Control Technique Research Articles

Enhanced performance of a parallel manipulator with hybrid joint-space and task-space control approaches

Abstract This paper introduces two enhanced control approaches to improve the performance of parallel manipulators, addressing their inherent nonlinear dynamics and complex structure. The first approach results in a hybrid control system in joint space, integrating acceleration-based control, sliding mode, and disturbance observer techniques. The control system is designed to correct tracking errors and compensate for generalized disturbances, thus improving accuracy in tracking reference positions. The second approach merges the joint-space and task-space formulations, implementing proportional-derivative controllers in task space to manage the end-effector positions while maintaining safe operational configurations. The stability of the proposed controllers is demonstrated through Lyapunov analysis, while their performance is validated through comprehensive simulations and real-time experiments.

Machining deformation control technique based on stress-sensitive region and direction analysis

Machining deformation control technique based on stress-sensitive region and direction analysis

Multiload Resonant Inverter With Boosting for All‐Metal Domestic Induction Heating System

ABSTRACTInduction heating (IH) systems have gained significant attention because of their high efficiency, rapid heating, versatility, and precise control. Induction cooking (IC) is one of the primary domestic applications of IH technology. Traditional IC systems typically employ single‐frequency inverters optimized for ferromagnetic (FM) material loads. This approach presents limitations when confronted with various cookware materials including nonferromagnetic (NFM) materials. To address the growing demand for multimaterial load IC systems with enhanced performance and flexibility, a multiload resonant inverter integrated with boosting is proposed with a double full‐bridge three‐leg architecture. The proposed system features three independent legs, each operating at a different frequency to power three different material loads. Integrating this topology with boost functionality enhances performance and optimizes energy utilization. Pulse frequency modulation (PFM) and asymmetrical duty cycle (ADC) control techniques are used to control the load powers independently and simultaneously. A detailed analysis of the inverter and its design procedure is presented. A 1.5‐kW hardware prototype is designed, and the experimental results are in good agreement with the simulation results.

Investigating The Flapped Horizontal Axial Wind Turbine Experimentally to Improve Power coefficient and Stability

This paper investigates the potential of deploying flaps on wind turbine blades to enhance their efficiency and energy capture capabilities. The FX66-S-196V, FX63-137 S, and SG6043 supercritical airfoils were used and distributed along the blade radius. Flaps, situated 20% along the trailing edge of the blade chord, offer a means of actively controlling aerodynamic forces and optimizing blade performance under varying wind conditions. Through computational fluid dynamics (CFD) simulations and optimization techniques. The aerodynamic effects of flap deployment on wind turbine blades are analyzed. The study explores the impact of flap angle, position, and deployment strategy on key performance metrics such as power coefficient, lift-to-drag ratio, and energy extraction efficiency. Results demonstrate that judiciously deploying flaps can lead to significant improvements in turbine efficiency, with power output enhancements ranging from 2.5% to 4.6%, depending on operating conditions such as wind speed, tip speed ratio, angle of attack, and flap angle setting. Furthermore, sensitivity analysis reveals optimal flap configurations for different wind regimes, highlighting the importance of adaptive control strategies. This research contributes to the growing body of knowledge on active aerodynamic control techniques for wind turbine optimization and underscores the potential of flaps as a viable means of enhancing wind turbine blade efficiency in practical applications.

Modeling, Monitoring, and Controlling Road Traffic Using Vehicles to Sense and Act

This review offers a comprehensive overview of current traffic modeling, estimation, and control methods, along with resulting field experiments. It highlights key developments and future directions in leveraging technological advancements to improve traffic management and safety. The focus is on macroscopic, microscopic, and micro-macro models, as well as state-of-the-art control techniques and estimation methods for deploying vehicles in traffic field experiments.

Minimization of torque ripple in the BLDC drive using a high performance novel switched inductor QZS converter

Abstract In brushless direct current drives, ripple during commutation is an important issue that arises during speed changes and transitions, as the incoming and outgoing phase currents vary at different rates simultaneously. This research study introduces a novel approach to minimize the variation in the commutation torque of a BLDC motor. The strategy involves the use of a quasi-Z source-based DC-DC converter circuit with a switched inductance. A comprehensive study of torque variations in both the commutation and conduction zones is performed for the BLDC drive, and a switching inductor quasi-Z source DC-DC converter has been built alongside the three-phase voltage source inverter to minimize the variation in commutation torque. The control technique and switch selector circuit have been integrated to attain the intended input direct current voltage throughout the commutation phase. The novel methodology being examined has been developed utilizing the MATLAB/Simulink software. By presenting simulation data, the efficacy of the proposed system and traditional BLDC drive is validated.

8. Groundwater Control

Groundwater control techniques can be used to avoid or mitigate groundwater problems that can affect below ground construction works, both in the temporary case during construction, and under permanent or long-term conditions. There are two main categories of groundwater control techniques: pumping methods (also known as construction dewatering), whereby groundwater levels are lowered by pumping from an array of wells or sumps; and exclusion, methods where low permeability barriers (cut-off walls or zones of ground treatment) are installed around an excavation or structure to prevent or reduce groundwater inflows. Often a combination of these two approaches is appropriate. This Chapter describes the characteristics and application of groundwater control methods.

Managing Machine Learning Complexity with Advanced Version Control Techniques

Managing Machine Learning Complexity with Advanced Version Control Techniques

Model-Free Swing-Up and Balance Control of a Rotary Inverted Pendulum using the TD3 Algorithm: Simulation and Experiments

The Rotary Inverted Pendulum (RIP) system is a highly nonlinear and under-actuated mechanical system, which presents significant challenges for traditional control techniques. In recent years, Reinforcement Learning (RL) has emerged as a prominent nonlinear control technique, demonstrating efficacy in regulating systems exhibiting intricate dynamics and pronounced nonlinearity. This research presents a novel approach to the swing-up and balance control of the RIP system, employing a RL algorithm, Twin Delayed (TD3) Deep Deterministic Policy Gradient (DDPG), obviating the necessity for a predefined mathematical model. The physical model of the RIP was designed in SolidWorks and subsequently transferred to MATLAB Simscape and Simulink for the purpose of training the RL agent. The system was successfully trained to perform both swing-up and balance control using a single algorithm for both tasks, representing a significant innovation that eliminates the need for two or more separate algorithms. Additionally, the trained agent was successfully deployed onto an experimental model, with the results demonstrating the feasibility and effectiveness of the model-free TD3 approach in controlling under-actuated mechanical systems with complex dynamics, such as the RIP. Furthermore, the results highlight the sim-to-real transfer capability of this method.

Intelligence Based Controlling Models for Effective Power Tracking and Voltage Enhancement in Grid-PV Systems

The underlying research work is focused on enhancement in the efficiency and voltage gain for solar PV systems with the help of designing a novel regulating framework that includes advanced converter topologies integrated with intelligent control techniques. Optimization in extracting energy from the solar panel at different climatic conditions, voltage gain with minimum losses, and enhancing overall system efficiency and power quality are major tasks to be undertaken. The proposed control architecture presents a new Fractional Order Proportional-Integral-Derivative Control (FOPTC) technique and its adaptation mechanism for correct MPPT under dynamic variations of meteorological conditions. Consequently, it offers improved energy harvesting because it is able to identify the global maximum power point with higher speed and precision than traditional control techniques that apply hybrid approaches. The improved topological structure will ensure a substantial rise in voltage gain and efficiency with reduced voltage and current stresses upon the circuit components. In addition, the idea of a Neuro Feed Quadratic Controller (NFQC) is introduced to generate the regulating pulses for switching components of the converter for optimizing the voltage conversion process. Simulation and analytical studies confirm the higher efficiency, improved voltage gain, and reduced total harmonic distortion in the proposed framework over conventional systems. Doi: 10.28991/ESJ-2025-09-01-015 Full Text: PDF

Integrating AI and advanced spectroscopic techniques for precision food safety and quality control

Integrating AI and advanced spectroscopic techniques for precision food safety and quality control

Reform and exploration of the experimental teaching mode of teaching assistant and group rotation system: taking pharmaceutical analysis experiment course as an example

Experimental courses in pharmaceutical analysis are an important part of the training process for pharmaceutical talent. These courses focus on applying theoretical knowledge in practice and using large instruments, with the aim of inspiring innovative thinking and cultivating student development. Currently, several issues impede the success of experimental pharmaceutical analysis courses both in China and abroad. In domestic colleges and universities, the content of these courses varies significantly and is relatively unsophisticated. Owing to economic and human resource limitations, students lack training in the operation and use of large analytical instruments. In foreign universities, the range of professional instruments is not comprehensive, experimental class hours are limited, and the availability of large instruments for experimental teaching is insufficient. The School of Pharmaceutical Science and Technology, Faculty of Medicine, Tianjin University, explored the teaching assistant system with group rotation for the delivery of experimental pharmaceutical analysis courses. In combination with the large instrument sharing platform of the school, this approach resulted in a relatively comprehensive teaching model. This model reduced the demand for experimental instruments at a certain time by extending the time axis, thereby relieving the pressure on large instrument allocation. Furthermore, a complete pharmaceutical analysis teaching program was designed according to the curriculum requirements, covering common analytical methods and instruments used in pharmaceutical analysis. With guidance from experimental teaching assistants, students consolidated their theoretical knowledge, mastered key techniques for drug quality control and the drug research process, and laid a foundation for developing new drug analysis methods. Over years of continuous exploration, this model has matured to achieve good teaching outcomes. This work can provide a reference for the development of experimental pharmaceutical analysis courses in domestic universities.

Artificial Intelligence without Restriction Surpassing Human Intelligence with Probability One: Theoretical Insight into Secrets of the Brain with AI Twins of the Brain

Artificial Intelligence (AI) has apparently become one of the most important techniques discovered by humans in history while the human brain is widely recognized as one of the most complex systems in the universe. One fundamental critical question which would affect human sustainability remains open: Will artificial intelligence (AI) evolve to surpass human intelligence in the future? This paper shows that in theory new AI twins with fresh cellular level of AI techniques for neuroscience could approximate the brain and its functioning systems (e.g. perception and cognition functions) with any expected small error and AI without restrictions could surpass human intelligence with probability one in the end. This paper indirectly proves the validity of the conjecture made by Frank Rosenblatt 70 years ago about the potential capabilities of AI, especially in the realm of artificial neural networks. This paper also gives the answer to the two widely discussed fundamental questions: 1) whether AI could have potentials of discovering new principles in nature; 2) whether error backpropagation (BP) algorithm commonly and efficiently used in tuning parameters in AI applications is also adopted in the brain. Intelligence is just one of fortuitous but sophisticated creations of the nature which has not been fully discovered. Like mathematics and physics, with no restrictions artificial intelligence would lead to a new subject with its self-contained systems and principles. We anticipate that this paper opens new doors for 1) AI twins and other AI techniques to be used in cellular level of efficient neuroscience dynamic analysis, functioning analysis of the brain and brain illness solutions; 2) new worldwide collaborative scheme for interdisciplinary teams concurrently working on and modelling different types of neurons and synapses and different level of functioning subsystems of the brain with AI techniques; 3) development of low energy of AI techniques with the aid of fundamental neuroscience properties; and 4) new controllable, explainable and safe AI techniques with reasoning capabilities of discovering principles in nature.

Adaptive control techniques for improving anti-lock braking system performance in diverse friction scenarios

Anti-lock braking systems (ABS) enhance vehicle safety by preventing wheel lock-up, but their effectiveness depends on tire-road friction. Traditional braking systems struggle to maintain effective performance due to the risk of wheel lock-up on varying road surfaces, affecting vehicle stability and control. This study presents a novel method to improve ABS efficiency across varying friction conditions. The proposed approach employs a feedback control mechanism to dynamically adjust the braking force of each wheel based on the prevailing friction coefficient. Specifically, we incorporate a P-controller in the input signal and two additional P-controllers as output and input parameters for friction. By manipulating the proportional control values, key parameters such as wheel speed, stopping distance, and slip rate can be effectively managed. Notably, our investigation reveals intriguing interactions between the proportional controls, highlighting the complexity of ABS optimization. The method was evaluated through simulations across various friction conditions, comparing it to conventional ABS in terms of brake performance, stability, and stopping distances. The results indicate that the proposed method significantly enhances ABS performance across varying friction coefficients; however, additional research is warranted to address stopping distance and time issues, particularly in snowy and icy conditions.

Unveiling hidden geometric phase of neutron spin rotation in the Bitter–Dubbers experiment

Abstract We propose a novel framework to describe geometric phases in quantum systems under non-adiabatic conditions by introducing the concept of a hidden geometric phase. Conventional geometric phases, such as the Berry phase, rely on adiabatic evolution, limiting their applicability in rapidly changing systems. Here, we remove this constraint by reinterpreting the geometric phase as arising from a dynamically evolving reference basis, independent of the external topological features. The hidden phase is revealed through transitionless quantum control techniques, ensuring pure geometric phase accumulation even in non-adiabatic regimes. Our method offers an exact solution to the neutron spin rotation phase in the Bitter–Dubbers experiment, aligning more closely with experimental data without depending on adiabatic approximations. This unexpected result broadens our understanding of the geometric phase observed in neutron spin rotation beyond the adiabatic conditions that are conventionally required.

Consolidated Microscale Interferon-γ Release Assay with Tip Optofluidic Immunoassay for Dynamic Parallel Diagnosis of Tuberculosis Infection.

Interferon-γ release assay (IGRA) is one of the most important diagnostic tools for tuberculosis (TB) infection. Despite its high accuracy, conventional IGRA has several drawbacks, including complicated procedures, large blood volume requirements, lengthy incubation times, and difficulties in parallel testing. Efforts have been made to develop miniaturized and highly sensitive biosensors for interferon-γ or to evaluate the specific immune response through microfluidic platforms. However, the need for sophisticated consumables and equipment, as well as the partial experimental design, has limited the application of these advanced techniques in TB diagnosis and disease control. Here, we report the development of a tip optofluidic immunoassay (TOI)-based consolidated microscale IGRA (CM-IGRA) for the dynamic and parallel evaluation of TB infection, refining both the blood incubation and interferon-γ quantification processes. The TOI system comprises 12 microfluidic immuno-reactors and a portable chemiluminescent imaging station, capable of quantifying interferon-γ with high sensitivity (8.00 pg/mL in plasma) and a wide detection range (∼104). The results generated with CM-IGRA achieved 98.39% agreement with the standard IGRA while reducing blood sample consumption to 50 μL per assay (20-fold reduction) and significantly shortening the incubation time from 20 to 10 h. This diagnostic method simplifies operations and improves efficiency for the parallel assays required in IGRA, providing a promising solution for TB screening in patients for whom current methods are inconvenient, such as children and older adults.

A review on soil erosion and its control techniques

This study focuses on Soil erosion, which is a critical environmental challenge, and has profound impacts on agriculture, biodiversity, and water quality. This paper explores the historical and contemporary perspectives of soil erosion in India and globally, highlighting its causes, impacts, and mitigation strategies. India's agrarian economy has long grappled with soil erosion, exacerbated by monsoon-driven climates and unsustainable practices. Traditional conservation methods were undermined during colonial and industrial periods, but modern initiatives like watershed management and soil loss estimation models have renewed focus on combating erosion. At the global level, projects like the GLASOD provide insights into the severity of degradation and the urgency for sustainable practices. In India's arid regions, such as the Thar Desert, wind patterns play a significant role in soil erosion. Seasonal winds cause displacement and nutrient loss, affecting agriculture, infrastructure, and ecosystems. The paper outlines various mitigation strategies, including vegetative barriers, sand fences, chemical stabilizers, and advanced technologies like precision agriculture and geotextiles. Despite progress, challenges persist, such as integrating traditional knowledge with modern techniques and addressing socio-economic barriers. Future directions emphasize holistic approaches, community involvement, and climate-resilient strategies to ensure sustainable soil and ecosystem management.

Flaky sputtered silicon MWCNTs core-shell structure as a freestanding binder-free electrode for lithium-ion battery

Core-shell silicon/multiwall carbon nanotubes are one of the most promising anode candidates for further improvement of lithium-ion batteries. Sufficient accommodation for massive volume expansion of silicon during the lithiation process and preventing pulverization and delamination with easy fabrication processes are still critical issues for practical applications. In this study, core-shell silicon/MWCNTs anode materials were synthesized using a facile and controllable PECVD technique to realize aligned MWCNTs followed by a silicon sputtering step. The use of the PECVD technique and the direct growth of multi-walled carbon nanotubes on the current collector creates a low tortuosity, flexible, and conductive scaffold, which, in addition to preventing CNT agglomeration, alleviates the pulverization and delamination of the silicon active material from the current collector, leading to the formation of an electrode with unique electrochemical performance. The CNT-Si core-shell electrode can achieve an excellent gravimetric specific capacity of 3250 mAh/g under a rate of C/5 and 99.8% capacity retention after more than 700 cycles. Electron microscopy revealed that the electrode structure has maintained its integrity and stability during long cycling (700 cycles and more). Apart from achieving high charging capacity, the use of such configuration leads to the formation of facile, inexpensive free-standing binder-free electrodes with no need to polymeric binders.

Linear and Non-Linear Optimal Control Methods to Determine the Best Chemotherapy Schedule for Most Effectively Inhibiting Tumor Growth

Background/Objectives: Cancer is a dynamic and complex disease that remains largely untreated despite major advances in oncology and treatment. In this context, we aimed here to investigate optimal control techniques in the management of tumor growth inhibition, with a particular focus on cancer chemotherapy treatment strategies. Methods: Using both linear autoregressive with exogenous inputs (ARX) and advanced non-linear tumor growth inhibition (TGI) modeling approaches, we investigated various single-agent treatment protocols, including continuous, periodic, and intermittent chemotherapy schedules. By integrating advanced mathematical modeling with optimal control theory and methods, namely the Linear Quadratic Regulator (LQR) and the “pseudo-linear” state-space equivalent representation and suboptimal control of a non-linear dynamic system known as the State-Dependent Riccati Equation (SDRE) approach, this work explores and evaluates successfully, more effective chemotherapy treatment strategies at the computer simulation level, using real preclinical data which increases the expectation to be applied in the clinical practice of oncology. Results: The integration of these methods provides insights into how different drug administration schedules may affect tumor response at the preclinical level. This work uses mathematical modeling to evaluate the efficacy of various periodic and intermittent chemotherapy treatment strategies, with a focus on optimizing drug doses while minimizing the potential side effects of chemotherapy due to the administration of less effective chemotherapeutic doses. Conclusions: The treatment scenarios tested in this study could effectively stop tumor growth or even lead to tumor regression to a negligible or near-zero size. This approach highlights the importance of computational tools for more effective treatment strategies in chemotherapy and offers a promising direction for future research and more efficient clinical applications in oncology as part of a more individualized approach.

Application of Cost Control Techniques in Construction Projects Delivery

Purpose: This research work deals on the application of cost control techniques in Construction project delivery. The need for the work arose as projects suffer from cost and time overruns due to factors stemming from poor cost control during at the design and execution stages of Construction projects. Material and Methods: This study adopted an exploratory research design using a structured questionnaire as the primary instrument for data collection. The research was conducted in Rivers State, Nigeria, known for its robust infrastructure development and relevance to the construction sector. The study population comprised public and private contractors, including civil engineers and quantity surveyors. A random sampling technique was employed to select 50 contractors, considering time and financial constraints. Findings: The analysis of the data obtained from the respondents identified cost control techniques that include schedules, budgeting, inspection, meetings, reports, records, monitoring & evaluations, as the commonly used techniques for cost control. The study also revealed that most project managers and contractors in Port Harcourt find it difficult in controlling project costs due to problems which include delays by clients to release fund as at when due, indecision, lack of materials and equipment, bad weather, overlapping of activities, unclear and incomplete drawings, making good defective works, and generally failure to control the productivity of resources. Others of paucity were due to theft and vandalism, interference by clients, high labor turnover, and insufficient knowledge on cost control techniques. Implications to Theory, Practice and Policy : The study therefore recommends proper knowledge and application of cost control techniques, adequate management of the cost control techniques, good site organization and reporting and adequate supervision of Construction projects should be adopted and implemented.