Constant Speed Control Research Articles

Research into Energy-Saving Control Strategies of a Bulldozer Driven by a Torque Converter Based on the Minimum Fuel Consumption Rate of the Whole Machine

In order to address the issue of poor fuel efficiency in hydraulic bulldozers during operation, this paper proposes a speed–load control strategy aimed at minimizing the overall fuel consumption rate of the machine. First, input–output models of the engine, hydraulic torque converter and the entire vehicle were established. Then, based on the bulldozer’s output power and fuel consumption rate, a performance metric for the overall fuel consumption rate was proposed to reflect the machine’s working efficiency. The characteristics of the overall fuel consumption rate were analyzed under different load, speed, and gear conditions. Next, a work point optimization control strategy was proposed for the whole machine energy-saving mode and constant power mode, aiming to minimize the overall fuel consumption rate while using the load, speed, and gear as control variables. To verify the feasibility of the work point optimization control strategy, simulations were conducted for both the energy-saving and constant power modes. The simulation results showed that in the whole machine energy-saving mode, this control strategy resulted in the lowest fuel consumption compared to constant speed control strategies at 1500, 1700, and 2000 rpm, with significant reductions in most cases. In the constant power mode, a comparison between four optimal operating points and the whole machine energy-saving mode revealed that while the former had slightly higher fuel consumption, it ensured a stable power output. Finally, experimental testing demonstrated that the proposed control strategy reduced the overall fuel consumption rate by 12.5% compared to the constant speed mode, verifying the effectiveness of the strategy. The study concludes that the energy-saving control strategy, through the coordinated switching between the two modes in complex operating conditions, not only ensures a stable power output for the bulldozer but also significantly improves fuel efficiency, providing an important reference for optimizing the efficiency of transmission systems in construction machines.

A multi-objective physiological control system for continuous-flow left ventricular assist device with non-invasive physiological feedback

In order to enable continuous-flow left ventricular assist device (CFLVAD) to adjust pump speed adaptively in response to changes in ventricular load, we developed a multi-objective physiological control system for CFLVAD with non-invasive physiological feedback mechanism, and proposed a multi-objective hierarchical control (MOHC) strategy to coordinate three controllers. A model-based estimation method was utilized to gain the physiological feedback variables. Suction prevention controller, regurgitation prevention controller, and physiological pulsatility controller were developed and applied to achieve the objectives: preventing left ventricular suction, preventing pump regurgitation, pump flow adaptive adjustment, and enhancing vascular pulsatility. The constraint conditions of feedback variables and controller priority were used to implement multi-objective hierarchical control. The preload and afterload were increased or decreased to simulate the scenarios of the sharp increase in left ventricular flow, the sharp decrease in left ventricular flow, and the rest-exercise-rest. The performance of MOHC was evaluated by subjecting it to three scenarios and compared with that of constant speed control (CSC) and pulsatile varying speed control (PVSC). The simulation results show that the linear correlation between the filtered and actual feedback variables was as high as 99.9%. Compared with CSC and PVSC, MOHC can avoid ventricular suction and pump regurgitation when the left ventricular flow changed rapidly. During rest or exercise, MOHC provided more adequate physiological perfusion and enhances greater vascular pulsatility than CSC and PVSC. MOHC can adjust the CFLVAD pump speed in response to changes in ventricular load.

Customized stiffness control strategy for a six-bar linkage-based gait rehabilitation robot

Abstract Lower limb rehabilitation robots based on linkage-based mechanisms have recently drawn significant attention in the field due to their numerous advantages. The control of previously proposed linkage-based gait rehabilitation robotic orthoses has been achieved using constant speed control without consideration for the interaction forces. However, such an approach can be harmful to people with stroke since the level of disability varies among individuals, and it may cause potential injuries when excessive force is applied by the robot. To overcome this limitation and improve the rehabilitation process, it is necessary to recognize the force exerted by the person during walking and adjust the robot’s assistive torque accordingly, to provide synchronized motion. Thus, in this work, a human-cooperative approach based on a stiffness control strategy for the six-bar linkage-based gait rehabilitation robot is presented. The proposed methodology can serve as a solid foundation for developing a human-cooperative approach for linkage-based lower limb rehabilitation robotic orthoses. The control was validated and tested with eight healthy human subjects. As a result, customized robotic assistance with this mechanism can be provided during training to meet the individual needs of stroke patients, which can lead to increased engagement and contribution, thus improving treatment outcomes.

Performance study of dual heart assisted control system based on SL-SMC physiological combination controller.

The main challenges of Biventricular Assist Devices (BiVAD) as a treatment modality for patients with Bicardiac heart failure heart failure are the balance of systemic blood flow during changes in physiological activity and the prevention of ventricular suction. In this study, a model of the Biventricular Circulatory System (BCS) was constructed and a physiological combination controller based on Starling-Like controller and Sliding Mode Controller (SMC) was proposed. The effects of the physiological controller on the hemodynamics of the BCS were investigated by simulating two sets of physiological state change experiments: elevated pulmonary artery resistance and resting-exercise, with constant speed (CS) control and combined Starling-like and PI control (SL-PI) as controllers. Simulation and experimental results showed that the Starling-like and Sliding Mode Control (SL-SMC) physiological combination controller was effective in preventing the occurrence of ventricular suction, providing higher cardiac output, maintain balance of systemic blood flow, and have higher response speed and robustness in the face of physiological state changes.

Dynamic performance of strategy for transitioning from conventional bottom otter trawling to semi-pelagic trawling through towing tank experiments and numerical simulations

An innovative trawling strategy for transitioning from conventional bottom trawling to semi-pelagic trawling (elevating the otter board but allowing the trawl net to contact the seabed) was developed to mitigate the effects of seabed impact, and its dynamic performance was evaluated. Experiments were carried out using a 1/18 scale physical model of the otter trawl at a speed of 0.6 m/s, and the warp length was tuned in the range of 4–8 m under constant-speed control of the trawl winch for validating the numerical simulations. Numerical simulations were then conducted to investigate the effects of towing speed and winch speed on the dynamic loads of the otter trawl system and movement of the otter board, eventually develop a fuzzy or proportion-integration-differentiation (PID) controller for the trawl system. Numerical results showed the sharp increase of the warp tension and the overshoot of the otter board at the constant-speed control occurred, and the magnitudes of both raised as the towing speed and winch speed increased. The otter board spread was significantly reduced during the transition to semi-pelagic trawling at a low towing speed. The use of fuzzy and PID control successfully eliminated the overshoot and diminished the high warp tension.

Terra-22: an aerial soil sampling in densely compacted agricultural fields

Soil sampling is used in agriculture to monitor fields and plan fertilizer application. This task is typically performed manually, but ground robots have recently been introduced. However, ground robots are often slow and heavy, which contributes to soil compaction. Fast-flying drones could provide an interesting alternative to ground robots. However, drones are severely limited in their payload and in the forces that they can apply to the soil. This paper presents the Terra-22, the first airborne system capable of sampling densely compacted agricultural soils. To do so, many challenges were addressed, including the development of (i) a high-power density drilling system that outperforms typical brushed DC gear motor by 39%, (ii) a drill design that is 48% lighter than traditional steel auger drills and that keeps cross-contamination under 4%, and (iii) a drill penetration rate controller that reduces the torque requirement by 33% and the axial force requirement by eight folds when compared to a constant penetration speed controller. Outdoor soil sampling tests in a corn field (sandy loam soil, compaction between 0.8 and 2 MPa) demonstrated a 94% success rate on flat terrain and a sampling duration under one minute.

Experimental Study on Constant Speed Control Technology of Hydraulic Drive Pavers

The paver needs superior constant speed performance when paving the pavement. In order to effectively reduce the paver speed fluctuation of the paver, and the wandering deviation from the predetermined track during the paving operation, a control scheme of paver travelling system based on GNSS, Global Navigation Satellite System, is proposed; the scheme can realize open-loop control, closed-loop control, and deviation correction control according to the driver’s choice. During closed-loop control, the setting value and the PID controller output of the left wheel are combined to control the speed of the left wheel, as is the closed-loop control of the right wheel. During the deviation correction control, the coordinate provided by the RTK GNSS receiver and the predetermined trajectory line are used to calculate the lateral deviation of the paver. The lateral deviation is input to the right wheel navigation correction PID algorithm. After the calculation, the correction value of the right wheel speed is obtained, which is input to the right wheel PID controller for the deviation correction control. In this paper, the low constant speed performance of the paver, such as during straight driving, turning driving, and driving when resistance changing, was studied by means of experiments. The test results show that when the test paver was running at a speed of more than 2 m/min, the average speed was almost the same. The higher the average speed was, the more stable the speed was. When the paver was less than 1 m/min, its speed fluctuation tended to increase, and its constant speed performance could not be guaranteed. When the test paver hit a movable obstacle at a speed of 5 m/min, which changed the driving resistance, the average speed of the left and right wheels decreased significantly, with a change of about 2.8%, and there was no significant change in the speed fluctuation of the left and right wheels. At the same time, the wandering deviation test proves that the strait-line travelling wandering deviation was basically controlled within 2.5 cm. Without driver intervention, the wandering deviation of the test paver travelling 50 m decreased by about 97.4%, and the constant speed control fluctuation was within 0.2% when the paver travelled at the speed of 5 m/min.

Grey Wolf Particle Swarm Optimized Pump–Motor Servo System Constant Speed Control Strategy

Aiming to solve the problems of poor dynamic response characteristics and the weak anti-jamming capability of the conventional proportional–integral–derivative (PID) controlled pump-motor servo system (PMSS) under the actual working environment, this study created a brand new hybrid grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithm to determine the best parameters of the PID controller for the PMSS speed control to make the PMSS achieve a constant speed control. We developed a GWOPSO-PID controller and compared it with a conventional PID controller, GWO-PID, PSO-PID, and GA-PID. In comparison to the other four control methods, the simulation and experimental results demonstrate that the designed GWOPSO-PID control had better dynamic response characteristics, with its rise times being reduced by 78.6%, 64.7%, 67.1%, and 41.5%, respectively. Additionally, the system under the GWOPSO-PID control exhibits a good stability and robustness even in the face of different load circumstances, with decreases in the re-equilibration times of 59.6%, 23.4%, 53.2%, and 41.9%, respectively, with a significantly improved immunity to disturbances.

A control technique for hybrid floating offshore wind turbines using oscillating water columns for generated power fluctuation reduction

Abstract The inherent oscillating dynamics of floating offshore wind turbines (FOWTs) might result in undesirable oscillatory behavior in both the system states and the generated power outputs, leading to unwanted effects on critical, extreme, and fatigue loads, and finally to a premature failure of the facility. Therefore, this kind of system should be capable of lessening such undesired effects. In this article, four oscillating water columns (OWC) have been installed within a FOWT barge-type platform. A novel switching control technique has been developed in order to reduce oscillations of the system created by both wind and wave, as well as the fluctuations in the generated power, by adequately regulating the airflow control valves. While the impact of the coupled wind-wave loads has been considered, a set of representative case studies have been taken into account for a range of regular waves and wind speeds. The study relies on the use of response amplitude operators (RAO) that have been pre-processed and evaluated in order to apply the switching control technique. In this sense, the starting time of the switching for below-rated, rated, and above-rated wind speeds have been calculated using the platform’s corresponding pitch RAO. Additionally, the blades’ pitch and generator torque have also been regulated by means of a constant torque variable speed controller to capture maximum energy for below-rated wind speed conditions and to match the rated generator power for rated and above-rated wind speed conditions, respectively. In order to peruse the feasibility and performance of the proposed strategy, a comparison has been carried out between the uncontrolled traditional barge-type platform and the controlled OWCs-based barge FOWT. The results demonstrate that the proposed control approach can effectively and successfully decrease both the oscillations in the system’s modes and the fluctuations in the generated power.

A Literature Review on Automation of Instrument Air Distribution System using Arduino and Integrate Industry 4.0

Abstract: This article is primarily concerned with developing a totally upgraded IA distribution controlling system, which includes the Arduino program and Industry 4.0 is further extended by employing IOT and wireless sensor interfaces, simulating the Arduino IAD plant and putting it online for remote access. Air conditioners have become an integral component of everyday life, particularly in tropical regions such as India. One of the most significant control variables in an infrastructure is considered to be an air conditioner. This project is all about controlling an air conditioner with voice commands. Here, voice commands are recognized and utilised to activate/deactivate an air conditioner using the Michel C. JARVIS application. Using voice sensors in ARDUINO, the air conditioner will be able to understand spoken instructions and regulate the compressor. Keywords: Internet of things (IoT), Industry 4.0 , Instrument air (IA)compressor, IA Distribution system, and Arduino Acronym: IAC-Instrument Air Compressor, CSC - Constant Speed Control , ASSC - Automatic Start Stop Control, IAD - Instrument Air Distribution , IA -Instrument Air

Physiologic Data-Driven Iterative Learning Control for Left Ventricular Assist Devices.

Continuous flow ventricular assist devices (cfVADs) constitute a viable and increasingly used therapy for end-stage heart failure patients. However, they are still operating at a fixed-speed mode that precludes physiological cfVAD response and it is often related to adverse events of cfVAD therapy. To ameliorate this, various physiological controllers have been proposed, however, the majority of these controllers do not account for the lack of pulsatility in the cfVAD operation, which is supposed to be beneficial for the physiological function of the cardiovascular system. In this study, we present a physiological data-driven iterative learning controller (PDD-ILC) that accurately tracks predefined pump flow trajectories, aiming to achieve physiological, pulsatile, and treatment-driven response of cfVADs. The controller has been extensively tested in an in-silico environment under various physiological conditions, and compared with a physiologic pump flow proportional-integral-derivative controller (PF-PIDC) developed in this study as well as the constant speed (CS) control that is the current state of the art in clinical practice. Additionally, two treatment objectives were investigated to achieve pulsatility maximization and left ventricular stroke work (LVSW) minimization by implementing copulsation and counterpulsation pump modes, respectively. Under all experimental conditions, the PDD-ILC as well as the PF-PIDC demonstrated highly accurate tracking of the reference pump flow trajectories, outperforming existing model-based iterative learning control approaches. Additionally, the developed controllers achieved the predefined treatment objectives and resulted in improved hemodynamics and preload sensitivities compared to the CS support.

A Mathematical Model of Artificial Pulse Synchronization for the HeartMate3 Left Ventricular Assist Device.

Constant speed control of rotary LVADs attenuates vascular pulsatility, which has been linked to clinical complications such as thrombus formation, bleeding, and valvular dysfunction. Speed modulation can improve pulsatility and washout, but optimization requires coordination with the native heartbeat. A simple mathematical model of the left ventricle-left ventricular assist device (LV-LVAD) flow interaction was developed that sums the individual contributions of the native LV and the HeartMate3 artificial pulse (AP) to predict the total systemic flow. The model flow and pulsatility predictions results were in good agreement with experimental data from a mock circulatory loop measured for full bypass support conditions. The model was used to evaluate three schemes for optimizing the synchronization of the AP with the native heart. The optimized interaction occurred when the AP speed increase occurred during contraction, resulting in a doubling of flow pulsatility, and corresponded to an increase in the area enclosed by the dynamic pressure-flow relation. The model provides a simple tool for exploring the optimization of LVAD speed modulation that can reduce the time and expense of mock loop studies during the development process.

Constant Speed Control of Hydraulic Travel System Based on Neural Network Algorithm

In order to solve the problems of poor stability of the output speed and poor synchronization of the pump-controlled dual motor in a hydraulic travel system during step input speed and external load disturbance, different control strategies were designed and compared with the state machine using the statechart module control, Z-N frequency response PID control, and GA-based PID parameter self-tuning methods. Our analysis shows that the BP algorithm-based PID parameter self-tuning control method has no overshoot and that the three methods reduced the target speed tracking time by 90.11%, 75.12% and 36.55%, respectively. The average synchronous error for the system output speed was 7.95%. The stability and synchronization requirements of the constant speed of the hydraulic travel system were satisfied. These research results can provide a reference for the design and application of constant speed control for pump-controlled dual-motor hydraulic travel systems in the fields of engineering and agricultural machinery.

Control and realization of intelligent fishing system based on PLC and fuzzy PID algorithm

In this paper, based on the frequency conversion constant speed control principle theory, to control the stability of the number of fish pipe to fish for the technical means, to control the number of fish to ensure catch efficiency and damage rate as the main purpose, research and design based on the fuzzy PID controller of intelligent pump suction fishing control system, determine the system platform, sucking fish overall frame structure of the control system is given, A complete electrical control system is designed. The purpose of this paper is to obtain a fully functional fish suction equipment control system, specifically realize the intelligent catch count, control fish suction switch, lossless fish transfer speed control system switch and automatic cycle control.

Optimal Power Control for a Variable-Speed Generator Integrated in Series Hybrid Vehicle

In series hybrid electric vehicles, the fossil energy source is composed of an electrical generator driven by an internal combustion engine. Compared to constant speed control, variable speed control of the electrical generator improves the vehicle’s energetic efficiency and releases the battery load. Such control is extremely sensitive because of the nonlinearities. In a plug-in hybrid vehicle, in addition to the obvious inherent variable speed nonlinearity, the large range of battery voltage variation increases the complexity of the controller design. Moreover, in our case, to take advantage of the variable speed feature, the generator load has transient constraints because it must follow the vehicle load. In equivalent applications, for the electrical side, usually, there is a use of high-frequency control strategies based on the generator’s three phases current and voltage acquirement. This article investigates a low-frequency power control strategy through a model-based method for a specific power electronics vehicle architecture. Starting with an adaptive proportional, integrator, and derivative (PID)-based controller to tackle the nonlinearity issues, this article explains progressively the reasons and choices that lead to design a sliding hybrid fuzzy logic controller. The designed controller demonstrates good performance in power tracking and permits to reduce fuel consumption.

A novel multistage constant compressor speed control strategy of electric vehicle air conditioning system based on genetic algorithm

This study establishes a passenger cabin-coupled air conditioning model that the heat exchangers adopted in the air conditioning model, are calibrated by testing, during which the parameters for establishing the passenger cabin model are measured. The cabin temperature simulation results of the air conditioning model proposed in this paper fit well with the test results, with a maximum difference of 3 °C. A genetic algorithm (GA) optimization-based multistage constant-compressor speed (MCCS) air conditioning system control strategy is proposed. This control strategy sets the cabin temperature as the input control factor and the compressor speed as the output factor, and different cabin temperature ranges correspond to the MCCSs, which are optimized by the GA. The presented strategy is contrasted with the most commonly used on/off controllers and the proportional integral derivative (PID) controller, and an engineering-applied (EA) air conditioning control strategy. The proposed controller can maintain passenger cabin thermal comfort and save energy simultaneously, and it can be easily applied in engineering. Based on the simulation results, the MCCS controller can save 17.5, 7.5, and 5.8% more energy consumption than the on/off, PID, and EA controllers. Moreover, it can improve the coefficient of performance of the air conditioning system by 5.3 and 3.9% more than the PID and EA controllers. Therefore, the proposed MCCS controller can increase the operation efficiency of electric vehicles AC system.

A Flow Sensor-Based Suction-Index Control Strategy for Rotary Left Ventricular Assist Devices.

Rotary left ventricular assist devices (LVAD) have emerged as a long-term treatment option for patients with advanced heart failure. LVADs need to maintain sufficient physiological perfusion while avoiding left ventricular myocardial damage due to suction at the LVAD inlet. To achieve these objectives, a control algorithm that utilizes a calculated suction index from measured pump flow (SIMPF) is proposed. This algorithm maintained a reference, user-defined SIMPF value, and was evaluated using an in silico model of the human circulatory system coupled to an axial or mixed flow LVAD with 5–10% uniformly distributed measurement noise added to flow sensors. Efficacy of the SIMPF algorithm was compared to a constant pump speed control strategy currently used clinically, and control algorithms proposed in the literature including differential pump speed control, left ventricular end-diastolic pressure control, mean aortic pressure control, and differential pressure control during (1) rest and exercise states; (2) rapid, eight-fold augmentation of pulmonary vascular resistance for (1); and (3) rapid change in physiologic states between rest and exercise. Maintaining SIMPF simultaneously provided sufficient physiological perfusion and avoided ventricular suction. Performance of the SIMPF algorithm was superior to the compared control strategies for both types of LVAD, demonstrating pump independence of the SIMPF algorithm.

Research on Load Disturbance Based Variable Speed PID Control and a Novel Denoising Method Based Effect Evaluation of HST for Agricultural Machinery

This paper aims to realize and improve the constant speed control performance of tractors with HST (Hydrostatic Transmission) variable speed units. To achieve this, based on the HST test bench of the tractor, we perform a verification test of the adjustable speed characteristics, a denoising filter test of the response signal, a test on the influence of the load disturbance on the adjustable speed characteristics and a PID-based constant speed performance detection test. The results of the verification test of the adjustable speed characteristics show that the theoretical value and actual value of the adjustable speed transmission characteristics of the HST used are essentially consistent with each other. The results of the test of the load disturbance’s influence on the adjustable speed characteristics show that the increase in load torque inhibits the HST output response. Therefore, the paper proposes and designs a PID-based closed-loop constant speed control system. The paper uses a step response test and a load disturbance test to research the control result of the constant speed system. Collecting and analyzing all test results, we find that the constant speed control based on PID has a very good result. The average error between the average HST output speed and the target speed set was 0.37%, and the average standard deviation of output speed was 1.18 rpm. In addition, the paper proposes a denoising method combing the empirical mode decomposition method and the Gaussian distribution determination. The method shows that the first two orders of the components of the HST response signal should be removed as noise. The paper uses the denoised signal and the partial least squares method to analyze the influencing factors of the constant speed control result. The analysis results show that the rate of change of load torque has the biggest influence on the stability of HST output speed, followed by the target value.

Control strategy to enhance pulmonary vascular pulsatility for implantable cavopulmonary assist devices: A simulation study

ObjectiveFontan failure can be potentially addressed with an implantable pump in the cavopulmonary junction (cavopulmonary assist device, CPAD) to replace the missing subpulmonary power source. Fontan pulmonary circulation lacks pulsatility due to the absence of the right ventricle, which has adverse physiological consequences. CPAD can augment pulmonary flow and improve Fontan hemodynamics. However, CPAD operating at a constant pump speed does not provide pulmonary arterial pulsatility, provide physiologic flow to match cardiac demand, or avoid suction. To overcome these limitations, a sensorless control strategy for CPAD is proposed. MethodsCPAD pump speed measurement, an intrinsic pump parameter, was used to estimate cavopulmonary pressure head (CPPH). A gain scheduled proportional-integral controller alternates CPPH between high/low setpoints (CPPHHr/CPPHLr) that generates pulsatility, while simultaneously adapting to cardiac demand and avoiding suction. Computer simulations were performed to quantify the overall performance of the proposed algorithm at rest and exercise, rapid transition from exercise to rest, and doubling of the vena caval resistance. The performance was compared against CPPH measured using pressure sensors, and a constant pump speed control strategy. ResultsThe sensorless algorithm generated a pulmonary vascular pulsatility of approximately 10 mmHg, and matched the cardiac demand at rest and exercise. The frequency of pump speed modulation was 10–15 cycles per minute and no suction was observed. Conclusion and significanceThe sensorless strategy outperformed constant CPAD speed control algorithm for improvement of pulmonary vascular pulsatility and physiologic perfusion. Further validation is needed using mock loop and animal tests.

Induction Motor Drive Using Fractional-Order Proportional Integral Derivative (FOPID) Controller Based on Nelder-Mead and Grey Wolf Optimizers. (Dept. E)

Induction motors are widely used in industrial applications due to their advantages over dc motors in terms of low cost, low maintenance, high performance, and high power density. This article aims to achieve constant speed control of the induction motor (IM) and improves the motor performance using a Fractional-order PID controller (FOPID). The FOPID controller contains five important variables coefficients. They are named as follows: - proportional operator (Kp), integral operator (Ki) derivative operator (Kd), integral of fractional-order (λ) and the derivative of fractional-order μ. The performance of any controller depends mainly on the chosen values of the aforementioned operators (Kp, Ki, Kd, λ, μ) so one of the main objectives of this paper how to optimize the values of these five parameters to improve the system performance. Actually there are many methods to achieve the optimization problem but a two selected optimizers (Grey Wolf Optimizer, and Nelder-Mead) are chosen in this paper due their nature which make them more suitable for the presented problem. Three cases study of the induction motor integrated with the proposed controllers are simulated based on Matlab SIMULINK and the obtained results are discussed in details. The obtained results in all the cases ensured that the proposed FOPID controller introduced always the better performances indices which make it favorably recommended instead of other conventional controllers