Step Response Experiments Research Articles

Multi-bandwidth observer-based adaptive robust pressure control for electro-hydraulic brake system with uncertainties and measurement noise

Accurate pressure regulation of electro-hydraulic brake system (EHB) is essential for enhancing braking performance in automobiles. However, component wear and pressure measurement noise can cause model parameters and controlled states to drift, resulting in system chattering. This nonlinear and uncertain state can significantly degrade pressure control performance. Motivated by this, the article presents a controlled state reconstruction-based adaptive robust pressure control technique with noise suppression. Firstly, a reduced dynamics model is established for controller design, which effectively captures the fundamental characteristic of the EHB. Secondly, a multi-bandwidth extended state observer (MBESO) capable of noise suppression is designed to reconstruct controlled states, including unknown disturbances and unmeasured pressure change rates of the EHB. Thirdly, an MBESO-based adaptive robust pressure control technique is introduced, where the control gain and robust factor are updated based on control and observation errors. In addition, the overall performance of the proposed control strategy is analyzed in the frequency domain, and close-loop stability is demonstrated via the Lyapunov method. Finally, the pressure control precision and robustness of the proposed algorithm are validated in both dynamic and static scenarios through sinusoidal and step-response experiments on a hardware-in-loop test bench. The results indicate that the proposed algorithm reduces dynamic pressure-tracking error by up to 62% compared to traditional method under sinusoidal conditions, with steady-state error remaining within 1 bar under step-response conditions.

Fractional-Order Modeling and Identification for an SCR Denitrification Process

This paper presents an application of a fractional-order system on modeling an industrial process system with large inertia and time delay. The traditional integer-order model of the process system is extended to a fractional-order one in this work. To identify the parameters of the proposed fractional-order model, an output-error identification algorithm is presented. Based on the experimental step response data of the selective catalytic reduction (SCR) denitrification process in a power plant, this proposed fractional-order model shows a better fitting result compared with the typical integer-order models. An integer-order proportional–integral (PI) controller is designed for the process plant using a simple scheme according to the identified fractional-order and integer-order models, respectively. Validation tests are performed based on the obtained fractional-order and integer-order models, demonstrating the advantages of the proposed fractional-order model with the corresponding system identification approach for industrial processes with large inertia and time delay.

Pressurized Water reactor power level control: A nonlinear generalized predictive control with extended Kalman filter method

Reactor power level control is an effective way to achieve load tracking of Pressurized Water Reactor (PWR) in a nuclear power station. A novel Nonlinear Generalized Predictive Control with Extended Kalman Filter (NGPC + EKF) is proposed to solve the problem that discrete predictive model mismatch in noisy environment. In this paper, an NGPC controller is developed to realize the reactor load tracking, and an EKF is used to estimate reactor states and suppress noise. Finally, the control methods of PID, MPC, NGPC and NGPC + EKF are compared by two simulation experiments, load tracking experiment and step response experiment. The load tracking experiment results show that NGPC + EKF method obtains better noise suppression ability and tracking effect. In the step response experiment, the proposed NGPC + EKF scheme is also proved to have better step response performance than others.

Adaptive laboratory evolution in a novel parallel shaken pH-auxostat.

Adaptive laboratory evolution (ALE) is a widely used microbial strain development and optimization method. ALE experiments, to select for faster-growing strains, are commonly performed as serial batch cultivations in shake flasks, serum bottles, or microtiter plates or as continuous cultivations in bioreactors on a laboratory scale. To combine the advantages of higher throughput in parallel shaken cultures with continuous fermentations for conducting ALE experiments, a new Continuous parallel shaken pH-auxostat (CPA) was developed. The CPA consists of six autonomous parallel shaken cylindrical reactors, equipped with real-time pH control of the culture medium. The noninvasive pH measurement and control are realized by biocompatible pH sensor spots and a programmable pump module, to adjust the dilution rate of fresh medium for each reactor separately. Two different strains of the methylotrophic yeast Ogataea polymorpha were used as microbial model systems for parallel chemostat and pH-auxostat cultivations. During cultivation, the medium is acidified by the microbial activity of the yeast. For pH-auxostat cultivations, the growth-dependent acidification triggers the addition of fresh feed medium into the reactors, leading to a pH increase and thereby to the control of the pH to a predetermined set value. By controlling the pH to a predetermined set value, the dilution rate of the continuous cultivation is adjusted to values close to the washout point, in the range of the maximum specific growth rate of the yeast. The pH control was optimized by conducting a step-response experiment and obtaining tuned PI controller parameters by the Chien-Hrones-Reswick (CHR) PID tuning method. Two pH-auxostat cultivations were performed with two different O. polymorpha strains at high dilution rates for up to 18 days. As a result, up to 4.8-fold faster-growing strains were selected. The increased specific maximum growth rates of the selected strains were confirmed in subsequent batch cultivations.

Determination of effective liquid-phase diffusion coefficients by tracer method in continuous packed columns

Many industrially relevant chemical processes are affected by the liquid-phase diffusion resistance in porous materials, for example in heterogeneous catalysts. Therefore, reliable experimental methods for the determination of effective diffusion coefficients in porous structures are highly desirable. In this work, a method was developed to study the internal diffusion effects in porous media by step response experiments with tracers injected to fixed beds filled with porous particles and inert material. The tracer responses were recorded at the outlet of the bed by UV–vis spectrometry. Ethanol was used as the tracer and water as the solvent. Porous aluminum oxide particles were selected as the model material. The step responses were described with a dynamic axial dispersion model, i.e. partial differential equations for the inert and catalyst sections of the bed. The partial differential equations describing the model were discretized with finite differences and the resulting ordinary differential equations were solved numerically with a solver for stiff ordinary differential equations. From the experimental data, the dispersion coefficients of the bed and the effective diffusion coefficient in the porous aluminum oxide particles were successfully determined by non-linear regression analysis. The values of the effective diffusion coefficents had a good agreement with the liquid-phase diffusion coefficients estimated from correlations. The method is applicable for any porous material.

Active Vibration Damping Using Rotor Torque Control in Electric Aircraft

Vibration damping in aerospace structures can decrease the likelihood of failures and instabilities and improve passenger comfort. This paper introduces the novel idea of damping vibration using the electric proprotors on aircraft without compromising flight control. The equations of motion of a cantilevered beam with a propeller at the tip driven by an electric motor are obtained using Hamilton’s principle, solved analytically in the frequency domain, and approximately in the time domain. Feeding back the beam tip angular rate to the motor torque is shown to asymptotically stabilize all transverse beam vibration modes. The overall vibration control consists of the inner rate feedback damping loop with an outer rotor speed control loop. Experimental frequency response and step response validate the models and show that the closed-loop damping in the first mode is three times higher than open loop with less than 1% rotor speed change for a 3% initial tip displacement. Theoretical results give good agreement with experiments. Parametric studies based on a 12 kg quadcopter indicate that if the rotor inertia is sufficiently large the proposed control can provide 8% damping with minimal impact on rotor speed.

Development and Validation of an Automatic Waypoint Navigation Control System for Watercrafts

This paper presents the development and testing of an automatic control system for waypoint navigation in a solar boat, initially designed for manual operation. It covers the boat's modifications for automation, system identification through step response experiments, and control strategy implementation. The system includes a Base Controller for yaw rate and speed as well as a subsequent Waypoint Path Controller for navigation. Utilizing a nominal dynamic model of the boat, the Base Controller's design emphasizes robustness against parameter uncertainties, while the Waypoint Path Controller follows a conventional approach. The effectiveness of the system is validated with real driving tests.

Exploration of the NO-char reaction pathway by in-situ DRIFTS and isotope gas tracing techniques

For NO abatement by carbon-based material (for example, char), many studies have been performed on the reactions between carbon and NO. Oxygen is believed to play a key role during the denitrification process: not only positive, but also negative. Some specific intermediates are worth investigating, and reaction routes are needed to be clarified in order to reveal and explain the mechanism of the concerned reactions. To account for the reaction scheme, chemical evolution information of both solid surface side and gaseous side are collected and analyzed by means of in-situ DRIFTS analysis and isotopic gas tracing, respectively. In combination with experimental results of the NO-char reaction in a fixed bed, possible reaction pathway is proposed. The in-situ DRIFTS analysis shows that C(N) and thermodynamically active C = O complexes are produced during NO adsorption on coal char. The presence of O2 promotes the chemisorption of NO molecules. Oxygen combines with carbon to generate not only thermodynamically stable C-O complexes but active C = O complexes. Step response experiments using isotope gas tracing technique demonstrate that CO and CO2 are produced by C = O desorption and the combination between C-O and C = O complexes, respectively. N2 is generated by the reaction of C(N) complexes on the coal char surface with NO molecules in gas phase. The stable C-O complexes promote NO adsorption and dissociation by reaction with C = O complexes and subsequently producing new active sites.

Dynamic Characterization of Optical Coherence-Based Displacement-Type Weight Sensor

Dynamic characteristics play a crucial role in evaluating the performance of weight sensors and are essential for achieving fast and accurate weight measurements. This study focuses on a weight sensor based on optical coherence displacement. Using finite element analysis, the sensor was numerically simulated. Frequency domain and time domain dynamic response characteristics were explored through harmonic response analysis and transient dynamic analysis. The superior dynamic performance and reduced conditioning time of the non-contact optical coherence-based displacement weight sensor were confirmed via a negative step response experiment that compared the proposed sensing method to strain sensing. Moreover, dynamic performance metrics for the optical coherence displacement-type weight sensor were determined. Ultimately, the sensor’s dynamic performance was enhanced using the pole-zero placement method, decreasing the overshoot to 4.72% and reducing the response time to 0.0132 s. These enhancements broaden the sensor’s operational bandwidth and amplify its dynamic response capabilities.

Humanoid Walking Control Using LQR and ANFIS

Humanoid robots possess remarkable mobility and adaptability for diverse environments. Nonetheless, accurate walking pattern tracking remains challenging, especially when employing the linear quadratic regulator (LQR) due to delays in high-mobility setpoint tracking. We propose a novel control approach to address this limitation by integrating an artificial neuro-fuzzy inference system (ANFIS) with the LQR to enhance pattern tracking. The research contributes to developing a control system that combines LQR and ANFIS to enable humanoid robots to follow various walking patterns with increased precision and efficiency and also the scheme to incorporate LQR and ANFIS. The study involves four experiments: step response, walking phase, static straight walking, and varied straight walking. Each test runs for 5 seconds with a 100-millisecond sampling rate, repeated five times, and employs the Integral Absolute Value (IAE) metric for evaluation. The LQR-ANFIS method exhibits superior performance, achieving a maximum overshoot of 0%, a rise time of 0.3 seconds, a settling time of 0.3 seconds, and a steady-state error of 0% in the step response experiment. The proposed control system also enables stable walking with step periods ranging from 0.15 to 4 seconds and step ranges of 0.05 to 0.03 meters. In conclusion, the integration of ANFIS with the LQR significantly enhances the mobility of humanoid robots, enabling them to navigate diverse environments and accurately track various walking patterns proficiently.

Direct Tilt Controller Design with Disturbance Compensation and Implementation for a Narrow Tilting Electric Vehicle

Three-wheeled electric city vehicles are becoming popular because they have lower cost and enable motorcycle driving feeling with electric powertrain performance. These vehicles need a driver assistant system, also known as an active tilting stability controller, to provide a safe cornering manoeuvre. Active tilt control methods are direct tilt control (DTC), steering tilt control (STC) and a combination of these methods. In this study, DTC system design with a servo motor actuator with simulation and experimental results are presented. State feedback control with pole placement design has been improved with disturbance compensation control. This novel controller structure enhances the response of DTC and enables a faster-tilting response. Simulation results are given up to 10 m/s speed. Experimental results of the developed method are given up to 3.05 m/s (11 km/h) speed on a three-wheeled electric vehicle. The speed control loop of the servo motor drive unit (SMDU) stabilizes the DTC system. In the state of the art, a proportional derivative controller is commonly used as a tilt controller. By including the speed control loop of SMDU in the tilt control system, the use of the derivative term can be eliminated. The stability effect of the speed control loop is shown by MATLAB analysis, simulations in Simulink and experimental step response test as well.

KENDALI TORKA PREDIKTIF DENGAN PREDIKSI DUA LANGKAH MOTOR INDUKSI YANG DICATU OLEH SEBUAH INVERTER TIGA FASE

The predictive torque control (PTC) technique of electric motor drive is based on the principle that the determined optimum voltage vector will be applied to the motor in the next cycle. If a three-phase inverter is used, this inverter can only realize eight different switching states. One of the eight switching states is used as the optimum inverter switching state for the next cycle. PTC with one-step prediction cannot obtain an experimental motor speed control, because in the real-time implementation, there is a single sampling delay between input and optimal actuation due to a large number of real time calculations. The delay time problem could be solved by modifying the optimization steps by using the two-step prediction of PTC model. The experimental results show that the motor can follow the reference speed and command torque in the step response and variable speed experiments. In variable speed experiment, good speed and torque dynamics can be achieved by selecting the proportional gain value that corresponds to the motor speed

Exploiting a Simple Asymmetric Pleating Method to Realize a Textile Based Bending Actuator

This work presents the design, modeling and control of an asymmetrically pleated textile actuator (APTA). The presented actuator utilizes a simple inflatable beam which is constrained asymmetrically using a pleat that is fixed only to a single side. Due to the difference in length between the constrained side and the unconstrained side, a bend at the pleat is generated upon inflation. This method utilizes sewing and/or heat sealing to create bending, making it easy to manufacture compared to many soft actuators and further allows for the creation of complex 3D structures in conjunction with methods presented in literature due to the in-plane bending generated by the presented pleating method. The design, fabrication and modeling of the APTA are presented and the actuator characterization in the form of bending angle, quasi-static torque and hysteresis tests are performed. A maximum normalized output torque of 400 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{Nm/kPa.m}^{3}$</tex-math></inline-formula> was demonstrated by the presented APTA. An empirical model for the APTA using the collected data was derived to predict torque output throughout the actuator range of motion. A controller using the empirical model was designed to track desired torque profiles. Single and Multiple step response experiments were conducted to evaluate the efficacy of the controller for burst-like actuation which could have implications in physical assistance for biological systems and in shape forming deployable structures. Further, we present several potential applications to this actuator in the form of 3D inflatable structures, a continuum module segment, and a wearable elbow device.

A Novel Toolbox for Automatic Design of Fractional Order PI Controllers Based on Automatic System Identification from Step Response Data

This paper describes a novel automatic control toolbox, designed for non-experienced practitioners. Fractional order (FO) controllers are easily tuned with the main purpose of easy practical implementation. Experimental step data are required for the automatic FO controller tuning. An embedded system identification algorithm uses the step data to obtain a process model as a second order plus dead-time (SOPDT) system. Finally, the FO controller is computed based on the previously estimated SOPDT model in order to fulfil a set of user-imposed frequency domain performance specifications: phase margin, gain crossover frequency and gain margin maximization. Experimental step response data from a strongly nonlinear vertical take-off and landing unit have been used to design an FO controller using the toolbox. The experimental closed loop results validate the proposed toolbox. The end result is a user-friendly automatic fractional order controller tuning with endless possibilities of real-world applicability.

Lockable Lower-Limb Exoskeleton Based on a Novel Variable-Stiffness Joint: Reducing Physical Fatigue at Squatting

Abstract Some special tasks require human operations and cannot be performed by robots or other autonomous equipment, such as special industrial assembly and surgical procedures in small and crowded spaces. Workers/surgeons in these cases tend to have physical fatigue. In this study, a novel variable-stiffness joint based on positive pressure was proposed, and a torque model was established. The locking torque variation, step response, and energy consumption were evaluated in comparison with a torque motor. A lockable lower-limb exoskeleton based on the variable-stiffness joint was developed, and wearable tests were conducted to evaluate a voice recognition interface and supporting performance. The locking torque of the variable-stiffness joint could be continuously varied from 0 Nm to 26 Nm with the air pressure ranging from 1.6 bar to 5.5 bar. The settling time was 0.328 s in the step response experiment. With a load of 6 Nm, the variable-stiffness joint can realize an energy consumption reduction of 75.01% compared with using a torque motor. Moreover, the lockable lower-limb exoskeleton can realize a 35–60% reduction in the average muscle activation in each subject (aged 22–57) to maintain squatting postures at three different knee angles (paired t-test, P &amp;lt; 0.01). The proposed exoskeleton system has good mobility, low energy consumption, and easy-to-control features, showing great potential in supporting the weight of workers/surgeons during long-term operations.

Dynamic prediction of in-situ SO2 emission and operation optimization of combined desulfurization system of 300 MW CFB boiler

As the emission regulation becomes more stringent, in-situ desulfurization and wet flue gas desulfurization have been widely used for circulating fluidized bed (CFB) boilers. However, few studies focus on real-time operation optimization of combined desulfurization system (CDS) in wide-load range based on in-situ SO2 emission prediction. In this work, according to mechanism analysis, a dynamic prediction model of in-situ SO2 emission was developed. Then, closed-loop and step response experiments were conducted to validate the established model, combined with measured data from a 300 MW CFB boiler. Validation results show that the model has satisfactory prediction accuracy in different load conditions and it can capture special dynamic characteristics of in-situ SO2 desulfurization. More importantly, the model can be feasible for building an economical operation strategy of CDS. Thus, a novel control strategy based on dynamic prediction model was designed, which contributes to decrease the SO2 emission fluctuation and operation costs by correcting the limestone-feed rate in advance. The proposed control strategy was applied to actual operation of the 300 MW CFB boiler. In the long-term operation of CDS after optimization, it was easier to reach ultra-low SO2 emission standard and limestone consumption reduces 15.14% compared with before the operation optimization.

Research of permanent magnetic levitation system: Analysis, control strategy design, and experiment

Aiming to realize levitation for a novel permanent magnetic levitation system, this paper proposes a double control strategy. The coupled dynamic model with two subsystems was established at first. According to the analysis of stable levitation, four joint control strategies of air gap length and rotation angle were designed. Then, the controller parameters tuning was implemented utilizing the improved PSO (particle swarm optimization) algorithm with non-linear inertia weight. At last, step response simulations and experiments were carried out to compare the performance of the proposed four control strategies. Results demonstrate the validity of PSO using for tuning proportional-integral-derivative (PID) parameters. In addition, the parallel double PD controller and cascade double PD controller both have better dynamic performance but more significant steady-state error. When using PID control for the air gap, the error could be eliminated. Compared with the parallel PID-PD control strategy, the cascade control is competitive in terms of 0.03 s rising time, 4.3 s settling time, and 24% peak overshoot.

Renewable energy powered membrane technology: Impact of osmotic backwash on organic fouling during solar irradiance fluctuation

Organic fouling is a major issue of nanofiltration/reverse osmosis (NF/RO) membranes because it causes severe and usually irreversible flux decline. Consequently, NF/RO requires frequent chemical cleaning and/or replacement. In directly coupled photovoltaic (PV) powered NF/RO systems for brackish water desalination, solar energy fluctuations can induce a spontaneous osmotic backwash (OB) process, which may mitigate organic fouling. In this study, the feasibility of spontaneous OB as a self-cleaning method for organic fouling (humic acid with calcium) control under fluctuating conditions was evaluated with an online total organic carbon (TOC) analyser. The OB cleaning mechanisms with different solar energy fluctuating conditions, relevant feedwater chemistry (salinity, pH, and hardness) and membrane type (NF270 and BW30) were investigated. The visualisation of fouling layers by a helium ion microscope (HIM), a cryo scanning electron microscope equipped with a focused ion beam (FIB-SEM) and energy dispersive X-Ray spectroscopy (EDS) showed that partial foulants were removed by spontaneous OB, and the remaining layer was not uniform. Periodic solar irradiance step-response experiments’ results showed that spontaneous OB cleaning restored 46%–98% flux, depending on solar irradiance fluctuating conditions, feedwater chemistry, and membrane type. Specifically, low-level solar irradiance (i.e., more cloud coverage) and short operating time (i.e., high cleaning frequency) showed high OB cleaning efficiency. High salinity was found to enhance the OB performance but it was still ineffective for the enhanced organic fouling layer. Extremely pH (e.g. pH 2 or pH 12) weakened OB efficiency via a compact fouling layer/mixed fouling layer structures (calcite participation) in presence of calcium. Although spontaneous OB cleaning is promising to mitigate organic fouling, it is ineffective for severe organic fouling (e.g. 12.5 mM humic acid with 2.5 mM CaCl2). This work provides the contribution of process and water quality variables that make spontaneous OB effective for fouling control, which facilitates the further development and application of the OB technique in decentralised PV-NF/RO systems.

A novel fuzzy logic scheme for PID controller auto-tuning

This paper presents a novel method for PID (proportional–integral–derivative) controller auto-tuning based on expert knowledge incorporated into a fuzzy logic inference system. The proposed scheme iteratively tries to improve the performance of the closed-loop system. As performance measures, the proposed scheme uses the characteristics of the step response (rise time, overshoot, and settling time). PID parameters in the first iteration can be calculated based on the basic open-loop step response experiment or it is possible to use current parameters. In each successive iteration, step response characteristics are measured and the relative changes expressed in the percentage of value in the first iteration are calculated and converted into linguistic values. The fuzzy expert system computes fuzzy values that are used after defuzzification as multiplying factors for current PID parameters. To achieve a balance between the aggressive and robust closed-loop response, as well as between the slower and the faster one, the fuzzy expert system works in three operating modes: the one for speeding up the system, the one for reducing the overshoot, and the one for a balanced reduction of rise time and overshoot. The performance and robustness are verified by computer simulation using an extensive range of different processes.

A Real-Time Realization Method for the Pneumatic Positioning System of the Industrial Automated Production Line Using Low-Cost On–Off Valves

In the industrial automated production line, how to use the existing low-cost pneumatic equipment to obtain the best positioning effect has become a significant engineering problem. In this paper, a differential switching method is proposed in a pneumatic servo system consisting of four low-cost on–off valves for more precise control and lower prices. All valves are simultaneously open at the initial stage of each control period, and the differential closing time of the desired valves is calculated through the theoretical models. A sliding mode controller is applied with the proposed method, and the system stability is proven. The real-time control setup including three software layers is proposed to implement the algorithm. Several experiments are performed on a real-time embedded controller. Average 0.83% overshoot and 0.18 mm steady-state error are observed in the step response experiment. The highest frequency of sine wave that can be tracked is 1 Hz, and the average error is 1.68 mm. The maximum steady-state error is about 0.5 mm in the step response under payloads of 5.25 kg. All the simulation and experimental results prove the effectiveness of the control method.