Performance analysis of IMC-PID controller on PCT-14 air pressure control system.

This research presents a comprehensive performance analysis of the IMC-PID controller implemented in the PCT-14 air pressure control system, a platform ideal for experimenting with various control methodologies. The study aims to compare the effectiveness of the IMC-PID controller with IMC-PIDF, Good Gain - PID and Skogestad's - PI controllers, focusing on response time characteristics based on the simulation of the PCT-14's transfer function. Performance analysis is conducted by comparing system response characteristics to set point changes, including rise time, overshoot, settling time, peak time, and steady-state error. To validate the controller's effectiveness, performance index value such as Integrated Absolute Error (IAE) was calculated. The research findings indicate that the IMC-based PID controller outperforms the Good Gain - PID, Skogestad-PI, and IMC-PIDF controllers in handling set point changes.•Simulating the transfer function of the PCT-14 air pressure control system to examine the response time characteristics of the IMC-PID, IMC-PIDF, Good Gain - PID, and Skogestad's - PI controllers.•Conducting a performance analysis by comparing system response characteristics in response to changes in set point values.•Calculating performance index value, IAE to assess the controllers' effectiveness.

Immune or inherited thrombocytopenia? A population-based cohort study on children and adolescents presenting with a low platelet count.

BACKGROUND: Thrombocytopenia is a common hematologic finding in children and adolescents. Immune thrombocytopenia (ITP) is the most common cause of this finding, but the differential diagnosis includes a growing list of genetic disorders. We aimed to report differences in phenotypes of patients with ITP, inherited platelet disorder (IPD)/primary immunodeficiency disorder (PID), and other causes, with a focus on differentiating ITP from inherited thrombocytopenia. PROCEDURE: This retrospective, population-based observational cohort from 2006 to 2020 involved 506 Finnish children under 16 years of age presenting with isolated thrombocytopenia. RESULTS: Of the 506 participants, 79.7% had ITP, 6.7% had IPD/PID, and 13.6% had other causes of thrombocytopenia. A platelet count of ≤12 × 109/L best distinguished between ITP and other reasons with a sensitivity of 60% and a specificity of 80%. Among patients with the lowest platelet count of less than 10 × 109/L, 95.9% had ITP, 3.3% had IPD/PID, and 0.8% had other causes. Severe bleeding events were reported in 20 patients (4.0%), but there were no cases of intracranial or fatal bleeding due to thrombocytopenia. Up to 50% of patients with a high suspicion of inherited thrombocytopenia remained without a specific diagnosis despite genetic testing. CONCLUSIONS: ITP remains the most common cause of thrombocytopenia. A platelet count of ≤12 × 109/L often leads to an ITP diagnosis. Genetic disorders are rare but should be suspected in patients with persisting thrombocytopenia, especially with platelet counts constantly above 12 × 109/L, a positive family history, or atypical clinical features.

Performance comparison between PID and Fuzzy logic controllers for the hardware implementation of traditional high voltage DC-DC boost converter.

This research introduces a hardware implementation of DC-DC boost converter designed to elevate the DC voltage generated by renewable sources while effectively regulating it against line and load fluctuations for inverter application. The main objective is to boost the DC link voltage to the level of Vmax in the output AC voltage obtained from inverter circuits. This enables the inverters for transformer-less power conversion from DC to AC to reduce magnetic losses, size and weight of the inverter circuits used in the utility application. The proposed converter's topology and switching sequences play a crucial role in enhancing overall performance. Utilizing a Zero Current Switching (ZCS) technique, the converter efficiently recovers stored energy from the magnetics. The proposed converter attained the output voltage of 350 V at its current of 1A from the input voltage of 20 V at its current of 19 A. The ZCS technique and the topology of the converter enhances the efficiency to 92 %. The study employs traditional Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers for effective voltage regulation, analysing time domain specifications. Additionally, a Fuzzy logic controller is introduced as an alternative to PID controllers to compare their performance metrics, evaluating the optimization of the converter's transient and steady-state behaviours. The proposed converter is designed, simulated and their performance metrics are analysed using MATLAB for both with and without controllers. The step-time characteristics of the proposed converter with load resistance of RL = 500 Ω and an input voltage of Vi = 20 V has been determined and analysed. The PID system attained a rise time of 88.781 ms, an overshoot value of 9.341 %, and a steady-state error of 0.00043. The fuzzy system achieved a low-rise time of 10.624 ms, a low overshoot of 0.55 %, and a steady-state error of 0.0584. The hardware prototype of the proposed converter is implemented with a FPGA based PID and Fuzzy logic controllers for providing better voltage regulation and to improve the performance metrics of the converter. The simulation and experimental findings are contrasted, examined, and confirmed to ensure improved consistency in performance measures.

Design of MEMS Pressure Sensor Anti-Interference System Based on Filtering and PID Compensation.

Due to the inherent temperature drift and lack of static stability in traditional pressure sensors, which make it difficult for them to meet the increasing demands of various industries, this paper designs a new system. The proposed system integrates temperature measurement and regulation circuits, signal processing, and communication circuits to accurately acquire and transmit pressure sensor data. The system designs a filtering algorithm to filter the original data and develops a data-fitting operation to achieve error compensation of the static characteristics. In order to eliminate the temperature drift problem of the sensor system, the system also adopts an improved PID thermostatic control algorithm to compensate for the temperature drift. Finally, it can also transmit the processed pressure data remotely. The experimental results show that the nonlinear error at 50 °C is reduced from the initial 1.82% to 0.24%; the hysteresis error is significantly reduced from 1.23% to 0.046%; and the repeatability error control is reduced from 3.79% to 0.89%. By compensating for thermal drift, the system's thermal sensitivity drift coefficient is reduced by 74.67%, the thermal zero drift coefficient is reduced by 66.24%, and the wireless communication range is up to 1km. The above significant optimization results fully validate the high accuracy and stability of the system, which is perfectly suited for demanding pressure measurement applications.

Dynamic impact analysis of the time-delay levitation control system on maglev vehicle system after adding smith predictor.

The time delay (TD) in the levitation control system significantly affects the dynamic performance of the closed-loop system in electromagnetic suspension (EMS) maglev vehicles. Excessive TD can cause levitation instability, making it essential to explore effective mitigation methods. To address this issue, a Smith Predictor (SP) is integrated into the traditional PID levitation control system. The combination of theoretical analysis and numerical simulation is employed to assess the stability of the time-delay levitation control system after the integration of the Smith Predictor. Theoretical analysis reveals that when TD exceeds a critical threshold, the levitation system becomes unstable. The addition of SP alters the root trajectory of the system characteristic equation from positive to negative, and recovers the levitation system to stable status. Assuming complete knowledge of the dynamic system, the TD compensation value in the SP becomes a key parameter that determines its performance. A minimum effective value (MEV) for TD compensation is identified, correlating with the system's stability region. Under the influence of TD, more complex systems and higher running speeds of the maglev vehicle lead to a narrower stable region and a larger MEV for TD compensation. Given the simulation parameters in this paper, with a system TD of 15 ms and a maximum vehicle speed of 160 km/h, the MEV for TD compensation in the SP should be set at 12 ms.

FOPDT model and CHR method based control of flywheel energy storage integrated microgrid.

The main causes of frequency instability or oscillations in islanded microgrids are unstable load and varying power output from distributed generating units (DGUs). An important challenge for islanded microgrid systems powered by renewable energy is maintaining frequency stability. To address this issue, a proportional integral derivative (PID) controller is designed in this article. Firstly, islanded microgrid model is constructed by incorporating various DGUs and flywheel energy storage system (FESS). Further, considering first order transfer function of FESS and DGUs, a linearized transfer function is obtained. This transfer function is further approximated into first order plus time delay (FOPTD) form to design PID control strategy, which is efficient and easy to analyze. PID parameters are evaluated using the Chien-Hrones-Reswick (CHR) method for set point tracking and load disturbance rejection for 0% and 20% overshoot. The CHR method for load disturbance rejection for 20% overshoot emerges as the preferred choice over other discussed tuning methods. The effectiveness of the discussed method is demonstrated through frequency analysis and transient responses and also validated through real time simulations. Moreover, tabulated data presenting tuning parameters, time domain specifications and comparative frequency plots, support the validity of the proposed tuning method for PID control design of the presented islanded model.

Efficient DC motor speed control using a novel multi-stage FOPD(1 + PI) controller optimized by the Pelican optimization algorithm.

This paper introduces a novel multi-stage FOPD(1 + PI) controller for DC motor speed control, optimized using the Pelican Optimization Algorithm (POA). Traditional PID controllers often fall short in handling the complex dynamics of DC motors, leading to suboptimal performance. Our proposed controller integrates fractional-order proportional-derivative (FOPD) and proportional-integral (PI) control actions, optimized via POA to achieve superior control performance. The effectiveness of the proposed controller is validated through rigorous simulations and experimental evaluations. Comparative analysis is conducted against conventional PID and fractional-order PID (FOPID) controllers, fine-tuned using metaheuristic algorithms such as atom search optimization (ASO), stochastic fractal search (SFS), grey wolf optimization (GWO), and sine-cosine algorithm (SCA). Quantitative results demonstrate that the FOPD(1 + PI) controller optimized by POA significantly enhances the dynamic response and stability of the DC motor. Key performance metrics show a reduction in rise time by 28%, settling time by 35%, and overshoot by 22%, while the steady-state error is minimized to 0.3%. The comparative analysis highlights the superior performance, faster response time, high accuracy, and robustness of the proposed controller in various operating conditions, consistently outperforming the PID and FOPID controllers optimized by other metaheuristic algorithms. In conclusion, the POA-optimized multi-stage FOPD(1 + PI) controller presents a significant advancement in DC motor speed control, offering a robust and efficient solution with substantial improvements in performance metrics. This innovative approach has the potential to enhance the efficiency and reliability of DC motor applications in industrial and automotive sectors.

Research on Adaptive Closed-Loop Control of Microelectromechanical System Gyroscopes under Temperature Disturbance.

Microelectromechanical System (MEMS) gyroscopes are inertial sensors used to measure angular velocity. Due to their small size and low power consumption, MEMS devices are widely employed in consumer electronics and the automotive industry. MEMS gyroscopes typically use closed-loop control systems, which often use PID controllers with fixed parameters. These classical PID controllers require a trade-off between overshoot and rise time. However, temperature variations can cause changes in the gyroscope's parameters, which in turn affect the PID controller's performance. To address this issue, this paper proposes an adaptive PID controller that adjusts its parameters in response to temperature-induced changes in the gyroscope's characteristics, based on the error value. A closed-loop control system using the adaptive PID was developed in Simulink and compared with a classical PID controller. The results demonstrate that the adaptive PID controller effectively tracked the changes in the gyroscope's parameters, reducing overshoot by 96% while maintaining a similar rise time. During gyroscope startup, the adaptive PID controller achieves faster stabilization with a 0.036 s settling time, outperforming the 0.06 s of the conventional PID controller.

Hybrid golden jackal and golden sine optimizer for tuning PID controllers.

In the domain of control engineering, effectively tuning the parameters of proportional-integral-derivative (PID) controllers has persistently posed a challenge. This study proposes a hybrid algorithm (HGJGSO) that combines golden jackal optimization (GJO) and golden sine algorithm (Gold-SA) for tuning PID controllers. To accelerate the convergence of GJO, a nonlinear parameter adaptation strategy is incorporated. The improved GJO is combined with Gold-SA, capitalizing on the expedited convergence speed offered by the improved GJO, coupled with the global optimization and precise search capabilities of Gold-SA. HGJGSO maximizes the strengths of two algorithms, facilitating a comprehensive and balanced exploration and exploitation. The effectiveness of HGJGSO is assessed through tuning the PID controllers for three typical systems. The results indicate that HGJGSO surpasses the comparison tuning methods. To evaluate the applicability of HGJGSO, it is used to tune the cascade PID controllers for trajectory tracking in a quadrotor UAV. The results demonstrate the superiority of HGJGSO in addressing practical challenges.

Unraveling the unphosphorylated STAT3-unphosphorylated NF-κB pathway in loss of function STAT3 Hyper IgE syndrome.

Background: Patients with loss of function signal transducer and activator of transcription 3-related Hyper IgE Syndrome (LOF STAT3 HIES) present with recurrent staphylococcal skin and pulmonary infections along with the elevated serum IgE levels, eczematous rashes, and skeletal and facial abnormalities. Defective STAT3 signaling results in reduced Th17 cells and an impaired IL-17/IL-22 response primarily due to a compromised canonical Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway that involves STAT3 phosphorylation, dimerization, nuclear translocation, and gene transcription. The non-canonical pathway involving unphosphorylated STAT3 and its role in disease pathogenesis, however, is unexplored in HIES. Objective: This study aims to elucidate the role of unphosphorylated STAT3-unphosphorylated NF-κB (uSTAT3-uNF-κB) activation pathway in LOF STAT3 HIES patients. Methodology: The mRNA expression of downstream molecules of unphosphorylated STAT3-unphosphorylated NF-κB pathway was studied in five LOF STAT3 HIES patients and transfected STAT3 mutants post-IL-6 stimulation. Immunoprecipitation assays were performed to assess the binding of STAT3 and NF-κB to RANTES promoter. Results: A reduced expression of the downstream signaling molecules of the uSTAT3-uNF-κB complex pathway, viz., RANTES, STAT3, IL-6, IL-8, ICAM1, IL-8, ZFP36L2, CSF1, MRAS, and SOCS3, in LOF STAT3 HIES patients as well as the different STAT3 mutant plasmids was observed. Immunoprecipitation studies showed a reduced interaction of STAT3 and NF-κB to RANTES in HIES patients. Conclusion: The reduced expression of downstream signaling molecules, specially RANTES and STAT3, confirmed the impaired uSTAT3-uNF-κB pathway in STAT3 LOF HIES. Decreased levels of RANTES and STAT3 could be a significant component in the disease pathogenesis of Hyper IgE Syndrome.

Establishment of the microscope incubation system and its application in evaluating tumor treatment effects through real-time live cellular imaging.

Introduction: Long-term imaging of live cells is commonly used for the study of dynamic cell behaviors. It is crucial to keep the cell viability during the investigation of physiological and biological processes by live cell imaging. Conventional incubators that providing stable temperature, carbon dioxide (CO2) concentration, and humidity are often incompatible with most imaging tools. Available commercial or custom-made stage-top incubators are bulky or unable to provide constant environmental conditions during long time culture. Methods: In this study, we reported the development of the microscope incubation system (MIS) that can be easily adapted to any inverted microscope stage. Incremental PID control algorithm was introduced to keep stable temperature and gas concentration of the system. Moreover, efficient translucent materials were applied for the top and bottom of the incubator which make it possible for images taken during culture. Results: The MIS could support cell viability comparable to standard incubators. When used in real time imaging, the MIS was able to trace single cell migration in scratch assay, T cell mediated tumor cells killing in co-culture assay, inflation-collapse and fusion of organoids in 3D culture. And the viability and drug responses of cells cultured in the MIS were able to be calculated by a label-free methods based on long term imaging. Discussion: We offer new insights into monitoring cell behaviors during long term culture by using the stage adapted MIS. This study illustrates that the newly developed MIS is a viable solution for long-term imaging during in vitro cell culture and demonstrates its potential in cell biology, cancer biology and drug discovery research where long-term real-time recording is required.

2DOF-PID-TD: A new hybrid control approach of load frequency control in an interconnected thermal-hydro power system.

The Load Frequency Control (LFC) scheme, with its primary aim being the maintenance of uniform frequency, has been a heavily researched topic for decades. Achieving a consistent frequency necessitates a delicate balance between load demand and power generation. Researchers strive to find an optimal solution within the LFC domain-one that can effectively withstand drastic load fluctuations. Despite a plethora of efforts, the LFC dilemma remains unresolved, complicated by factors such as dwindling demand-supply and the rapid integration of renewables. Furthermore, the lack of innovation in controller structure design exacerbates the complexity of solving modern LFC problems. Consequently, a robust control approach capable of handling uncertainties while simultaneously regulating system frequency becomes crucial. In light of this, we propose a novel hybrid control architecture called 2DOF-PID-TD. This architecture combines Two Degrees Of Freedom Proportional-Integral-Derivative (2DOF-PID) and Tilt-Derivative (TD) controllers. To optimize the proposed controller, we employ a metaheuristic called the Artificial Gorilla Troops Optimizer (AGTO), which mimics the social behavior and intelligence of gorilla troops. The proposed approach is analyzed in a realistic multi-area multi-source hydro-thermal system, accounting for nonlinearities, random load perturbations, and system parametric uncertainties. Experimental results, when compared with current state-of-the-art optimization algorithms and traditional controller structures, demonstrate the prowess of our approach in terms of precision, robustness, and resilience.

A Proportional-Integral-Derivative type regulation scheme with non-Lipschitz control actions for mechanical systems with constrained inputs.

Motivated by the benefits that recent finite-time continuous control approaches have proven to give rise, this work aims to design a proportional-integral-derivative (PID) type control scheme for the global regulation of constrained-input mechanical systems that incorporates design features characteristic of such finite-time continuous algorithms. This is proven to be achieved through a more general PID type control structure that incorporates exponential weights on the P and D type terms, through which such control actions are permitted to loose Lipschitz-continuity at the desired equilibrium values. This entails an important challenge consisting on the introduction of an appropriate analytical framework and the development of a suitable closed-loop analysis through which the resulting design is properly supported. The study is complemented by experimental tests which show that appropriate (less-than-unity) values on the incorporated exponential weights indeed give rise to closed-loop improvements characteristic of finite-time continuous control approaches, such as reduction of overshoot on the position error responses and of the control effort, alleviating such a performance adjustment task.

Fuzzy-PID controller based sliding-mode for suppressing low frequency oscillations of the synchronous generator.

A novel intelligent stabilizer is designed to address the issue of low-frequency electromechanical oscillations in a synchronous generator in this article. This stabilizer incorporates three controllers: a three-level sliding mode controller, a fuzzy logic controller, and a proportional-integral-derivative (PID) controller enhanced through genetic algorithm optimization. The discontinuous segments of the first two levels of the sliding mode controller are substituted with fuzzy-PID links, utilizing error and its rate of change to adjust stabilizer parameters. The discontinuous portion of the third level is replaced by a saturation function to constrain current within permissible limits. The advantage of this proposed controller is that it integrates the benefits of the three constituent controllers and is capable of handling a wide range of disturbances. Additionally, thanks to the fuzzy engine, which considers error variations, there is no longer a need to calculate the error derivative, which could amplify measurement noise. The proposed stabilizer is compared to available literature results. As a result, the proposed stabilizer exhibits an undershoot of -0.003, an overshoot of 0.001, a response time of 0.01s, high robustness for parameter variations ranging from 0.5 to 4 times the nominal value, and very rapid suppression of oscillations compared to other controllers.

Implementation of Rapid Nucleic Acid Amplification Based on the Super Large Thermoelectric Cooler Rapid Temperature Rise and Fall Heating Module.

In the rapid development of molecular biology, nucleic acid amplification detection technology has received more and more attention. The traditional polymerase chain reaction (PCR) instrument has poor refrigeration performance during its transition from a high temperature to a low temperature in the temperature cycle, resulting in a longer PCR amplification cycle. Peltier element equipped with both heating and cooling functions was used, while the robust adaptive fuzzy proportional integral derivative (PID) algorithm was also utilized as the fundamental temperature control mechanism. The heating and cooling functions were switched through the state machine mode, and the PCR temperature control module was designed to achieve rapid temperature change. Cycle temperature test results showed that the fuzzy PID control algorithm was used to accurately control the temperature and achieve rapid temperature rise and fall (average rising speed = 11 °C/s, average falling speed = 8 °C/s) while preventing temperature overcharging, maintaining temperature stability, and achieving ultra-fast PCR amplification processes (45 temperature cycle time < 19 min). The quantitative results show that different amounts of fluorescence signals can be observed according to the different concentrations of added viral particles, and an analytical detection limit (LoD) as low as 10 copies per µL can be achieved with no false positive in the negative control. The results show that the TEC amplification of nucleic acid has a high detection rate, sensitivity, and stability. This study intended to solve the problem where the existing thermal cycle temperature control technology finds it difficult to meet various new development requirements, such as the rapid, efficient, and miniaturization of PCR.

DS based 2-DOF PID controller for various integrating processes with time delay.

This study proposes a direct synthesis-based two-degree-of-freedom (2-DOF) controller for various types of integrating processes with time delays. This 2-DOF controller includes a proportional-integral-derivative (PID) controller to enhance load disturbance rejection performance and a set-point filter to improve servo response performance. The main PID controller parameters are expressed as process model parameters and a single adjustment variable, while the set-point filter is composed of PID controller parameters with weighted factors. The adjustment variable is tuned to achieve an optimal balance between response performance and robustness, based on the maximum magnitude of the sensitivity function (Ms). Controller parameters for various Ms values and guidelines for setting these parameters are provided in a consistent formulaic form using a curve-fitting method. These parameter-setting formulas facilitate the accurate implementation of PID controllers with specified Ms values and allow the controller design to be extended to processes with larger dimensionless time delays for a given Ms value. Although a 2-DOF controller was proposed, the adjustment variable for setting the parameters of the main PID controller and the set-point filter was solely the desired time constant. The proposed method was applied to various integrating processes with time delays, and its performance was compared with existing methods reported in the literature, based on performance indices such as settling time, overshoot, integral of absolute error, total variation in input usage, and global performance index. Simulations were conducted using six examples of various integrating processes with time delays to verify the effectiveness and applicability of the proposed controller.

Advanced temperature control in ethanol fermentation using a PSO-PID controller with split-range control strategy.

Global energy demand is experiencing a notable surge due to growing energy security. Renewable energy sources, like ethanol, are becoming more viable. In the present study, the application of a PSO-PID (Particle Swarm Optimization - Proportional Integral Derivative) controller with a split-range control strategy was suggested for the regulation of temperature within the fermentation system. To optimize performance, a POS-PID controller with a split-range arrangement utilizing two control valves for hot and cold utilities was constructed. The study began by examining the open-loop dynamic response of the system to inlet temperature and concentration disturbances during ethanol production fermentation. Subsequently, a transfer function model was developed through linearization at the steady-state operating point. The split-range controller structure, implemented by optimizing the PSO-PID controller parameters using PSO, effectively demonstrated temperature control in simulations of a nonlinear model. In this investigation, the ethanol fermentation system was modeled as a CSTR using a modified Monod equation for microbial growth kinetics. Various dynamic behavioral disturbances were explored and verified in the model with plant data in this study. The simulation model results were validated through plant data. The proposed method showed superior closed-loop performance with respect to errors, with the actuators proving to be effective than other reported methods for temperature control.

Exponential PID controller for effective load frequency regulation of electric power systems.

Load frequency regulation (LFR) is an indispensable scheme in planning electrical power production to provide consumers with stable, reliable and uninterrupted power. In the face of complicated power system (PS) structures with increasing and intricate power demand, new controllers that offer not only good performance, but also easy commissioning in practice are required. To this end, this research introduces an exponential PID (EXP-PID) controller as a new control scheme to ameliorate the LFR performance of PSs. This controller is simple to design and has a nonlinear feature inherited from two tunable exponential functions, which are placed in front of the PID controller and act on the error signal and its time derivative individually. To achieve the utmost performance, the EXP-PID controller's parameters are procured by a corrected variant of the snake optimizer (co-SO). To validate the proposed control scheme, various single-/multi-area single-/multi-source PSs favored in the area are considered as test benches. A thorough comparison with the state-of-the-art approaches is performed to disclose the true efficacy of our proposal. Among the rivals, co-SO tuned EXP-PID controller, despite its simplicity, is found to render credible and promising performance in mitigating frequency and tie-line power deviations effectively.

A new hybrid learning control system for robots based on spiking neural networks.

This paper presents a new hybrid learning and control method that can tune their parameters based on reinforcement learning. In the new proposed method, nonlinear controllers are considered multi-input multi-output functions and then the functions are replaced with SNNs with reinforcement learning algorithms. Dopamine-modulated spike-timing-dependent plasticity (STDP) is used for reinforcement learning and manipulating the synaptic weights between the input and output of neuronal groups (for parameter adjustment). Details of the method are presented and some case studies are done on nonlinear controllers such as Fractional Order PID (FOPID) and Feedback Linearization. The structure and the dynamic equations for learning are presented, and the proposed algorithm is tested on robots and results are compared with other works. Moreover, to demonstrate the effectiveness of SNNFOPID, we conducted rigorous testing on a variety of systems including a two-wheel mobile robot, a double inverted pendulum, and a four-link manipulator robot. The results revealed impressively low errors of 0.01 m, 0.03 rad, and 0.03 rad for each system, respectively. The method is tested on another controller named Feedback Linearization, which provides acceptable results. Results show that the new method has better performance in terms of Integral Absolute Error (IAE) and is highly useful in hardware implementation due to its low energy consumption, high speed, and accuracy. The duration necessary for achieving full and stable proficiency in the control of various robotic systems using SNNFOPD, and SNNFL on an Asus Core i5 system within Simulink's Simscape environment is as follows: - Two-link robot manipulator with SNNFOPID: 19.85656 hours - Two-link robot manipulator with SNNFL: 0.45828 hours - Double inverted pendulum with SNNFOPID: 3.455 hours - Mobile robot with SNNFOPID: 3.71948 hours - Four-link robot manipulator with SNNFOPID: 16.6789 hours. This method can be generalized to other controllers and systems like robots.

Adaptive Control for a Two-Axis Semi-Strapdown Stabilized Platform Based on Disturbance Transformation and LWOA-PID.

A two-axis semi-strapdown stabilized platform is a device designed to eliminate aircraft disturbances and ensure the stability of the sensor's orientation. A traditional two-axis semi-strapdown stabilization platform for aircraft can effectively control disturbance in pitch and yaw channel, but it cannot achieve ideal disturbance control in the roll channel. In order to solve this problem, an adaptive control method based on disturbance transformation and LWOA-PID is proposed. Disturbance transformation is the process of integrating the angular position disturbance of the roll from the previous moment into the combined disturbance of the pitch and yaw at the current moment. This is followed by decoupling the combined disturbance of the pitch and yaw at the current moment, thereby eliminating the disturbance caused by the roll from the previous moment. This process is repeated to achieve the goal of eliminating roll channel disturbances. To ensure the line of sight (LOS) pointing accuracy stability in the two-axis semi-strapdown stabilized platform system for aircraft, a whale optimization adaptive proportional-integral-derivative (LWOA-PID) controller based on Latin hypercube sampling is designed. It is then compared with the classical PID controller in Matlab/Simulink. The simulation results indicate that the disturbance conversion module proposed in this paper can eliminate the impact of roll axis disturbances on the LOS pointing accuracy of the two-axis semi-strapdown stabilized platform for aircraft. Compared to the classical PID controller, the LWOA-PID controller reduces tracking errors for step and sinusoidal signals by 50% and 75%, respectively. It also shortens optimization time by 37.5% compared to the WOA-PID while maintaining the same level of accuracy. Furthermore, when combined with the conversion module, the tracking error is reduced by an additional order of magnitude.