysis of a family of polynomials. If the parameters vary in a compact set A$$ A $$, then obtaining necessary and sufficient conditions to determine stability of the family FA$$ {\mathfrak{F}}_A $$ is one of the most important tasks in the field of robust control. Three interesting classes of families arise when A$$ A $$ is a diamond, a box or a ball of dimension n+1$$ n+1 $$. These families will be denoted by FDn$$ {\mathfrak{F}}_{D_n} $$, FBn$$ {\mathfrak{F}}_{B_n} $$, and FSn$$ {\mathfrak{F}}_{S_n} $$, respectively. In this article, a study is presented to contribute to the understanding of Hurwitz stability of families of polynomials FA$$ {\mathfrak{F}}_A $$. As a result of this study and the use of classical results found in the literature, it is shown the existence of an extremal polynomial f(α∗,x)$$ f\left({\alpha}^{\ast },x\right) $$ whose stability determines the stability of the entire family FA$$ {\mathfrak{F}}_A $$. In this case f(α∗,x)$$ f\left({\alpha}^{\ast },x\right) $$ comes from minimizing determinants and in some cases f(α∗,x)$$ f\left({\alpha}^{\ast },x\right) $$ coincides with a Kharitonov's polynomial. Thus another extremal property of Kharitonov's polynomials has been found. To illustrate our approach, it is applied to families such as FDn$$ {\mathfrak{F}}_{D_n} $$, FBn$$ {\mathfrak{F}}_{B_n} $$, and FSn$$ {\mathfrak{F}}_{S_n} $$ with n≤5$$ n\le 5 $$. The study is also used to obtain the maximum robustness of the parameters of a polynomial. To exemplify the proposed results, first, a family FDn$$ {\mathfrak{F}}_{D_n} $$ is taken from the literature to compare and corroborate the effectiveness and the advantage of our perspective. Followed by two examples where the maximum robustness of the parameters of polynomials of degree 3 and 4 are obtained. Lastly, a family FB5$$ {\mathfrak{F}}_{B_5} $$ is proposed whose extreme polynomial is not necessarily a Kharitonov's polynomial. Finally, a family FS3$$ {\mathfrak{F}}_{S_3} $$ is used to exemplify that if the boundary of A$$ A $$ is given by a polynomial equation in several variables, the number of candidates to be an extremal polynomial is finite. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a synthesis method for robust, regret optimal control. The plant is modeled in discrete‐time by an uncertain linear time‐invariant (LTI) system. An optimal non‐causal controller is constructed using the nominal plant model and given full knowledge of the disturbance. Robust regret is defined relative to the performance of this optimal non‐causal control. It is shown that a controller achieves robust regret if and only if it satisfies a robust H∞$$ {H}_{\infty } $$ performance condition. DK‐iteration can be used to synthesize a controller that satisfies this condition and hence achieve a given level of robust regret. The approach is demonstrated two examples: (i) a single‐input, single‐output (SISO) classical design, and (ii) an active suspension for a quarter car model. The SISO example is simple but is intended to provide insight about the robust regret control design. The quarter car example compares the robust regret controllers against regret controllers designed without plant uncertainty. [ABSTRACT FROM AUTHOR]

This paper aims to develop a robust decomposed system control (RDSC) strategy under input constraints for an electro‐mechanical linear actuator (EMLA) facing model uncertainty and external disturbances. At first, a state‐space model of a complex multi‐stage gearbox EMLA system, driven by a permanent magnet synchronous motor (PMSM), is developed, and the non‐ideal characteristics of the ball screw are presented through the model. The result is a four‐order nonlinear strict‐feedback form (NSFF) system decomposed into three subsystems. As the paper's main result, a novel RDSC strategy with uniform exponential stability for controlling subsystem states is presented. This developed controller avoids the "explosion of complexity" problem associated with backstepping by treating the time derivative of the virtual control input as an uncertain system term. The proposed method, despite assuming load disturbances and input constraints with arbitrary bounds, offers a straightforward control approach for a broader range of applications. Further, the controller's performance is evaluated by simulating two distinct duty cycles, each representing different levels of demand on the actuator facing load disturbances near the rated motor performance. [ABSTRACT FROM AUTHOR]

For uncertain multiple‐inputs multi‐outputs nonlinear systems, it is nontrivial to achieve asymptotic tracking due to the intrinsic coupling among inputs, while the controllability conditions in most existing methods are rather restrictive or even impractical especially when unexpected actuator faults are involved. In this article, we focus on extending such controllability condition by resorting to the existence (instead of a priori knowledge) of some feasible auxiliary matrix, upon which a robust adaptive control scheme is first presented in the absence of actuator faults that is not only able to achieve asymptotic tracking even in the presence of non‐parametric uncertainties with all the closed‐loop signals globally ultimately uniformly bounded, but also able to deal with a larger class of system models. Furthermore, for the case with intermittent actuator faults, we develop a fault‐tolerant control scheme with extended condition for controllability that is able to accommodate such faults automatically without using any fault detection or fault diagnosis unit. The effectiveness and benefits of the proposed method are verified via simulation on robotic systems. [ABSTRACT FROM AUTHOR]

This paper proposes an enhanced and robust tracking control method for the class of uncertain and disturbed affine nonlinear systems. The approach is based on predictive sliding mode control (PSMC) to combine the advantages of sliding mode control (SMC) with those of model predictive control (MPC). The resulting controller offers numerous benefits, including high robustness, quick transient response, finite-time convergence, and robustness against uncertainties and external disturbances. However, a significant limitation of the proposed PSMC is its reliance on prior knowledge of the disturbance and uncertainty bounds. To address this drawback, a sliding mode observer (SMO) is synthesised to identify uncertainties and disturbances. The proposed controller successfully eliminates the chattering effect without compromising robustness and precision. The Lyapunov theory is used to prove the stability of the closed-loop system. The effectiveness of the proposed approach is validated through simulations on a well-known benchmark. [ABSTRACT FROM AUTHOR]

During the operation of space gravitational wave detectors, the constellation configuration formed by three satellites gradually deviates from the ideal 60° angle due to the periodic variations in orbits. To ensure the stability of inter-satellite laser links, active compensation of the breathing angle variation within the constellation plane is achieved by rotating the optical subassembly through the telescope pointing mechanism. This paper proposes a high-performance robust composite control method designed to enhance the robust stability, disturbance rejection, and tracking performance of the telescope pointing system. Specifically, based on the dynamic model of the telescope pointing mechanism and the disturbance noise model, an H∞ controller has been designed to ensure system stability and disturbance rejection capabilities. Meanwhile, employing the method of an H∞ norm optimized disturbance observer (HODOB) enhances the nonlinear friction rejection ability of the telescope pointing system. The simulation results indicate that, compared to the traditional disturbance observer (DOB) design, utilizing the HODOB method can enhance the tracking accuracy and pointing stability of the telescope pointing system by an order of magnitude. Furthermore, the proposed composite control method improves the overall system performance, ensuring that the stability of the telescope pointing system meets the 10 nrad/Hz1/2 @0.1 mHz~1 Hz requirement specified for the TianQin mission. [ABSTRACT FROM AUTHOR]

This paper proposes a robust tracking control method for wheeled mobile robot (WMR) against uncertainties, including wind disturbances and slipping. Through the application of the differential flatness methodology, the under-actuated WMR model is transformed into a linear canonical form, simplifying the design of a stabilizing feedback controller. To handle uncertainties from wheel slip and wind disturbances, the proposed feedback controller uses sliding mode control (SMC). However, increased uncertainties lead to chattering in the SMC approach due to higher control inputs. To mitigate this, a boundary layer around the switching surface is introduced, implementing a continuous control law to reduce chattering. Although increasing the boundary layer thickness reduces chattering, it may compromise the robustness achieved by SMC. To address this challenge, an active disturbance rejection control (ADRC) is integrated with boundary layer sliding mode control. ADRC estimates lumped uncertainties via an extended state observer and eliminates them within the feedback loop. This combined feedback control method aims to achieve practical control and robust tracking performance. Stability properties of the closed-loop system are established using the Lyapunov theory. Finally, simulations and experimental results are conducted to compare and evaluate the efficiency of the proposed robust tracking controller against other existing control methods. [ABSTRACT FROM AUTHOR]

Summary: Variable‐pitch quadrotors have demonstrated their capability to enhance control performance and overcome limitations compared to conventional fixed‐pitch quadrotors, while still facing challenges such as nonlinearity, couplings, uncertainties and so on. This article aims to address the robust attitude control problem of variable‐pitch quadrotors afflicted with parametric uncertainties and unpredictable external disturbances. Initially, a practical actuator allocation strategy for the motor‐propeller is proposed, followed by the development of a nonlinear robust attitude tracking controller capable of addressing all uncertainties. The effectiveness of the proposed controller in ensuring exponential stability of the closed‐loop system, thereby driving the attitude tracking error to a small range within a finite time, has been substantiated. To evaluate the control performance, a hardware‐in‐the‐loop testbed is constructed to conduct real‐time experiments. The experimental results from attitude control case, comparative case, and position control case demonstrate that the designed motor‐propeller allocation method and robust controller are effective in achieving a fast response and excellent control performance. [ABSTRACT FROM AUTHOR]

Summary: This work proposes a reinforcement learning control scheme for systems affected by persistent external perturbations. This scheme relies on ℋ∞$$ {\mathscr{H}}_{\infty } $$ and high‐order sliding mode control techniques combined to estimate the parameters with a certain degree of precision and simultaneously attenuate persistent and state‐dependent perturbations. The proposed solution is a novel design technique based on the minimization method via Discontinuous Gradient. The stability of the proposed scheme is proved via the Lyapunov approach. [ABSTRACT FROM AUTHOR]

In response to the high performance requirements of pulse width modulation (PWM) converters in grid-connected power systems, H-Infinity (H∞) control has attracted significant research interest due to its robustness against parameter variations and external disturbances. In this work, an advanced robust H∞ control is proposed for a grid-connected three-phase PWM rectifier. A two-level control strategy is adopted, where cascaded H∞ controllers are designed to simultaneously regulate the DC bus voltage and input currents even under load disturbances and non-ideal grid conditions. As a result, unit power factor, stable DC bus voltage, and sinusoidal input currents with lower harmonics can be accurately achieved. The design methodology and stability of the proposed controller are verified through a comprehensive analysis. Simulation tests and experimental implementation on a dSPACE 1103 board demonstrate that the proposed control scheme can effectively enhance disturbance rejection performance under various operating conditions. [ABSTRACT FROM AUTHOR]

The wind power generation system of a 5 MW horizontal axis wind turbine has a high wind energy conversion efficiency. The proportion of installed capacity in practical production applications is increasing year on year, so that the stability of its operation becomes a central factor in determining the productivity of the wind farm in question. This paper takes a 5 MW wind turbine as the research object and proposes a parameter‐adaptive robust model predictive control method to achieve self‐optimization of controller parameters through a Bayesian optimization approach. A robust model predictive control strategy, aiming to reduce the power fluctuation while maximizing the power output, is developed in this paper to enhance the dynamic economic performance under uncertain wind speed variation. A Bayesian algorithm is used in this paper to optimize the parameters of the controller. Moreover, wind speeds are simulated using TurbSim for different turbulence intensities of 5%, 10%, and 15% turbulence. Finally, the robust model predictive control toolbox in MATLAB is designed and simulated. The results show that the operational instability of the wind energy system is overcome. Meanwhile, the robustness of the wind energy system operation is improved compared to the traditional model predictive control approach. [ABSTRACT FROM AUTHOR]

This paper deals with a discrete-time observer-based state feedback control design by taking into consideration bounded parameter uncertainty, actuator faults, and stochastic noise in an inner control loop which is extended in a cascaded manner by outer PI- and P-control loops for velocity and position regulation. The aim of the corresponding subdivision of the quadrotor model is the treatment of the control design in a systematic manner. In the inner loop, linear matrix inequality techniques are employed for the placement of poles into a desired area within the complex z-plane. A robustification of the design towards noise is achieved by optimizing both control and observer gains simultaneously guaranteeing stability in a predefined bounded state domain. This procedure helps to reduce the sensitivity of the inner control loop towards changes induced by the outer one. Finally, a model-based optimization process is employed to tune the parameters of the outer P/PI controllers. To allow for the validation of accurate trajectory tracking, a comparison of the novel approach with the use of a standard extended Kalman filter-based linear-quadratic regulator synthesis is presented to demonstrate the superiority of the new design. [ABSTRACT FROM AUTHOR]

This article discusses a quantiser-based stabilisation problem for uncertain nonlinear systems with the aid of robust $ \mathcal {[K, KL]} $ [ K , KL ] sector. We confirmed that the quantised-feedback control steers the state trajectories of the uncertain nonlinear systems within the robust $ \mathcal {[K, KL]} $ [ K , KL ] sector in finite time by adjusting the quantisation parameters. Furthermore, control-Lyapunov functions are helpful to obtain sufficient conditions for ensuring the closed-loop system's asymptotic stability and the reachability of the robust $ \mathcal {[K, KL]} $ [ K , KL ] sector. Finally, a nonlinear electronic circuit is provided to test the effectiveness of the designed control law. [ABSTRACT FROM AUTHOR]

This paper proposes a novel, robust flight control system using adaptive nonlinear sliding mode control for a quadrotor UAV in the presence of parametric uncertainties and aerodynamical disturbances. The proposed control system is based on a proportional derivative sliding surface combined with a non-singular fast terminal sliding mode control to enhance the tracking accuracy and reduce the chattering influence. Moreover, an adaptive mechanism is proposed to approximate the unknown upper limit of external disturbances/uncertainties. The Lyapunov criteria is used to prove the closed-loop stability and calculate the adaptive mechanism. The proposed adaptive PD-NFTSMC (APD-NFTSMC) can cope with the negative influence of modeling uncertainties, external disturbances, and measurement noise, allows null error in the steady state, and solves the chattering problem. Moreover, intensive simulation experiments under various external conditions are carried out to highlight the sovereignty of the developed control approach. Finally, comparisons with some well-known control techniques are performed to show the usefulness, smoothness, and robustness of the proposed APD-NFTSMC strategy. [ABSTRACT FROM AUTHOR]

Due to its attractive features of bidirectional power flow, zero-voltage switching (ZVS), high power density, and electric isolation, the current source-based isolated dual-active-bridge (IDAB) dc–dc converter is widely employed in various renewable energy applications. Efficacy and sublime dynamic performance are two primary control objectives for IDAB-dc–dc converter. Recently a single-phase shift-based fast current controller (SPS-FCC) was proposed to enhance the dynamic performance of the IDAB-dc–dc converter. However, this control technique suffers from high current stresses when the voltage ratio between two bridges deviates from 1, which can affect the overall efficiency of the converter. A typical extended-phase shift (EPS) control scheme can substantially improve the converter efficiency by minimizing these current stresses, but it cannot meet the robust dynamic response requirements. To overcome the drawbacks of SPS-FCC and EPS, this study proposes a novel EPS-based fast current controller for current source-based IDAB-dc–dc converters (EPS-FCC). The proposed control strategy combines the high efficiency of EPS and the robust dynamic performance of FCC. Thus, the IDAB-dc–dc converter implemented with the proposed control technique has the advantages of excellent dynamic response and high efficiency under light load conditions. Moreover, the proposed controller is cost-effective compared to SPS-FCC as for the same transmission power, the electric equipment with low current ratings can be selected. To confirm the effectiveness of the proposed control scheme, a 300 W IDAB-dc–dc converter prototype is developed. Different test cases are designed, and the proposed control technique is compared in detail with SPS-FCC and EPS control schemes under these test cases. The experimental results have validated the effectiveness of the proposed control technique. [ABSTRACT FROM AUTHOR]

The coupled systems with numerous interdependent variables pose considerable control and stability issues in commercial chemical processes. These systems exhibit complex interactions, time delays, parameter uncertainties and disturbances, which can lead to poor performance and reduced productivity. Conventional single-loop controllers struggle to effectively manage the interactions between variables, leading to poor disturbance rejection and tracking accuracy. A more robust and efficient control strategy is essential to tackle these limitations. Hence, a robust decentralized PID controller design is proposed to address the shortcomings of coupled industrial chemical processes. The aim is to enhance control system performance by achieving better disturbance rejection and tracking accuracy, thereby improving process efficiency and product quality. The complementary sensitivity function is exploited to attain this, and a novel graphical tuning method is proposed for obtaining optimal PID controller parameters. The use of the H ∞ robust criterion ensures robust stability and minimizes the influence of external disturbances. The proposed approach offers an efficient means to design robust decentralized controllers for complex chemical processes. The simulation results demonstrate the effectiveness of the method compared to existing controllers. Numerically, the proposed controller is able to attain almost a 20 % reduction in integral absolute error and a 30 % decrease in the settling time for all cases compared to existing controllers. The graphical tuning method enables efficient parameter optimization, resulting in faster response times and reduced settling time. This work represents a significant step toward achieving enhanced control system performance and stability in coupled industrial chemical processes. [ABSTRACT FROM AUTHOR]

The robust stability assessment of the second order plus interval time delay (SOPITD) plant controlled by Fractional-Order Proportional Integral Derivative (FOPID) controllers is the focus of this research. A simple graphical procedure for analyzing the robust stability of the interval system is presented based on the zero exclusion condition and the value set concept. The incorporation of an auxiliary function, derived through a judicious application of fundamental geometric principles intrinsic to convex polygons, serves to significantly alleviate the complexity and facilitate the application of the robust stability analysis approach, thereby affording a more streamlined and efficient means of designing robust control systems. Moreover, the computational burden for the robust stability analysis is also reduced by novel bounds. Moreover, a novel robust performance checking function is provided to improve the performance system. Three illustrative examples are then given to support the findings and show their applicability. [ABSTRACT FROM AUTHOR]

In this paper, a fixed-time sliding mode control scheme is developed to fulfill the trajectory tracking task of a marine surface vehicle with unknown dynamics. To restrain the adverse effects of the unknown dynamics including the parameter inaccuracy and exogenous disturbances, a fixed-time disturbance observer is designed to estimate the lumped uncertainties using the bi-limit homogeneous theory without requiring any knowledge of the model uncertainties. Then, a nominal tracking controller is proposed to stabilize the error dynamic model in the sense of fixed-time Lyapunov stability, based on which a novel integral-type sliding mode manifold with bi-limit homogeneity is constructed to drive tracking error convergence in fixed time. To enhance the robustness of the vessel control system, a disturbance observer–based fixed-time integral sliding mode tracking controller is finally proposed, and the chattering phenomenon is effectively alleviated by direct estimation compensations. The analysis of Lyapunov stability indicates that the closed-loop system is fixed-time stable. Numerical simulations on a model vessel are carried out to validate theoretical results of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach for designing estimators to achieve consensus in uncertain multi-agent systems (MAS), even when various fault conditions are present and communication is assumed to be undirected and connected. The method includes an adaptive fault detection technique to detect faults and a unique adaptation in the unscented Kalman filter (UKF) to adjust noise covariance matrices and reconstruct uncertain states in the MAS is proposed in the framework of Q-learning. Additionally, it involves training neural network internal parameters using previous measurements. A Chebyshev neural network (CNN) is employed to model the uncertain plant, and a hyperbolic tangent-based robust control term is used to mitigate neural network approximation errors. This novel approach is known as reinforced UKF (RUKF). The paper also discusses the asymptotic stability of the proposed method and presents numerical simulations to demonstrate its effectiveness with reduced computational load. [ABSTRACT FROM AUTHOR]

This paper develops an algorithm for synthesizing negative imaginary (NI) systems with a specified H∞-norm bound by exploiting the convex relaxation technique in the static output-feedback (SOF) control design framework. This scheme improves the robustness objective since the present framework can handle both NI and H∞-norm-bounded unstructured uncertainty of the system. The non-strict inequality involved in the NI system description that creates a major difficulty in the SOF control design, can efficiently be tackled by the developed convex relaxation-based iterative algorithm. The advantages of the algorithm are shown using several examples and the results are compared with the existing works. [ABSTRACT FROM AUTHOR]

This work introduces an innovative robust partial state feedback controller designed for robotic manipulators actuated by brushless DC motors. The proposed controller/observer structure relies solely on actuator current and robot joint position measurements, while effectively compensating for dynamic uncertainties in both the electrical (actuator dynamics) and mechanical (robot's dynamical terms) subsystems. Specifically, a model–based robust observer, eliminating the need of joint velocity measurements, is combined with a backstepping‐type controller design. As opposed to the previous model based observers that depend on the actual model parameters, the proposed observer structure utilizes the best guest estimates of the system parameters supported with a robust compensation term. This approach eliminates the need for precise knowledge of system parameters of the observer design which is a significant improvement over most of the previous results. This approach ensures the semi‐global, uniformly ultimately bounded joint tracking error signal. The overall stability of the closed‐loop system is affirmed through Lyapunov‐based arguments. Experimental studies conducted on an in‐house‐built two‐link robotic manipulator, actuated by brushless DC motors, are presented to demonstrate the effectiveness and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is aimed at performing a comprehensive review of the approaches employed in nanosatellite platforms, specifically 1 U and 3 U, for electrical power systems (EPS). Moreover, it seeks to develop a robust maximum power point tracking (MPPT) controller using the sliding mode control (SMC) method. The proposed control strategy is intended to monitor the solar panel's maximum power point (MPP) and adapt to changes in temperatures and solar irradiance in low Earth orbit (LEO). The EPS model, designed with the proposed sizing method, is built in MATLAB-Simulink and integrates a solar panel, battery storage, and power converters controlled by diverse MPPT methods. Then, simulation results demonstrate the effectiveness of the proposed SMC approach compared to other conventional control methods for the designed EPS under varying LEO conditions. To achieve a robust validation of the most appropriate MPPT control method under steady-state conditions, this paper presents an experimental investigation into the proposed EPS hardware design. The proposed SMC method achieved an increase in power generation from 10% to 12% for buck and boost power converters, respectively, compared to traditional control methods. [ABSTRACT FROM AUTHOR]