Robust Hybrid Control Research Articles

A Novel Robust Hybrid Control Strategy for a Quadrotor Trajectory Tracking Aided with Bioinspired Neural Dynamics

This paper introduces a novel hybrid control strategy for quadrotor UAVs inspired by neural dynamics. Our approach effectively addresses two common issues: the velocity jump problem in traditional backstepping control and the control signal chattering in conventional sliding mode control. The proposed system combines an outer-loop bioinspired backstepping controller with an inner-loop bioinspired sliding mode controller, ensuring smooth trajectory tracking even under external disturbances. We rigorously analyzed the system’s stability using Lyapunov stability theory. To validate our algorithm’s effectiveness, we conducted trajectory tracking experiments in both disturbance-free and step-disturbance conditions, comparing it with the traditional backstepping control, conventional sliding mode control, and saturated sliding mode control. The results demonstrate that our algorithm not only tracks trajectories more effectively but also significantly outperforms these methods in suppressing velocity jumps and signal chattering.

Robust non-fragile hybrid control for delayed uncertain singular impulsive jump systems based on improved impulse instant-dependent auxiliary functions method

This article researches the issue of robust non-fragile hybrid control for delayed uncertain singular impulsive jump systems (USIMJSs). The key aim is to design non-fragile hybrid state feedback controllers (including a non-fragile normal state feedback controller and a non-fragile impulsive state feedback controller), which are insensitive to the uncertainties of gains of controllers and can provide sufficient tuning margins. The non-fragile normal state feedback controller can eliminate the internal impulses and overcome the external disturbances; the non-fragile impulsive state feedback controller can suppress the interference of external unstable impulses and restrain the instantaneous jumps caused by Markovian modes switching. By introducing impulse instant-dependent auxiliary functions, the improved impulse-time-dependent Lyapunov–Krasovskii functional is constructed, which can capture the information of the impulse instants and Markovian jump modes. Novel criteria of robust admissibilization for delayed USIMJSs are acquired under linear matrix inequalities framework. Lastly, the effectiveness of the derived algorithm and designed method is confirmed by simulation examples including a direct current motor-controlled inverted pendulum device and a Quarter-Car active suspension model.

Robust hybrid control strategy for active power management in Kabertene wind farm within Algeria’s PIAT grid

The paper introduces a hybrid control strategy for optimised active power management in Algeria's Kabertene wind farm, crucial for the pole insalah-adrar-timimoune (PIAT) grid's stability. This strategy merges simultaneous interconnection and damping assignment (SIDA) passivity theory, passivity-based control (PBC), and multivariable proportional-integral-derivative (PID) controllers. This combined approach ensures frequency and voltage stability within the PIAT grid, which encompasses various elements like wind farms, solar plants, gas turbines, and dynamic impedance (Z), current (I), and active power (P) (D-ZIP), load model. By tailoring controllers for doubly fed induction generators (DFIGs) using SIDA-PBC principles and optimising internal parameters, the strategy achieves precise control of active power output. Additionally, particle swarm optimisation (PSO) refines power scheduling, which is especially beneficial for intermittent renewable sources like DFIGs. This comprehensive strategy offers numerous advantages: improved network stability, minimized voltage deviations, reduced frequency fluctuations, and enhanced integration of renewable energy sources. The paper emphasises practical implementation considerations, providing valuable guidance for efficient Kabertene wind farm operation and integration. This research contributes significantly to fostering cleaner and more reliable energy systems, facilitating the PIAT grid's transition towards sustainable energy generation.

Designing robust hybrid controllers for enhancing output voltage regulation in CPL feed boost converters through backstepping and nonsingular fast terminal sliding mode approaches

This paper presents a novel and robust hybrid controller that combines the backstepping controller with the nonsingular fast terminal sliding mode controller (NFTSMC) for DC-DC boost converters (DDBCs) operating alongside constant power loads (CPLs). The primary aim of the controller is to enhance the stability of the DC-bus voltage while consistently delivering power to the CPL. To achieve this objective, the exact feedback linearization approach is applied to transform the nonlinear dynamical model of the DDBC into Brunovsky’s canonical forms. The incorporation of matched uncertainties into the dynamical model illustrates the robustness of the proposed control approach. The hybrid controller is formulated based on this model, leveraging Lyapunov stability theory to ensure large signal stability under the designated control law. Significantly, the NFTSMC effectively addresses the singularity problem associated with sliding mode controllers (SMCs). The effectiveness and resilience of the proposed controller are validated under variations in input voltage, reference voltage, and power demand. Comparative analysis is conducted by contrasting simulation results with those obtained using conventional SMC (CSMC) and a typical PI controller (PIC). The results unequivocally highlight the superiority of the proposed controller in terms of ensuring system stability and providing a rapid response across various operating modes. Furthermore, to authenticate the practical applicability of the proposed controller, processor-in-loop (PIL) validation is employed, confirming its effectiveness in real-world scenarios.

A stochastic variance reduction gradient-based GSO-ANFIS optimized method for maximum power extraction of proton exchange membrane fuel cell

Proton Exchange Membrane Fuel Cells (PEMFCs) play a pivotal role in the clean energy landscape, yet their efficiency is contingent upon effective power optimization. This paper presents Maximum PowerPoint Tracking (MPPT) control schemes for PEMFCs, focusing on a ground-breaking methodology. Traditional MPPT controllers are instrumental in maintaining optimal performance; however, they often struggle with dynamic operating conditions. In response to this challenge, this research work presents a pioneering MPPT control scheme employing a stochastic variance reduction gradient system. The novelty of this approach lies in its fusion with the Glow Swarm Optimization (GSO) and the Adaptive Neuro Fuzzy Inference System (ANFIS), resulting in a robust hybrid controller. In the pursuit of optimizing the PEMFC system, the proposed GSO-ANFIS controller is subjected to rigorous testing under dynamic variations in both PEMFC temperature and load. Notably, PEMFCs, due to fluctuations in pressure and temperature, exhibit stochastic behaviour, forming a Gaussian surface. In this research, the popular Perturb and Observe (P&O) and Incremental Conductance methods are evaluated alongside the newly introduced GSO-ANFIS model. The proposed GSO-ANFIS controller outperforms its counterparts, showcasing an impressive accuracy level of 89.97%. In contrast, the Artificial Neural Network (ANN) achieves 80.33% accuracy, and the standalone ANFIS controller attains 86.5% accuracy. This disparity underscores the efficacy and potential of the novel hybrid approach, which not only adeptly handles the stochastic nature of PEMFCs but also significantly enhances accuracy in power optimization. This research not only contributes a valuable addition to the field of MPPT control but also offers a promising trajectory for the future development of efficient and reliable PEMFC systems.

A Multi-Terminal Control Method for AC Grids Based on a Hybrid High-Voltage Direct Current with Cascaded MMC Converters

The hybrid high-voltage direct current (HVDC) transmission system with cascaded MMC converters has become a promising alternative for possessing the technical merits of both line-commuted converter (LCC) and voltage source converter (VSC), resulting in favorable characteristics and potential control of good prospect. This paper pays heightened attention to the feasible power and DC voltage control modes of a hybrid HVDC system; characteristics of master–slave control show higher flexibility than the LCC-VSC HVDC system, which demonstrates that the exceptional potential can serve to stability support the AC power grids. To optimize the control effect, besides damping level to attenuate power oscillations, the robustness suitable for various faults is also considered to obtain a multi-objective control problem. A detailed solution is proceeding using the TLS-ESPRIT identification algorithm and H2/H∞ hybrid robust control theory. This motivates multi-terminal controllers in the LCC rectifier and MMC inverters, which immensely improve the stability of both sending and receiving girds at the same time. According to the parameters of the actual hybrid HVDC project, the simulation model is established in PSCAD v4.6.2 software, and proposed control methods have been verified to satisfy damping objectives and perform well in multiple operating scenarios.

Enhancing aerial robots performance through robust hybrid control and metaheuristic optimization of controller parameters

Enhancing aerial robots performance through robust hybrid control and metaheuristic optimization of controller parameters

Adaptive robust control for biped walking under uncertain external forces

Adaptability and robustness are important expressions of the intelligent walking ability of biped robots. This paper is concerned with the problem of dynamical biped walking and robust control of biped robots under external forces. Due to the characteristics of strong coupling and hybrid, the robotic system is modeled as a rigid kinematic chain with Lagrange equations. A novel adaptive feedback controller is proposed based on sliding mode control (SMC) and hybrid zero dynamics. The novelty of the proposed work lies in taking the uncertainty of upper-bound error into consideration. The hybrid robust control is mentioned to approximate unknown dynamic functions with the adaptive weight. The restricted Poincare return map is utilized to analyze the stability of a nonlinear impulsive system. It ensures that the flow of the continuous subsystem can pass through the impact cross section. Finally, the simulation results illustrate that the proposed adaptive SMC control system can favorably track the reference trajectories, even when a fault occurs, which verifies the effectiveness of the proposed method.

Adaptive Backstepping Integral Sliding Mode Control of a MIMO Separately Excited DC Motor

This research proposes a robust nonlinear hybrid control approach to the speed control of a multi-input-and-multi-output separately excited DC motor (SEDCM). The motor that was under consideration experienced parametric uncertainties and load disturbances in the weak field region. The proposed technique aims to merge the benefits of adaptive backstepping (AB) and integral sliding mode control (ISMC) to enhance the overall system’s robustness. The unknown parameters with load disturbances are estimated using an adaptation law. These estimated parameters are incorporated into the controller design, to achieve a highly robust controller. The theoretical stability of the system is proved using the Lyapunov stability criteria. The effectiveness of the proposed AB–ISMC was demonstrated by simulation, to track the reference speed under parametric uncertainties and load disturbances. The control performance of the proposed technique was compared to that of feedback linearization (FBL), conventional sliding mode control (SMC), and AB control laws without and with the adaptation law. Regression parameters, such as integral square error, integral absolute error, and integral time absolute error, were calculated to quantitatively analyze the tracking performance and robustness of the implemented nonlinear control techniques. The simulation results demonstrated that the proposed controller could accurately track the reference speed and exhibited robustness, with steady-state error accuracy. Moreover, AB–ISMC overperformed, compared to the FBL, SMC, AB controller without adaptation law and AB controller with adaptation law, in reducing the settling time by factors of 27%, 67%, 23%, and 21%, respectively, thus highlighting the superior performance of the proposed controller.

Robust hybrid nonlinear control approach for stability enhancement of a constant power load DC-DC boost converter

This paper presents a robust hybrid super-twisting reaching law-based sliding mode controller in conjunction with a complementing recursive backstepping controller for DC-DC boost converters with constant power loads (CPLs). The key control goal is to keep the DC-bus voltage steady and constant while continuously powering the CPL. The nonlinear dynamical model of the DC-DC boost converter is translated into Brunovsky’s canonical forms, utilizing the precise feedback linearization technique to attain this control goal. It is worth mentioning that the dynamical model has been modified with bounded external uncertainties to demonstrate the restraint performance for huge loads and input voltage variations. The proposed hybrid controller is then constructed using this model. Furthermore, to ensure the large signal stability of the whole system under the designed control law, the Lyapunov stability theory is used. Numerical simulation analysis are carried out in MATLAB/Simulink to validate the performance of the designed robust controller for a DC–DC boost converter feeding a CPL when the operating point change. The results show that the designed controller outperforms both existing nonlinear controllers and a traditional PI controller in terms of ensuring the system’s stability and fast response in a variety of operating modes. Finally, in order to confirm the theoretical design and simulation results of the designed robust hybrid controller, experimental results are also provided in this paper.

Robust Discrete-Time Hybrid Controller for Non-Inverting Buck-Boost DC-DC Converter

Petro-Processors of Louisiana, Inc. (PPI) site, located North of the city of Baton Rouge Parish, used two sites as depositories for various petrochemical wastes from mainly the 1960s until the 1980s. The main problem was the potential for leachate migration and for exposure of toxic materials, which had been released into local waterways. Therefore, the site is considered a public health hazard area because of risks to human health from past, present, and future exposure to hazardous substances. This study focuses on investigating selected chlorinated organic liquids, which are the predominant contaminants among all wastes: Hexachlorobenzene (HCB) and Hexachlorobutadiene (HCBD) with possible health effects using a risk assessment study. The results show that even though the petrochemical waste disposal has completely shut down since1980, it will still take an average of the HCB and HCBD to reach the domestic well with groundwater is 68 years and 57 years, respectively via slow migration, which will increase the cancer risks for the people who live near PPI site. Our results indicated that the cancer risks of exposure to HCB and HCBD are 4.6x10-6 and 2.6x10-3, respectively, which are more than the 10-6 goal. In addition, this study can be used at similar sites and for different compounds to investigate the potential impacts of pollutants on human health.

A Hybrid Robust Adaptive Sliding Mode Controller for partially modelled systems: Discrete-time Lyapunov stability analysis and application

This work presents a new discrete-time Hybrid Robust Adaptive Sliding Mode Controller, developed from the union of a Robust Model Reference Adaptive Controller, an Adaptive Sliding Mode Controller, and an Adaptive One Sample Ahead Preview Controller in an unique control structure. Robust Model Reference Adaptive Controller is an adequate direct adaptive control strategy to control partially known plants, but can present slow closed-loop response to ensure global stability. Therefore, an adaptive One Sample Ahead Preview controller is incorporated to accelerate transient regimes, once it tries to track reference signal in one sample. Furthermore, an adaptive Sliding Mode Controller is also merged in the controller structure to help controller performance in transient regime and it also improves relevantly the steady state response in a scenario of several unmodelled dynamics Stability analysis of this controller using Lyapunov criterion and its robustness proof are provided, considering the plant subjected to unmodelled dynamics, which provides controller design constraints. These proofs show the controller is globally stable, and the tracking error tends to a residual set in steady state, even in the presence of matched and unmatched dynamics. Numerical simulations of the Hybrid Robust Adaptive Sliding Mode Controller applied on an unstable nonminimum-phase plant are presented, where only part of the overall plant is take into consideration for controller design. Results corroborate the feasibility and robustness of the developed control strategy and the performance superiority when compared to an adaptive One Sample Ahead Preview controller, with a 75% tracking error reduction in a scenario of several unmodelled dynamics.

Iterative Learning Hybrid Robust Predictive Control for Multi-Phase Batch Processes with Asynchronous Switching via a Lyapunov-Razumikhin Approach

Iterative Learning Hybrid Robust Predictive Control for Multi-Phase Batch Processes with Asynchronous Switching via a Lyapunov-Razumikhin Approach

Robust Hybrid Control Strategy PI-Sliding Mode Control of a STATCOM in the Presence of a Decentralized PV Source

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Adaptive robust finite-time tracking control for quadrotor subject to disturbances

Quadrotors are extremely agile UAVs with many unknowns regarding their moment of inertia, drag coefficients, and mass. Aside from aerodynamic turbulence, the quadrotor has a high level of nonlinearity due to its underactuated mechanical system. These last two factors cause issues that necessitate adaptive and robust control. A hybrid robust nonlinear control approach for a quadrotor is described in this research paper. To address the quadrotor trajectory tracking problem, a combination of backstepping and sliding-mode approaches based on proportional integral derivative (PID) surfaces is developed, with the Lyapunov method used to evaluate the control system’s stability. The adaptive technique, in conjunction with sliding-mode and super-twisting algorithm, is then investigated in order to reduce the chattering impact of sliding mode control and estimate the various controller parameters. Super-twisting adaptive backstepping PID sliding mode approach for the quadrotor rotational and translational subsystems is presented to reduce error convergence time and improve speed tracking performance. The simulation results under various scenarios (parameters uncertainties under Gaussian random disturbances, constant and time-varying external disturbance) are given to demonstrate the efficacy and practicability of the proposed control. A comparative analysis is performed with different developed controllers using the performance of the integral of absolute error and the integral of the absolute value of the derivative of the control inputs to demonstrate the superiority and effectiveness of the designed control technique.

A linear hybrid active disturbance rejection controller design to extenuate powerline bushfires in resonant grounded distribution power systems

This paper proposes a robust linear hybrid controller by combining the active disturbance rejection and proportional–integral controllers (ADRC+PI) for inverter-based arc suppression coils (ASCs) in resonant grounded distribution power systems (RGDPSs). Resonant grounding techniques are used in real power distribution networks for reducing the fault current in order to reduce the severity of powerline bushfires in the presence of single line-to-ground (SLG) faults. The severity of bushfire hazards due to these SLG faults depends on environmental conditions (e.g., wet or dry grounds) that define the behavior of the system. With respect to these conditions, the fault resistance will be lower for wet grounds for which the system model comprises one dominant pole while dry grounds force the system to have one dominant zero with two dominant poles. By considering the circumstances of such groundings, the behavior of power distribution systems changes when there are SLG faults. This paper investigates a detailed analysis in frequency- and time-domains to design a robust arc mitigator based on the hybrid ADRC+PI controller. Furthermore, the robustness of the proposed hybrid controller against the input disturbances is explored in terms of transient and steady-state stability analysis and the results are compared with the ADRC and PI controllers. In addition, the performance of the proposed hybrid ADRC+PI controller is justified by utilizing virtual- and real-time implementations in a digital signal processor (DSP) through MATLAB/SIMULINK platform on a 22 kV (line-to-line) RGDPS under distinctive grounding conditions.

Improved radial basis function artificial neural network and exact-time extended state observer based non-singular rapid terminal sliding-mode control of quadrotor system

PurposeThe purpose of this paper is to design a hybrid robust tracking controller based on an improved radial basis function artificial neural network (IRBFANN) and a novel extended-state observer for a quadrotor system with various model and parametric uncertainties and external disturbances to enhance the resiliency of the control system.Design/methodology/approachAn IRBFANN is introduced as an adaptive compensator tool for model and parametric uncertainties in the control algorithm of non-singular rapid terminal sliding-mode control (NRTSMC). An exact-time extended state observer (ETESO) augmented with NRTSMC is designed to estimate the unknown exogenous disturbances and ensure fast states convergence while overcoming the singularity issue. The novelty of this work lies in the online updating of weight parameters of the RBFANN algorithm by using a new idea of incorporating an exponential sliding-mode effect, which makes a remarkable effort to make the control protocol adaptive to uncertain model parameters. A comparison of the proposed scheme with other conventional schemes shows its much better performance in the presence of parametric uncertainties and exogenous disturbances.FindingsThe investigated control strategy presents a robust adaptive law based on IRBFANN with a fast convergence rate and improved estimation accuracy via a novel ETESO.Practical implicationsTo enhance the safety level and ensure stable flight operations by the quadrotor in the presence of high-order complex disturbances and uncertain environments, it is imperative to devise a robust control law.Originality/valueA new idea of incorporating an exponential sliding-mode effect instead of conventional approaches in the algorithm of the RBFANN is used, which makes the control law resistant to model and parametric uncertainties. The ETESO provides rapid and accurate disturbance estimation results and updates the control law to overcome the performance degradation caused by the disturbances. Simulation results depict the effectiveness of the proposed control strategy.

Spherical Wrist With Hybrid Motion-Impedance Control for Enhanced Robotic Manipulations

This article presents a back-drivable spherical wrist with smart compliance for rendering human wrist-like capabilities in robotic applications. In order to synthetically impose both motion accuracy and active compliance for dedicated wrist manipulations, a robust hybrid control method is proposed that can switch between motion control (at free motion) and impedance control (at interactions with the environment). A sliding manifold is formulated so that when the control law drives the sliding manifold to zero, the motion/impedance errors will automatically converge to bounded regions despite system uncertainties/inaccuracies. Due to the direct-drive configuration of the proposed spherical wrist, the contact torque can be precisely estimated with an observer, providing an intuitive criterion of contact based on which the control modes can switch autonomously without external force/torque sensors and predefined geometric boundaries that are usually required in conventional hybrid force/position control. The concept is validated on a spherical wrist test-bed in the context of a throat swabbing process. The performance of the hybrid motion-impedance control evaluated against conventional impedance and admittance control methods demonstrate that the proposed spherical wrist enables a robotic system with both fine manipulations and smooth compliant interactions in wrist space.

Boost Converter Based 3-phase AC-AC Active Tracking Voltage Regulator Controlled by a Robust Hybrid Control Method

In this study, a switch-mode three-phase active tracking AC-AC voltage regulator based on the boost converter is proposed with a moderate number of active and passive elements used in the topology. A robust hybrid control, where a novel designed feedforward controller supports the closed-loop PID controller, is proposed for the control of the regulator apart from similar studies in the literature. Active tracking response of the reference output phase voltages is augmented by the proposed hybrid control method. Thus nearly close to sine-wave output phase voltages can be obtained, whether the input AC phase voltages are ideal pure sine or not. Also, the modular structure of the regulator topology enables independent control for each output phase. Thus, the supply of balanced/unbalanced wye-connected three-phase loads or independent single-phase loads with nearly close to ideal sine wave voltages can be achieved by the modularity of the regulator. Both experimental and simulation test studies are performed for the proposed regulator system. A laboratory set-up for the regulator is designed for 0-200 Vp input phase voltages (50 Hz), and 0-300 Vp output phase voltages, and 1.8 kW output power. The achieved results for both simulation and experimental tests verify the proposed switch-mode boost-type regulator’s ability to provide output phase voltages nearly close to sine wave with total harmonic distortion (THD) values under 5%.

Adaptive Backstepping Integral Sliding Mode Control Combined with Super-Twisting Algorithm For Nonlinear UAV Quadrotor System

Quadrotors are extremely agile UAVs with many uncertainties related to their moment of inertia, drag coefficients, and mass. Besides aerodynamic turbulence, the quadrotor is rich in non-linearity due to its underactuated mechanical system. These last two factors lead to problems that require adaptive and robust control. This research paper describes a new hybrid robust nonlinear control technique for a quadrotor. First, a combination of backstepping and sliding-mode approaches based on proportional integral derivative modified surfaces is developed to address the quadrotor trajectory tracking problem, where the Lyapunov method is used to evaluate the control system's stability. Second, adaptive technique combined with sliding mode control to estimate the various parameters of the proposed controller. Super-Twisting algorithm is examined in order to minimize the chattering impact of sliding mode control. To reduce the error convergence time and to increase the performance of speed tracking, a novel super-twisting adaptive backstepping PID sliding mode approach is presented for the quadrotor rotational and translational subsystems. Simulation results are shown to demonstrate the efficacy and practicality of the proposed control. To illustrate the superiority and the designed control technique's effectiveness, a comparative analysis is performed with different newly developed controllers.