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Upper limb prostheses are commonly propelled by pneumatic artificial muscles organized in an antagonistic arrangement. Nonetheless, the control of upper limb prostheses under changing/unknown situations is difficult and necessary for a variety of real-world applications. Adaptive control, learning-based control, and robust control have been studied to deal with such challenges. However, their adaptability is insufficient for prostheses used in daily life, which are exposed to variable task levels, user motor characteristics, and prosthetic features. This paper introduces a highly adaptive controller for the first time based on Generative Adversarial Nets and proportional–integral–derivative controller (G-PID controller). G-PID controller comprises a generator for generating compensation actions to enhance PID responsiveness when controlling the unknown/changing system. Moreover, it incorporates a discriminator that receives responses from both a user-preselected reference system and the compensated changing/unknown system, and simultaneously determines the source of these responses. Through continuous updates, the compensator modifies the response of unknown/changing system to align with the reference system, thereby facilitating adaptive control. The G-PID controller's effectiveness is evaluated through 1-degree of freedom (DoF) joint and 2-DoF shoulder prostheses in simulation experiments, and further validated in prototype experiments focusing on online learning for unknown and time-varying payload. The results demonstrate its ability to deal with diverse types of unknowns/changes, marking a significant advancement towards incorporating prostheses seamlessly into daily life. [ABSTRACT FROM AUTHOR]

PI-PD controllers have superior performance compared to traditional PID controllers, especially for controlling unstable and integrating industrial processes with time delays. However, computing the four tuning parameters of this type of controller is not an easy task. Recently, there has been significant interest in determining the tuning rules for PI-PD controllers that utilize the stability region. Currently, most tuning rules for the PI-PD controller are presented graphically, which can be time-consuming and act as a barrier to their industrial application. There is a lack of analytical tuning guidelines in the literature to address this shortfall. However, the existing analytical tuning guidelines do not consider a rigorous design approach. This work proposes new robust analytical tuning criteria based on predefined gain and phase margin bounds, as well as the centroid of the stability region. The proposed method has been tested using various simulation studies related to a DC–DC buck converter, a DC motor, and a heat exchanger. The results indicate that the proposed tuning rules exhibit strong performance against parameter uncertainty with minimal overshoots. Furthermore, the suggested technique for simultaneous control of yaw and pitch angles has been tested in a real-time application using the twin rotor multi-input multi-output system (TRMS). Real-time results indicate that, compared to other methods under investigation, the suggested approach provides nearly minimal overshoots. [ABSTRACT FROM AUTHOR]

Gas turbine engines have several advantages over piston reciprocating engines, such as higher output per unit volume, reduced vibration, rapid acceleration and deceleration, high power output, and clean exhaust gases. As a result, their use for propulsion in ships has been steadily increasing. However, gas turbine engines exhibit significant parameter variations depending on the rotational speed, making the design of controllers to ensure system stability while achieving satisfactory control performance, a very challenging task. In this paper, a novel CEM-based 2-DOF PID controller design technique is proposed to ensure the stability of a gas turbine engine while improving tracking and disturbance rejection performance. The proposed controller consists of a PID controller focused on enhancing disturbance rejection performance and a set-point filter to improve tracking performance. The set-point filter is composed of gains from the controller and a single weighting factor. When tuning the gains of the controller, the maximum sensitivity is considered to maintain an appropriate balance between system stability and response performance. The key novelty of this study can be summarized in two main points. One is that the controller is designed by matching characteristic equations, and by setting the roots of the desired characteristic equation as multipoles, the gains of the PID controller can be tuned with only one adjusting variable, making the tuning of the 2-DOF controller easier. The other is that the controller parameters are tuned based on maximum sensitivity, thus taking into account the robust stability of the control system. To demonstrate the feasibility of the proposed method, simulations are conducted for four scenarios using various performance indices. [ABSTRACT FROM AUTHOR]

The BLDC motor is becoming more popular in electric vehicles than other motors because of its high torque, robust control, etc. Antithetically, it is more challenging to regulate the torque ripples of a BLDC motor under various real-time conditions. To overcome these shortcomings, this study uses novel methodology to analyse the effectiveness of BLDC motor with different energy management controllers. In this study, to control the torque variations of a BLDC motor, supervisory, hybrid, intelligent, and PID controllers are designed using MATLAB/Simulink. This study integrates experimental and modelling techniques to understand the behaviour of a BLDC motor with various EMCs in real-time conditions. The simulation finding indicates that the supervisory controller exhibits a minimal settling time (0.05 s), rise time (0.01 s), and overshoot (0.93%) than other conventional controllers. It integrates knowledge of real-time rules and numerical data with a neural network in order to forecast and reduce error statistics in the BLDC motor. As well, the proposed supervisory approach significantly reduces the torque fluctuations of BLDC motors under various real-time operating conditions. Further, an experimental study is conducted to validate the results of the simulation; this work entails the development of efficiency maps for a variety of energy management controllers. The efficiency of the various controllers is 97, 91, 85, and 78%, respectively. The recommended supervisory strategy surpasses other controllers in terms of time-domain characteristics under different conditions. Therefore, the proposed controller will enhance the efficiency of the BLDC motor and extend driving range of EVs under various real-time driving situations. [ABSTRACT FROM AUTHOR]

The role of pumped storage in global energy structure transformation is becoming increasingly prominent. This article introduces a flexible excitation system based on fully controlled device converters into pumped storage units (PSUs). It can address the issues of insufficient excitation capacity and limited stability associated with traditional thyristor excitation systems. The study focuses on linear active disturbance rejection control (LADRC) for the flexible excitation control system of pumped storage units and utilizes intelligent optimization algorithms to optimize the controller parameters. This addresses the inherent problem of traditional PID controllers, which are unable to alleviate the trade-off between response speed and overshoot. At the same time, the robustness and anti-interference of the control system are improved, effectively enhancing the performance of the pumped storage flexible excitation control system. Simulation verifies the feasibility and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Decentralized control systems are frequently employed to tackle control challenges in multi-input multi-output (MIMO) systems. Hence, this paper proposes a decentralized PID controller that relies on frequency domain specifications. This controller is designed to minimize the loop interactions and fulfill the design criteria of the MIMO system. The PID parameters are calculated based on gain and phase margin specifications. Additionally, a first-order plus dead time model is derived for each of the decoupled subsystems. Furthermore, robust stability is analysed using disc margin analysis, which overcomes the constraints of traditional margins. Moreover, the paper determines a secure range of uncertainty for various levels of gain and phase uncertainties. The findings suggest that the proposed controller achieves robust stability over a broader range of margins when compared to alternative control methods. [ABSTRACT FROM AUTHOR]

This paper presents the synthesis results of a robust H∞ (H-infinity) loop-shaping controller combined with a PID (Proportional-Integral-Derivative) controller using fuzzy logic for the pitch autopilot of a tail control missile. The results take into consideration the change of mass, moment of inertia, and aerodynamic coefficients. The combination of the control signal of the robust controller and the PID controller is formed on the basis of adjusting the membership function of fuzzy logic according to the ITAE (Integral of Time-multiplied Absolute value of Error) optimization criterion. The performance and robustness of the missile autopilot are verified by nonlinear simulation. [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 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]

Copyright of Dokuz Eylul University Muhendislik Faculty of Engineering Journal of Science & Engineering / Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi is the property of Dokuz Eylul Universitesi Muhendislik Fakultesi Fen ve Muhendislik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a new approach for head camera stabilization of a humanoid robot head is proposed, based on a bio-inspired soft neck. During walking, the sensors located on the humanoid's head (cameras or inertial measurement units) show disturbances caused by the torso inclination changes inherent to this process. This is currently solved by a software correction of the measurement, or by a mechanical correction by motion cancellation. Instead, we propose a novel mechanical correction, based on strategies observed in different animals, by means of a soft neck, which is used to provide more natural and compliant head movements. Since the neck presents a complex kinematic model and nonlinear behavior due to its soft nature, the approach requires a robust control solution. Two different control approaches are addressed: a classical PID controller and a fractional order controller. For the validation of the control approaches, an extensive set of experiments is performed, including real movements of the humanoid, different head loading conditions or transient disturbances. The results show the superiority of the fractional order control approach, which provides higher robustness and performance. [ABSTRACT FROM AUTHOR]

This paper introduces an analog integrated fractional order type-2 fuzzy PID control system. Current approaches frequently depend on energy-intensive embedded digital systems, consuming substantial energy levels ranging from a few μW to mW. To address this limitation we propose a fully analog design offering insights into the potential of analog circuits for powerefficient robust control in complex and uncertain environments. It consists of Gaussian function, min/max, Operational transcoductance amplifier circuits and Resistor-Capacitor networks for the implementation of the fractional-order components. Crafted for operation under a reduced voltage supply (0.6 V), the controller attains minimal power usage (861.8 nW), facilitating uninterrupted, extended-term functioning. Post-layout simulation results confirm the proper operation of the proposed design. The proposed system is designed and simulated using the Cadence IC Suite in a TSMC 90 nm CMOS process. [ABSTRACT FROM AUTHOR]

A pressure control method that incorporates parameter adaptation has been devised for the pressure control system of pintle solid rocket motors, which exhibit notable nonlinearities and uncertainties in parameters. Firstly, the mathematical relationship between pressure and pintle displacement is derived using the zero-dimensional interior ballistic model., and the state space equation is deduced by incorporating the dynamics of motor inertia load. Secondly, by capitalizing on the robustness of robust control, the parameter identification capabilities of adaptive control, and the rigor of Lyapunov stability theory, the proposed approach enables precise control of the pintle position while effectively addressing uncertainties, thereby enhancing the overall performance and stability of the system. Finally, the aforementioned theoretical framework has been validated through rigorous numerical simulations. The findings demonstrate a notable enhancement in the pressure response speed of the adaptive robust controller, with improvements of 10.01 % and 13.16 %, 0.03 % and 1.54 %, 0.06 % and 22.39 % in different orders of magnitude of free volume as compared to the robust controller and PID controller, respectively. Moreover, it is evident that the adaptive robust controller relies on the accuracy of the model. The applied controller demonstrates notable advantages in terms of stability, robustness, and accuracy, thereby substantially enhancing the overall performance of the pressure control system. • The state space equation for the pressure of the pintle solid rocket motors is derived. • The pressure dynamics equation and the motor inertial load equation are combined. • An adaptive robust controller with respect to pressure is designed. • The controller response laws for various free volumes, pressure index and characteristic velocity are obtained. • The adaptive robust controller exhibits a higher dependence on model accuracy is observed. [ABSTRACT FROM AUTHOR]

In this paper, a novel flow control strategy which is the inlet throttled pump was used to design an angular velocity control system for rotary actuator. Inlet throttled systems have good performance in addition to their high efficiency compared to traditional valve-controlled systems. The flow in the proposed system is adjusted by a valve that is positioned at the pump inlet with the purpose of reducing the energy loses across the valve. This regulated flow is used then to control the actuator angular velocity. The system was modeled and the open loop stability and performance were studied. In order to improve the system performance, proportional-integralderivative (PID) and H-infinity controllers have been designed. The multiplicative uncertainty was analyzed to assess the robustness of the feedback control system where six parameters were considered uncertain within a range of +10%. The robust stability and performance requirements of the closed-loop angular velocity control system were assessed in the frequency domain. The time response of the system showed that the system is stable with both PID and H-infinity controllers. The PID controller have the advantages of simplicity and high response speed while the H8 controller provides better nominal performance, robustness, and stability. The H8 controller can handle parametric uncertainty without requiring pure integral term which is a significant advantage over the PID controller. On the other hand, the PID controller falls short of achieving robust performance, making it less suitable for systems that require high levels of performance and robustness. In summary, the H8 controller is a more comprehensive solution for ensuring the best performance of a system. In contrast, the PID controller may be more suitable for systems with less stringent performance requirements. [ABSTRACT FROM AUTHOR]

In this study, we propose a new approach to selecting PID controller parameters for a UAV tricopter during programmed flights. The approach uses optimization techniques to determine the optimal values of the PID controller parameters based on the desired performance of the UAV. The proposed method is particularly effective for repeated programmed flights in which the UAV follows a defined flight path. The use of a PID control provides a reliable and robust control system that can cope with various disturbances and uncertainties in UAV dynamics. The proposed method provides an alternative to adaptive control, which requires a significant amount of system identification and parameter tuning. The effectiveness of the proposed method has been verified in simulation studies, and the results show its ability to achieve satisfactory performance with low tracking error and fast response time. The result of the work is an improvement in control for a specific object at a specific mission. We present how the recipients can perform this procedure for their object and their mission to be able to improve the control gain in the physical controller. [ABSTRACT FROM AUTHOR]

In the chemical and petrochemical industry, the Continuous Stirred Tank Reactors (CSTR) are, without doubt, one of the most popular processes. From a control point of view, the mathematical model describing the temporal evolution of the CSTR has a strongly nonlinear crosscoupled character. Moreover, modeling errors such as external disturbances, neglected dynamics, and parameter variations or uncertainties make its control task a very difficult challenge. Even though this problem has been the subject of a wide number of control strategies, this article attempts to propose a viable, robust, nonlinear decoupling control scheme. The idea behind the proposed approach lies in the design of two nested control loops. The inner loop is responsible for the compensation of the nominal model nonlinear cross-coupled terms via static nonlinear feedback; whereas the outer loop, designed around an Extended State Observer (ESO) of which the additional state gathers the global effect of modeling errors, is charged to instantaneously estimate, and then to compensate the ESO extended state. This way, the CSTR complex dynamics are reduced to a series of decoupled linear subsystems easily controllable using a simple Proportional-Integral (PI) linear control to ensure the robust pursuit of reference signals respecting the desired performance. The presented control validation was performed numerically by an objective comparison to a classical PID controller. The obtained results clearly show the viability and the effectiveness of the proposed control strategy for dealing with such nonlinear, strongly crosscoupled plants subject to a wide range of disturbances despite the precision of their described mathematical model. [ABSTRACT FROM AUTHOR]

Tuning a nonlinear inverted pendulum is a complex and uncertain optimization problem. In this paper, we develop two new GWO variants by introducing a DLH (Dimension Learning-based Hunting) module and new formulas to enhance the exploitation/exploration ratio aiming to avoid local minima. A statistical analysis is carried out to compare the two proposed approaches with five GWO variants. After that, they are used to tune a PID and FSMC controller. The obtained results are promising even when compared to other approaches. [ABSTRACT FROM AUTHOR]

Over the past few years, many electrical vehicle manufacturers have focused on developing enhanced controller efficiency for Four-Wheel Drive (FWD) systems. The control of the speed and direction of the FWD is crucial for safe and efficient operation, particularly in challenging maneuvers. The FWD system movements in straight routes and during maneuvers, turning all four wheels right and left, have not been well covered. Therefore, a robust control design that is capable of controlling the FWD system at an optimal time of operation is highly required. In this research, a Finite Time Control (FTC) is designed, implemented, and simulated to improve the robustness and performance of the FWD system during challenging maneuvers. The proposed FTC controls both the speed and direction of all wheels of FWD according to the route situations. The proposed FTC is compared with an FWD system that is controlled by a traditional Proportional, Integral, and Derivative (PID) controller during straight moving and maneuvers. The comparison is based on controlling parameters such as settling time, maximum overshoot, and speed error values. The results showed that the proposed FTC has a much faster settling time, significantly less maximum overshoot, and much lower error values than the PID controller. These factors are considered the main features of the contribution of any controller system that aims for optimal and robustness and FTC proved to have them adequately. [ABSTRACT FROM AUTHOR]

In this paper, the high accuracy motion output feedback control of a kind of launching platforms driven by motors is focused. The launching platform is used to launch kinetic load to hit the target so it is susceptible to external disturbance. In addition, significant issues arise due to limitations on the plant inputs, such as actuator energy limits and velocity state is usually unavailable due to the limitation of system cost and volume. A new adaptive fuzzy output feedback controller based on dual observers is proposed for solving these problems. A smooth and continuous model is established for input saturation to compensate it. A sliding mode observer and a fuzzy observer with proper membership function are combined to estimate the unmeasured system states more accurately. An adaptive robust controller and the fuzzy observer are combined to realize a motion control with disturbance rejection, which allows correct adaptation while the plant input is saturated. Lyapunov theorem proves the bounded stability of the proposed controller when there exists observation error. Extensive comparative simulation and experiment results verify the effectiveness and practicability of the proposed controller and show that the control accuracy can be improved by an order of magnitude compared with the traditional PID controller and better than some other nonlinear controllers. [ABSTRACT FROM AUTHOR]

In this article, a new multiobjective particle swarm optimization (MOPSO) algorithm is introduced to improve the performance of a sliding mode based robust fuzzy proportional–integral–derivative (PID) controller. In this regard, the non-dominated solution having minimum number of neighbors is considered as the global best position, while the sigma values of the members are employed to determine the personal best position. A modified multiple-crossover operator is combined with the operators of the particle swarm optimization to significantly increase the convergence speed of the algorithm. To limit the size of the archive, a dynamical elimination scheme defined in the Euclidean space is introduced. Besides, iteration-based linear relations are implemented to adaptively compute the inertia weight and learning coefficients. To evaluate the effectiveness of the introduced MOPSO algorithm, the requirements are conducted by means of three benchmark functions with regard to generational distance, spacing, and maximum spread metrics. This analysis demonstrates that the proposed algorithm operates better through comparison with well-known elitist multiobjective evolutionary algorithms. Moreover, the MOPSO algorithm is applied for optimal design of a hybrid robust fuzzy PID controller for a pneumatic system with two bellows. Conflicting objective functions are considered as the normalized values of overshoot and settling time of the displacement between the bellows that should be simultaneously minimized. The feasibility and efficiency of the strategy are assessed in comparison with the conventional controllers. [ABSTRACT FROM AUTHOR]

This paper exploits the design of a decentralized proportional integral derivative (PID) controller based on nonlinear optimization for a continuously stirred tank reactor system. The basic objective is to attain the design specifications by maintaining both the temperature and concentration. The continuously stirred tank reactor is modeled to a first-order plus dead time system by designing a decoupler. The proposed PID controller is designed on the basis of fundamentals of nonlinear optimization. Further, the overshoot is bounded with constraints on the maximum closed-loop amplitude ratio. The control algorithm is designed for decoupled systems to reduce the loop interactions and attain the servo response. The robust stability is analyzed by considering multiplicative input as well as output uncertainties, while stability is verified with the Kharitonov–Hurwitz theorem. A concise comparison is made between the proposed technique with existing methods. It is envisaged that the proposed control algorithm exhibits better servo and regulatory responses compared to the existing techniques. Furthermore, the efficacious nature of the proposed control scheme is validated by considering a wide range of closed-loop amplitude ratios. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In robotic applications, the correct execution of a task can be a challenge for robotics experts. Therefore, it is necessary to implement a robust control structure for trajectory tracking. This paper proposes a robust control design to track the trajectory of an industrial robot via a fractional order PID controller with the Computed Torque Control (CTC) technique based on the Grey Wolf Optimizer (GWO). To examine the proposed robust control, the Fanuc 710ic/70 robot manipulator model is used as a case study. To begin with, the dynamic formulation of the robot is described. Then, with respect to the control design, the CTC controller that helps overcome the nonlinearity problem of the system is designed to improve the tracking performance. It is proposed to combine the fractional order PID with the CTC technique. This hybridization increases the performance of the control strategy and overcomes external disturbances, sensor noise suppression and especially input control constraints. Typically, FOPID controller parameters are set without considering the constraints of the actuator control inputs. Therefore, it affects its performance over time. To solve this problem, the controller parameters are updated online and optimized according to the input constraints using the GWO technique. The effectiveness of the proposed control strategy is demonstrated by the simulation results in terms of stability, trajectory tracking and compliance with limited inputs. [ABSTRACT FROM AUTHOR]

Axial piston pumps provide a number of benefits, including strong pressure resistance, high efficiency, high transmission power, a broad speed range, and a long lifespan. These characteristics have led to their widespread usage in naval applications, construction machines, and hydraulic machinery. On the other hand, axial piston pumps frequently display reduced operating speeds as well as instability because of their inherently nonlinear properties. In this study, a mathematical model of these changeable (variable) processes is developed using a mix of theoretical calculations and acquired data. An investigation of variable mechanism control in axial piston pumps is carried out centered on robust control methods, and the controller is constructed utilizing robust H∞ theory. In terms of resilience, control precision, and system reaction time, simulations show that the H controller surpasses the PID controller. [ABSTRACT FROM AUTHOR]

In this paper, the designing of robust controllers for well-known convey crane systems in the presence of uncertainties is presented. Cranes play a great role in the industrial environment, construction sites, ship-yard, and rial-yard because of their efficiency and accuracy in moving heavy and dangerous materials from one loading location to another. The main challenge in controlling such kinds of systems is to minimize the undesirable swings when different payloads are carried. This phenomenon is because the convey crane is classified as an under actuated nonlinear system and there are many sources of uncertainties that affect the plant of the physical system Hence, the stability of the convey crane system in the presence of the uncertainties became a challenging task between the researchers in the control engineering field and used as a benchmark in universities. In this research, firstly, the stability of the linearized model of the conveycrane system is analyzed using the edge theorem in the presence of two uncertain parameters: the rope length and the weight of the load, where the classical pole placement technique is used for stabilization purposes. Secondly, the sliding mode control (SMC) is proposed in order to stabilize the nonlinear model of the convey-crane system with the presence of noise signals. In order to test the effectiveness of the proposed SMC controller, a conventional PID control is applied to the linearized model of the convey-crane system, where the PID parameters are tuned using the well-known Ziegler-Nicholas method. The robustness against the uncertainties in the parameters of the convey crane is achieved by using the Edge theorem, whereas the robustness against the noise signal is tested by using MATLAB; the simulation results show the superiority of the SMC controller over the PID. [ABSTRACT FROM AUTHOR]

The Photovoltaic (PV) system is an eco-friendly renewable energy system that is integrated with a DC-DC buck-boost converter to generate electrical energy as per the variations in solar irradiance and outdoor temperature. This article proposes a novel Adaptive Fractional Order PID (A-FOPID) compensator with self-adjusting fractional orders to extract maximum power from a stand-alone PV system as ambient conditions change. The reference voltage is generated using a feed-forward neural network. The conventional FOPID compensator, which operates on the output voltage error of the interleaved buck-boost converter, is employed as the baseline maximum-power-point-tracking (MPPT) controller. The baseline controller is retrofitted with an online state-error-driven adaptation law that dynamically modifies the fractional orders of the controller's integral and differential operators. The adaptation law is formulated as a nonlinear hyperbolic scaling function of the system's state error and error-derivative variables. This augmentation supplements the controller's adaptability, enabling it to manipulate flexibly the tightness of the applied control effort as the operating conditions change. The efficacy of the proposed control law is analyzed by carrying out customized simulations in the MATLAB Simulink environment. The simulation results show that the proposed MPPT control scheme yields a mean improvement of 25.4% in tracking accuracy and 11.3% in transient response speed under varying environmental conditions. [ABSTRACT FROM AUTHOR]

The fuel cell (FC) is a new technology for large-scale power generation. Providing of fast and sufficient air concentration in the FC cathode is a key to prevent the oxygen starvation and extend the life cycle of the FC. The proton exchange membrane fuel cell (PEMFC) parameter variations and output current disturbances can significantly influence on the airflow subsystem performance. For this purpose, this paper addresses the robust airflow control synthesis of the PEMFC based on the $ \mu $ and $ H_\infty $ control techniques. The presented advanced controllers are designed to regulate the oxygen concentration in the FC cathode on the desired value. Such robust controllers are tuned to guarantee PEMFC performance against parameter variations and output current disturbances. Then, the obtained results are compared with the optimal PID controller tuned by the well-known internal model control (IMC) method. Simulation results show that in comparison of the IMC-based PID controller, the applied robust control methodologies are more effective. The designed $ \mu $ and $ H_\infty $ controllers efficiently provide the required airflow of the PEMFC on the desired value, and avoid the oxygen starvation. Furthermore, due to the structured type of uncertainties, the $ \mu $ controller keeps the airflow on the desired value quite better than the $ H_\infty $ controller. [ABSTRACT FROM AUTHOR]

The traditional method of taxiing for civil aircraft, which relies on their engines, may be surpassed by the new method of towing taxi-out due to its superior advantages such as reduced energy consumption, lower emissions, and higher efficiency. However, the towing taxi-out system poses a challenge to lateral stability due to the concentration of mass at the rear, leading to severe instability when turning at high speeds. To address this issue, a nonlinear civil aircraft towing and taxiing system model and a linear four-degree-of-freedom civil aircraft towing and taxiing system reference model were established using TruckSim and Matlab/Simulink software. The fuzzy proportional–integral–derivative controller was utilized, with the braking torque of each wheel serving as the control variable and the real-time yaw rate difference and its rate of change as the fuzzy control input. The controller was compared and validated with a traditional PID controller. The results of the simulation showed that the fuzzy PID control has better nonlinear characteristics and stronger adaptability to operating conditions compared to traditional PID control, providing timely, effective, adaptive, and robust control effects for the vehicle dynamics model. Under the fuzzy PID control, the peak yaw speed of the civil aircraft decreased to 10 degrees per second under double-shift conditions, representing an increase of 23.1%. Furthermore, the lateral stability and safety of the towing taxi-out system were improved, as evidenced by the reduction in the yaw rate of the tractor and civil aircraft under the hook condition. The use of this controller provides valuable technical guidance and support for the practical development and safe application of the towed glide mode. [ABSTRACT FROM AUTHOR]

Any mismatch of power demand and power generation in an interconnected electrical power system causes deviances in tie-line power and frequencies. To overcome this issue, an automatic generation control system equipped with intelligent controllers is used in the power system. This study presents a maiden write-up on a two-d egree -of-f reedo m fractional order -fuzz y-pro porti onal-integ ral-d eriva tive (2DOF-FO-FuzzyPID) controller employed in an interconnected system with different nonlinearities. The controller proposed along with conventional controllers has its gains optimally enumerated by the application of modified whale optimization algorithm (MWOA). Besides this, the potency of the MWOA algorithm over WOA algorithm is examined through some popular benchmark functions. The superior transient response yielded by 2DOF-FO-FuzzyPID controller over PID and fractional-order propo rtion al-in tegra l-der ivati ve controllers of the proposed test system is evaluated. Further, the effectiveness of the projected controller is evaluated by taking the system's nonlinearities and abrupt load perturbation, which acknowledges the robustness of the controller. In spite of these attributes, the stability and relative stability of the 2DOF-FO-FuzzyPID controller is determined in the frequency domain. [ABSTRACT FROM AUTHOR]

This paper presents a study on controlling the out-of-water motion of amphibious multi-rotor UAVs using a cascade control method based on the Active Disturbance Rejection Control (ADRC) algorithm. The aim is to overcome the challenges of time-varying model parameters and complex external disturbances. The research involves developing an underwater dynamic model and analyzing hydrodynamic forces to calculate theoretical inertial hydrodynamic forces and simulate viscous hydrodynamic forces. This establishes the relationship between viscous hydrodynamic forces and exit velocity. A complete air dynamic model is then established, selecting model parameters based on the center of mass position of the amphibious vehicle to enable switching from water to air. To address control algorithm instability caused by changes in model parameters, position and attitude controllers are built using the ADRC algorithm. The control effects are compared with traditional PID and sliding mode controllers (SMC) to verify the effectiveness and superiority of the proposed cascade ADRC control strategy. Experimental results show that our controller has stronger anti-interference than traditional PID and SMC controllers and can overcome control instability caused by changes in model parameters. Our research highlights the importance of using ADRC-based controllers for amphibious multi-rotor UAVs to achieve robust and stable control. [ABSTRACT FROM AUTHOR]

This article proposes a novel method for maintaining the trajectory of an aerial manipulator by utilizing a fast nonsingular terminal sliding mode (FNTSM) manifold and a linear extended state observer (LESO). The developed control method applies an FNTSM to ensure the tracking performance’s control accuracy, and an LESO to estimate the system’s unmodeled dynamics and external disturbances. Additionally, an improved salp swarm algorithm (ISSA) is employed to parameter tune the suggested controller by integrating the salp swarm technique with a cloud model. This approach also uses a model-free scheme to reduce the complexity of controller design without relying on complex and precise dynamics models. The simulation results show that the proposed controller outperforms linear active rejection disturbance control and PID controllers in terms of transient performance and resilience against lumped disturbances, and the ISSA can help the proposed controller find optimal control parameters. [ABSTRACT FROM AUTHOR]

This paper presents the development of a modified Fractional Order Proportional Integral Derivative (FOPID) controller to mitigate frequency deviation in a four-area thermal power system. Change in load demand and noisy power system environment can cause frequency deviation. Reducing high-frequency deviation is very paramount in load frequency control. This is because large frequency deviation can cause the transmission line to be overloaded, which may damage transformers at the transmission level, damage mechanical devices at the generating stations and also damage consumer devices at the distribution level. The conventional PID has been widely used for this problem. However, the parameter values of the various generating units of the power system like generators, turbines and governors keep changing due to numerous on/off witching in the load side. As such, it is essential that the control strategy applied should have a good capability of handling uncertainties in the system parameters and good disturbance rejection. Fractional order PID controller is known to give a higher phase margin resulting in very good disturbance rejection, robustness to high-frequency noise and elimination of steady-state error. A four-area power system was designed, and FOPID was used as the supplementary controller to mitigate frequency deviation. Ant Lion Optimizer (ALO) algorithm was used to optimize the gains of the FOPID controller by minimizing Integral Square Error (ISE) as the objective function. Results obtained outperformed other designed methods available in the literature in terms of reducing frequency deviation, tie-line power deviation and area control error. [ABSTRACT FROM AUTHOR]

This paper presents a design framework to obtain a robust multivariable Proportional-Integral-Derivative (PID) controller for second-order linear vibrating systems. A Proportional-Integral-Derivative plus acceleration (PIDA) controller is also proposed to deal with the regularization problem. Relevant control challenges, such as modeling error, regulatory performance optimization, regional pole placement, saturation avoidance, and constant reference tracking are handled within the proposed Linear Matrix Inequality (LMI) design approach. The design strategy is obtained from a linear transformation that can be applied to achieve constant reference tracking for an actuated subspace of underactuated systems. Moreover, the integral action has two additional objectives: (1) to improve regulatory performance in the presence of constant disturbance and (2) to increase the design degree of freedom in order to robustly achieve closed-loop specifications. Three simulation case studies are used to highlight the benefits of the PID and PIDA controllers. [ABSTRACT FROM AUTHOR]

Based on the traditional PID control and robust control algorithm, a novel practical robust control method is designed for the 6‐DOF collaborative industrial robot with uncertainty. The proposed algorithm consists of a robust term and a model‐based PD control term, which we call MPDP controller. It is demonstrated by Lyapunov theoretical analysis that the algorithm is able to guarantee uniform boundedness and uniform ultimate boundedness of the system. Simulations and experiments show the good performance of MPDP control in a robot with smaller steady‐state tracking errors and better robustness compared to PID controllers. [ABSTRACT FROM AUTHOR]

This paper presents a robust hybrid controller for non-inverting buck-boost (NIBB) DC-DC converter. The proposed hybrid controller is comprised of feedback closed-loop PID controller and novel designed feedforward open-loop controller. The proposed open-loop controller supports the PID controller and enhances the system transient response during the system operating parameters transition. The open-loop controller has a simple and static structure. It is also independent of the closed-loop controller and thus has a modular behaviour. In order to show the accuracy, robustness and efficiency of the proposed hybrid control method, both simulation and experimental studies are performed. The comparative results prove that the proposed hybrid controller with the novel developed open-loop controller provides robust and efficient control of the converter. It improves the converter’s output response during the transients of the operating parameters: the change of input voltage, reference output voltage and output load. [ABSTRACT FROM AUTHOR]

Industries have many rotational operations that are used for design, transport, lift, drilling, rolling, robotics, and many other applications. These rotating applications require a proper controller for accurate control of the operation. Separately excited DC motors (SEDCMs) are versatile and have various industrial operations because of their specific speed control characteristics. So, for smooth and accurate operation of an SEDC motor, controllers should be used. PI and PID controllers are used in many cases, but they are ineffective for nonlinear load operation. A fuzzy controller is a heuristic controller and can provide automatic control of the operation. Its operation depends on the selection of the correct membership values. This work proposes a novel particle swarm optimization (PSO) technique that would provide the optimum value of the membership for fuzzy controllers for optimum control of the industrial processes. To obtain SEDC results, MATLAB simulation was performed, and the fuzzy controller with novel PSO was implemented. A fuzzy PSO controller used for motor speed control operation obtains a rise time of 0.00026 s, settling time of 0.000214 s, maximum overshoot of zero, and delay time of 0.016 s, which are the best values when compared to PID and PID-Fuzzy controllers. It is observed that the results obtained from the separately excited DC motor using a fuzzy PSO controller improve the dynamic behavior of the motor that so it smoothly tracks the required speed without any more overshoot or oscillation than the PID controller. Such dynamic, stable operation of the motor makes it perfect for industrial as well as household operations. [ABSTRACT FROM AUTHOR]

The control of processes with time delays is crucial in process industries such as petrochemical, hydraulic, and manufacturing. It is a challenging task for automation engineers, as it may affect both phase and gain margins. In this case, a robust control system is preferred. This article presents a novel controller structure combining computational intelligence (CI) and fractional-order control. A fractional-order PID (FOPID) controller based on a bio-inspired immune feedback mechanism (IFM) is developed for controlling processes described as first-order plus time-delay systems (FOPTD). A genetic algorithm (GA) is used to optimize the controller parameters. Fractional-order control has been used to give extra flexibilities and an immune feedback mechanism for its self-adaptability. Numerical simulations are presented to validate the proposed control strategy in terms of reference tracking and disturbance rejection. Comparative simulation results with an immune integer-order PID controller are also included to demonstrate the efficiency of the proposed fractional-order method. [ABSTRACT FROM AUTHOR]

In order to solve the problem of disturbance in grinding control system， a robotic force control end-effector is designed， and a grinding control method of robotic active compliance constant-force is proposed， based on the active disturbance rejection control and the fuzzy variable impedance control. A fuzzy variable impedance controller is adopted by the inner-loop control of the proposed method， and an active disturbance rejection grinding controller is adopted by the outer-loop control. Convergence of the tracking error to zero for the proposed method is guaranteed by the Lyapunov stability theory. The effectiveness and applicability of the proposed method are verified by the co-simulation and experiment. By comparing the proposed method and the PID controller， which is used to replace the outer-loop control， when the inner-loop control is same， the former has better ability to reduce force tracking error and position overshoot during simulation experiments. Meanwhile， using the proposed method， the control effects and the robustness of the force control system for the robotic grinding are improved， and the robotic compliant constant-force control is realized. [ABSTRACT FROM AUTHOR]

An improved robust predictive control method is proposed for a class of multicellular descriptive LPV systems with bounded state disturbances, and an output feedback controller is designed to ensure the asymptotic stability of the systems. To offset the bounded state disturbance, the controller considered the undisturbed LPV system, and based on the off-line state observer, the LMI is used to solve the minimum-maximum optimization problem in the infinite time domain of predictive control. Then the off-line state observer is used to obtain the difference between the estimated values of the disturbed LPV system and the undisturbed LPV system, and the feedback gain of the guaranteed performance is determined, so as to obtain the optimal offset that makes the disturbed LPV system asymptotically stable, which is combined with the undisturbed system control law as the optimal control law and applied to the actual system. The experimental results show that the improved robust predictive control method can obtain better control performance, and improve the stability of the system and the efficiency of solving optimization problems. Simulation experiments also verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

For the Amphibious bot movement control, this study provides an Internal Model Control (IMC) tuned PID controller using fuzzy logic optimization method. IMC approach is used to tune the PID controller parameter as per the robot movements for robust control. Fuzzy logic is used to optimize the input error for controlling output. The proposed control approach, which is based on an accurate robot model, resulted, design of the stable and robust control system. The proposed method produces better outcomes than the present methods. It is measured against performance indices. Comparative results show a significant improvement in the system's overshoot, rising time, and settling time. It is also performing better and better robustness against disturbances. [ABSTRACT FROM AUTHOR]

Fractional order Controllers have been used in several industrial cases to achieve better performance of the systems. This paper proposes a Fractional Order Proportional Integral Derivative (FOPID) controller. It is synthesized using Oustaloup approximation, and its parameters are tuned using the Genetic Algorithm (GA) optimization method. The aim is to minimize the error, the energy and the startup torques using two objective functions to improve the control performances and the robustness. The validity of the proposed controller is shown via simulation by controlling a two-link exoskeleton for children's gait rehabilitation, and the results are compared to an Integer order PID (IOPID) controller. Simulation results clearly indicate the superiority of the optimized FOPID in terms of trajectory tracking and the used torques. Moreover, the FOPID controller is tested with parameter uncertainties. Its robustness is proven against thigh and shank masses variation. Both controllers are simulated under the same frequency conditions using Simulink MATLAB R2018a. [ABSTRACT FROM AUTHOR]

A decentralized PI/PID controller based on the frequency domain analysis for two input two output (TITO) coupled tank systems is exploited in this paper. The fundamentals of the gain margin and phase margin are used to design the proposed PI/PID controller. The basic objective is to keep the tank at the predetermined level. To satisfy the design specifications, the control algorithm is implemented for decoupled subsystems by employing a decoupler. First-order plus dead time (FOPDT) models are obtained for the decoupled subsystems using the model-reduction technique. In addition, the control law is realized by considering the frequency domain analysis. Further, the robustness of the controller is verified by considering multiplicative input and output uncertainties. The proposed method is briefly contrasted with existing techniques. It is envisaged that the proposed control algorithm exhibits better servo and regulatory responses compared to the existing techniques. [ABSTRACT FROM AUTHOR]

This article deals with the calculation of all robustly relatively stabilizing (or robustly stabilizing as a special case) Proportional–Integral–Derivative (PID) controllers for Linear Time-Invariant (LTI) systems with unstructured uncertainty. The presented method is based on plotting the envelope that corresponds to the trios of P–I–D parameters marginally complying with given robust stability or robust relative stability condition formulated by means of the H ∞ norm. Thus, this approach enables obtaining the region of robustly stabilizing or robustly relatively stabilizing controllers in a P–I–D space. The applicability of the technique is demonstrated in the illustrative examples, in which the regions of robustly stabilizing and robustly relatively stabilizing PID controllers are obtained for a controlled plant model with unstructured multiplicative uncertainty and unstructured additive uncertainty. Moreover, the method is also verified on the real laboratory model of a hot-air tunnel, for which two representative controllers from the robust relative stability region are selected and implemented. [Display omitted] • Calculation of robustly relatively stabilizing PID controllers is introduced. • Controlled plants are in the form of LTI systems with unstructured uncertainty. • Boundaries of H ∞ norm-based robust relative stability conditions are utilized. • The regions of robust relative stability are plotted in a P–I–D space. • Robustly (absolutely) stable controllers can be obtained as a special case. [ABSTRACT FROM AUTHOR]

To create an autonomous surface vehicle, the microcontroller that will be responsible for the vessel' s response will have access to both engine thrust controls and steering controls. In the case of a vehicle with waterjet propulsion, the term "controls" refers to engine RPM and nozzle angle. The latter allows the thrust vectoring. Having performed the mathematical modelling of the surface vessel, a method must be found such that the microcontroller actions on the controls create the desired outputs, based on predefined performance objectives. A commonly selected control algorithm considered an industry standard for control applications—at least from the perspective of classical control methods—is the PID control scheme. Many times, a PID control scheme is sufficient for achieving the required performance. There are also many methods that extend the functionality of the PID to robust control schemes, to accomplish more specific targets, such as noise rejection. The vast majority of all these implementations, will have to be implemented using a digital microcontroller or an FPGA. This paper assists theoretically in implementing PID controllers digitally, by elaborating on the discrete-time perspective of PID control. It also provides a test method for evaluating the algorithmic implementation. [ABSTRACT FROM AUTHOR]

The control of mobile hydraulic systems presents several challenges: valve characteristics and position-dependent system behavior are sources of nonlinearity. In addition, position and velocity sensors are not common in mobile machines, although the primary objective is piston velocity control. The particular type of hydraulic system considered in this article uses four decentralized valves to control the inflow and outflow of the two cylinder chambers. In contrast to conventional controller synthesis by tuning PID-type controllers for different operating points, a systematic approach for robust identification and model-based control is presented. It benefits from the possibility of bypassing the cylinder chambers for the identification step. Here, the ranges of physical parameters are estimated to obtain a parametrization of all possible system realizations. To reduce the valve-dependent nonlinearity, electro-hydraulic pressure compensation is applied to all valves. Based on the identified model, a nominal linear quadratic Gaussian controller and a robust μ -synthesis controller are designed, tested, and compared to a state of the art PID controller with active damping The identification and control are partially demonstrated on a hydraulic test bed and in simulation. • Systematic approach for identification and model-based controller synthesis of mobile hydraulic systems. • Benefits from the flexibility of the decentralized valve structure. • Good controller performance without gain scheduling. [ABSTRACT FROM AUTHOR]

To achieve optimal control under all operating conditions for hydropower units, an intelligent robust controller (NSFLIRC) is proposed based on a novel state space equation and state-dynamic-measurement feedback linearization. Firstly, a nonlinear hydro-turbine regulation system (HTRS) model is constructed and a novel high-order state space equation model of HTRS is derived considering system tracking deviation. Then, the robust control for HTRS is achieved by combining the novel high-order state space equation and H ∞ control. Furthermore, the slime mold algorithm (SMA) is improved by incorporating hybrid chaotic mapping functions, Levy flight, and a nonlinear weight coefficient. The intelligent optimization of H ∞ controller parameters is realized using the improved SMA (ISMA). Finally, a nonlinear HTRS simulation platform is constructed to verify the performance of the proposed NSFLIRC. The simulation results show that when the overshoot is within a reasonable range, using NSFLIRC can respectively reduce the average values of adjusting time, rising time, overshoot, and power inversion by 46.6 %, 29.06 %, and 52.56 % comparing to the traditional PID controller under six typical operating conditions; also, the NSFLIRC has low sensitivity to changes in system parameters and most operating conditions, and has strong robustness under conventional load changes and extreme three-phase short circuit conditions. • A high-precision nonlinear simulation platform of the hydraulic turbine regulation system is built. • A novel state equation of the hydraulic turbine regulation system is introduced. • The robust control strategy for hydropower units is realized under the power control mode. • The slime mold algorithm is optimized and applied. • The designed robust controller is verified under normal conditions and extreme three-phase short circuit conditions. [ABSTRACT FROM AUTHOR]

In this study, the speed control of a DC motor with input delay and external disturbance is investigated. A delay-dependent memory state feedback robust predictor-based H ∞ controller that formerly has presented is utilized. Sufficient LMIs conditions provide the stabilizing gain of the predictor-based controller. The first-order model of a DC motor has been studied previously using PID and STA (super twisting algorithm) methods. However, in this paper, the delay-dependent robust H ∞ controller is used on both the first and second orders of the DC motor. Finally, the predictor-based H ∞ controller is compared to the PID controller and the common H ∞ controller as well. The simulation results show that the proposed method has been more useful and efficient. [ABSTRACT FROM AUTHOR]

This paper presents some aspects of robust control structure of DFIG-based wind turbine: drivetrain control and doubly fed induction generator control. Models of horizontal axis wind turbines and the theoretical principles of robust control that provides high performances under model uncertainties is presented. For the drivetrain, a state-space model is used to determine the transfer functions. For the induction generator, a vector control structure with stator flux orientation has adopted. An H-infinity controller is proposed for the drivetrain presents and a fractional order proportional integral controller (FOPI) is proposed for control the generator currents. With these controllers, high performances is obtained compared to conventional proportional integral controllers (PI) in the presence of external disturbances, measurement noises and turbine parameter variations. This paper an H-infinity controller and fractional order controller design methods presents. Comparative results of simulations, realized in Matlab-Simulink, are presented and include the control of the drivetrain with H-infinity controller and PID controller and the vector control of DFIG with a FOPI controller and a conventional PI controller. [ABSTRACT FROM AUTHOR]

In this study, an optimal and robust fractional order PID (FOPID) controller design approach is suggested for Smith predictor based FOPID (SP-FOPID) control system design. This new design approach considers continued fraction expansion (CFE) based approximate models in the optimal design task of FOPID controllers, and this approach preserves the design optimality in control applications. For this purpose, an inverse controller loop shaping design methodology is performed in order to approximate the frequency response of a Bode's ideal loop reference model, and robust performance CFE based FOPID controller models are obtained by solving a multi-objective optimisation problem via a genetic algorithm. Thus, the suggested algorithm can deal with several controller realisation concerns in the design task of FOPID controllers and overcome real-world controller performance issues related with model approximation errors and signal saturation boundaries of electronic hardware. Illustrative design examples demonstrate that the suggested design scheme can preserve design optimality and improve practical control performance in practice. [ABSTRACT FROM AUTHOR]

In this paper, a new optimal and robust IMC-PID control design is proposed for the LFC of time-delayed power systems. The proposed design is a process reduction control approach. Primitively, a simple and approximate model (i.e. Reduced Order Model (ROM)) is determined for the large-scale power system by using the proposed Enhanced Differential Evolution (EDE) algorithm-based Model Order Reduction (MOR) approach. Further, by considering the ROM as an internal plant model, the unknown IMC filter time constant is tuned to attain the optimal performance by minimizing the integral of error between the reference input and the actual output responses of the power system by using the EDE algorithm. Finally, the finest PID controller gains are determined by the least-square model matching with the optimal IMC. The proposed design is illustrated by applying to various Single-Area Power Systems (SAPS) with a delay between the power system sensing device to the control centre. The simulation results demonstrate the efficacy of the proposed IMC-PID design in improving the dynamic stability against consistent and inconsistent delays and the robustness towards the load disturbances, parameter uncertainties and model mismatches. [ABSTRACT FROM AUTHOR]