Search Results (42)

Active disturbance rejection control (ADRC) emerges as a promising control approach due to its partial model-based characteristics and strong disturbance rejection capabilities. Nevertheless, it is a difficult problem to tune various parameters of ADRC in practical applications. To address the challenge of parameter tuning, this work develops a parameter self-tuning rule based on spatial–temporal scale transformations to simplify the tuning process and enhance its control performance. In particular, based on the transformations of spatial–temporal scale, the parameter tuning relationships for ADRC’s components, including tracking differentiator (TD), extended state observer (ESO) and feedback controller, are provided for a second-order nonlinear system. Numerical simulations show that the proposed method can conveniently and effectively provide a set of well-tuned parameters for ADRC to boost the efficiency of control. Finally, the proposed parameter tuning rule is applied to the intake pressure control of the flight test chamber system, further validating its effectiveness. The results demonstrate that the ADRC with the proposed parameter self-tuning method significantly improves the precision of the intake pressure under different operating conditions, thereby ensuring the reliability of aeroengine flight tests. Full article

The temperature control of uncooled heating processes presents challenges due to a substantial lag and the absence of active cooling mechanisms, which can lead to overshoot and oscillations. To address these issues, we propose an anti-disturbance identification method based on a tracking differentiator (TD) and an input-constrained temperature predictive control (ICTPC) strategy. Our approach specifically considers the impact of unknown disturbances on model identification within a second-order heating process. By employing a TD to differentiate the input and output signals, we effectively minimize the identification error caused by low-frequency disturbances, yielding a robust anti-disturbance identification technique. Following this, we establish input constraints to limit the amplitude and variation of the control input, ensuring a more controlled and predictable system response. Using the identified model, an ICTPC algorithm is designed to achieve stable temperature control in uncooled heating processes. Experimental results from a typical uncooled heating system demonstrate that our method not only significantly reduces overshoot but also effectively mitigates temperature fluctuations, leading to enhanced control performance and system stability. This study provides a practical solution for temperature control in systems without cooling capabilities, offering substantial improvements in the efficiency and quality of industrial production processes. Full article

Different dimensions of visual attention to social (human faces) and non-social stimuli (objects) were assessed in 19 preschool children with Autism Spectrum Disorder (ASD) and 19 typically developing (TD) age, gender, and IQ-matched controls through an original paired preference eye-tracking paradigm. The present study found a significantly reduced attentional bias toward human faces in children with ASD compared to TD controls. The analysis of the total fixation time showed a significantly reduced preference for faces in children with ASD compared to TD children. Moreover, while TD children showed a significant preference for the face over the object, children in the ASD group observed the two paired pictures for a similar amount of time, thus showing no preference. Besides, children with ASD paid significantly more sustained attention to the objects than TD children. Children in the TD group paid greater sustained attention to the faces over the objects, while children in the ASD group did not differentiate between objects and faces. Finally, an age effect was found in ASD, as younger children in the group tended to prefer objects and to show more sustained attention towards them. Overall, these findings add to the literature on anomalies in attention toward social and non-social stimuli in young children with ASD compared to their TD counterparts. These results are discussed in the light of previous studies and suggest possible directions for future research. Full article

To address the performance degradation of the conventional linear frequency modulation signal ranging method in the presence of impulse noise, this paper proposes a novel technique that integrates a sliding-window tracking differentiator (TD) with the fractional Fourier transform (FrFT) ranging method. First, the sliding-window TD filtering algorithm is used to suppress the noise in the echo. Subsequently, the filtered signal is subjected to FrFT to calculate the time delay based on the difference in the peak point positions in the fractional domain for realizing target ranging. The simulation results show that the proposed method can effectively suppress impulse noise of different intensities and achieve an accurate and robust ranging of the target. Full article

In order to improve the performance of the active vibration isolation system (AVIS) with electromagnetic actuator, several problems of vibration control are studied. Position control is a critical component in suspension systems, and the position sensor noise can extremely affect the stability of the system, so a tracking differentiator (TD) is proposed to obtain effective differential signal from relative position sensor. In vibration control, the feedback of acceleration combined with PD position feedback is presented to suppress transmission of periodic vibrations. Then, taking the acceleration transmission as the evaluation index, the acceleration transmission under the presented control method is derived, and the influence of control parameters on vibration isolation performance is discussed in detail. The vibration isolation performance is improved from 24.47 dB to 2.4 dB at resonance frequency, and −34 dB attenuation is achieved at 100 Hz with respect to vibration isolation mount system tested on the ground. The experimental results demonstrate that the performance of active vibration isolation system are improved by the proposed acceleration feedback control. Full article

It is well-known that the successful implementation of current sliding-mode guidance laws relies on two key points: one is the prior knowledge of the upper bound of the target’s maneuver, and the other is the accurate measurement of motion information. The truth maneuver is usually difficult to acquire and can only be roughly estimated. Measurements are often affected by noise and physical limitations of the onboard sensor. This paper presents an improved second-order sliding-mode guidance law that can handle these two problems simultaneously while addressing the chattering phenomenon, which inherently exists in the sliding mode-based controller. We achieve this by using the estimation from an extended state observer (ESO) and tracking differentiator (TD). In light of the employed ESO, which is utilized to give an estimation of the external disturbance, prior knowledge of the target’s maneuver is not required. Most interestingly, we show that the motion information can be estimated efficiently from the ESO in real time. A TD filter can be further embedded to remove unwanted noise from the detected signal. A series of simulations has been conducted, clearly demonstrating that the estimation accuracy of the ESO is sufficient for the guidance law to implement accurate interception. The TD filter not only removes noise but also avoids the phase-loss problems associated with conventional filters. Moreover, the chattering phenomenon is completely eliminated in the control channel. Full article

This paper presents a novel extended state observer (ESO) approach for a class of plants with nonlinear dynamics. The proposed observer estimates both the state variables and the total disturbance, which includes both exogenous and endogenous disturbance. The study’s changes can be summarized by developing a sliding mode higher-order extended state observer with a higher-order augmented state and a nonlinear function for the estimation error correction terms (SMHOESO). By including multiple enhanced states, the proposed observer can monitor total disturbances asymptotically, with the second derivative of the total disturbance serving as an upper constraint on the estimation error. This feature improves the observer’s ability to estimate higher-order disturbances and uncertainty. To extend the concept of the linear extended state observer (LESO), a nonlinear function can modify the estimation error in such a way that the proposed observer can provide faster and more accurate estimations of the state and total disturbance. The proposed nonlinearity also reduces the chattering issue with LESOs. This research thoroughly examines and analyzes the proposed SMHOESO’s convergence using the Lyapunov technique. According to this analysis, the SMHOESO is asymptotically stable, and the estimation error can be significantly reduced under real-world conditions. In addition to the SMHOESO, a modified Active Disturbance Rejection Control (ADRC) scheme is built, which includes a nonlinear state error feedback (NLSEF) controller and a nonlinear tracking differentiator (TD). Several nonlinear models, including the Differential Drive Mobile Robot (DDMR), are numerically simulated, and the proposed SMHOESO is compared to several alternative types, demonstrating a significant reduction in controller energy, increased control signal smoothness, and accurate tracking of the reference signal. Full article

As a new disk-shaped autonomous underwater vehicle (AUV), the autonomous underwater helicopter (AUH) is devoted to subsea operations, usually diving into the seabed and docking with a subsea docking system. Due to the motion control’s performance, the AUH’s stability and steady-state accuracy are affected remarkably while docking. Moreover, considering the difficulties of hydrodynamic modeling of AUHs, the classical model-based control method is unsuitable for AUHs. Moreover, there is a large gap between the hydrodynamic simulation results and real situations. Hence, based on the data-driven principle, the linear active disturbance rejection control with a tracking differentiator (LADRC-TD) algorithm is employed for AUH depths and heading control. As the simulation experiments prove, LADRC and LADRC-TD have better anti-interference performance when compared with PID. According to the pool experiments, overshoots of the LADRC-TD are 20 cm and 3° for the depth control and heading control, respectively, which are superior to PID and LADRC. Meanwhile, the steady-state accuracy of the LADRC-TD is ±21 cm and ±2.5° for the depth and heading control, respectively, which is inferior to PID and the same as LADRC. Full article

In this paper, two new versions of modified active disturbance rejection control (MADRC) are proposed to stabilize a nonlinear quadruple tank system and control the water levels of the lower two tanks in the presence of exogenous disturbances, parameter uncertainties, and parallel varying input set-points. The first proposed scheme is configured from the combination of a modified tracking differentiator (TD), modified super twisting sliding mode (STC-SM), and modified nonlinear extended state observer (NLESO), while the second proposed scheme is obtained by aggregating another modified TD, a modified nonlinear state error feedback (MNLSEF), and a fal-function-based ESO. The MADRC schemes with a nonlinear quadruple tank system are investigated by running simulations in the MATLAB/SIMULINK environment and several comparison experiments are conducted to validate the effectiveness of the proposed control schemes. Furthermore, the genetic algorithm (GA) is used as a tuning algorithm to parametrize the proposed MADRC schemes with the integral time absolute error (ITAE), integral square of the control signal (ISU), and integral absolute of the control signal (IAU) as an output performance index (OPI). Finally, the simulation results show the robustness of the proposed schemes with a noticeable reduction in the OPI. Full article

Smoothness is a hallmark of skilled, coordinated movement, however, mathematically quantifying movement smoothness is nuanced. Several smoothness metrics exist, each having its own limitations and may be specific to a particular motion such as upper limb reaching. To date, there is no consensus on which smoothness metric is the most appropriate for assessing cycling motion in children with cerebral palsy (CP). We evaluated the ability of four preexisting metrics, dimensionless jerk, spectral arc length measure, roughness index, and cross-correlation; and two new metrics, arc length and root mean square error, to quantify the smoothness of cycling in a preexisting dataset from children with CP (mean age 13.7 ± 2.6 years). First, to measure the repeatability of each measure in distinguishing between different levels of un-smoothness, we applied each metric to a set of simulated crank motion signals with a known number of aberrant revolutions using subjects’ actual crank angle data. Second, we used discriminant function analysis to statistically compare the strength of the six metrics, relative to each other, to discriminate between a smooth cycling motion obtained from a dataset of typically developed children (TD), the control group (mean age 14.9 ± 1.4 years), and a less smooth, halted cycling motion obtained from children with CP. Our results show that (1) ArcL showed the highest repeatability in accurately quantifying an unsmooth motion when the same cycling revolutions were presented in a different order, and (2) ArcL and DJ had the highest discriminatory ability to differentiate between an unsmooth and smooth cycling motion. Combining the results from the repeatability and discriminatory analysis, ArcL was the most repeatable and sensitive metric in identifying unsmooth, halted cycling motion from smooth motion. ArcL can hence be used as a metric in future studies to quantify changes in the smoothness of cycling motion pre- vs. post-interventions. Further, this metric may serve as a tool to track motor recovery not just in individuals with CP but in other patient populations with similar neurological deficits that may present with halted, unsmooth cycling motion. Full article

A feedforward strap-down control with a compensator base on the linear extended state observer (LESO) is proposed for a miniaturized camera stabilized platform, which reduces the influence of the dead zone in speed regulation and uncertainties in parameters to reduce the level of angular bias to the field of vision (FOV) in a low-cost stabilized platform. Firstly, the feedforward control is inspired by an approximate linear model proposed for the dead zone to improve the response velocity of the system when tracking the varying reference. Then, the compensator, combining the LESO and proportional differential (PD) law, is designed to eliminate the disturbances including the model bias in the dead zone, inaccuracy in the plant model, and external disturbance. Moreover, the observation performance of the LESO is improved by a preprocessor based on a tracking differentiator (TD) to deal with the time delay and nonlinearities in sampling the state variables. Meanwhile, the complex and uncertain control plant is also simplified by an approximate model combining a disturbance compensator for practical application. Finally, the feasibility of the proposed controller is verified and analyzed by the simulation, and its effectiveness is simultaneously validated by the 2-DOF camera stabilized platform. Full article

Compared to alternating current (AC) grids, direct current (DC) grids are becoming more and more popular. A power distribution approach is suggested in order to solve the issue of uneven power distribution of distributed generation (DG) in a ship DC microgrid. Power control is carried out using a tracking differentiator (TD), while the output power change rate is not greater than the maximum power ramp rate permitted by the battery, and state-of-charge balance is attained quickly. The proposed strategy also reduces the communication pressure on the power grid. A distributed hierarchical control model of a DC microgrid based on a consensus algorithm is created in order to validate the suggested methodology. The simulation results demonstrate that the established model is capable of simulating the DC microgrid accurately, that the states of charge values of the five batteries gradually converge under the adjustment of the secondary strategy, and that the suggested strategy is reasonable and efficient. Full article

The quadrotor aircraft has the characteristics of simple structure, high attitude maintenance performance and strong maneuverability, and is widely used in air surveillance, post−disaster search and rescue, target tracking and military industry. In this paper, a robust control scheme based on linear active disturbance rejection is proposed to solve the problem that the quadrotor is susceptible to various disturbances during the take−off process of non−horizontal planes and strong disturbances. Linear Active Disturbance Rejection Control (LADRC) is a product of a tracking differentiator (TD), a linear extended state observer (LESO) and an error feedback control law (PD) and is a control technique for estimating compensation for uncertainty. Radial Basis Function Neural Networks (RBFNN) is a well−performing forward network with best approximation, simple training, fast learning convergence and the ability to overcome local minima problems. Combined with the advantages and disadvantages of LADRC, Adaptive Control and Neural Network, the coupling force between each channel, gust crosswind disturbance and additional resistance of offshore platform jitter in the flight state of the quadrotor are optimized. In the control, the RBF neural network is designed, the nonlinear control signal is wirelessly approximated and the uncertain disturbance to the quadrotor is identified online. Finally, the real−time estimation and compensation are performed by LESO to realize the full−attitude take−off of the quadrotor. In addition, this paper uses adaptive control to optimize the parameters of LADRC to reduce the problem of many LADRC parameters and difficulty to integrate. Finally, the robust control system mentioned in this paper is simulated and verified, and the simulation results show that the control scheme has the advantages of simple parameter adjustment and stronger robustness. Full article

Motivated by the fact that electrical transients are rather fast compared with mechanical response, the traditional cascade control structure constituted by the inner current and outer speed loops is usually employed in the permanent magnet synchronous motors (PMSMs) servo control community. According to the above-mentioned time-scale characteristic of the PMSMs drive systems, this technique addresses the problems of the non-cascade sliding mode control (SMC) strategy for the surface-mounted PMSMs. Firstly, by appropriately introducing the singular perturbation theory, the corresponding mathematical equations are modeled as a singular perturbation system. Meanwhile, a composite sliding mode surface is constructed based on the Lyapunov equation, such that the system stability can be also guaranteed. Then, according to the exponential reaching law, a standard non-cascade SMC law is designed. Furthermore, an optimal nonlinear function-based tracking differentiator (TD) is presented to smooth the reference velocity value, while providing differential signals. As a result, a novel TD-based SMC strategy is synthesized by incorporating a nonlinear function, thus improving the inherent chattering phenomenon. Finally, a surface-mounted PMSM servo system is performed to illustrate the advantages and effectiveness of the proposed approaches. The main contribution of this paper is to present an alternative non-cascade SMC framework based on the singular perturbation approach, which provides a novel control structure for a PMSM speed regulation system. Full article

Variable flow ducted rockets (VFDRs) are promising candidates for propulsion systems in hypersonic vehicles because of their inherent advantages, such as high specific impulse, low weight, and high speed. The control of gas flow is essential for optimal VFDRs performance. However, the characteristics of gas flow regulation systems, such as anti-regulation, non-linearity, and parameter variation, make it difficult to construct gas flow controllers. Aiming at the above problems, we propose a compound control strategy integrating a novel second-order fuzzy adaptive tracking differentiator (SOA-TD) and an intelligent proportional-integral controller based on adaptive neuro-fuzzy inference system (ANFIS). First, a mathematical model of a gas flow regulation system was developed to analyze the control characteristics of VFDRs. Next, an ANFIS-based proportional-integral controller to developed to respond to the system’s time-varying characteristics. In addition, a novel SOA-TD was constructed to optimize the “arrange transient process” of instructions, which effectively suppressed anti-regulation of the gas flow without increasing response time. Finally, a hardware in loop (HIL) simulation device for VFDRs was established, and serial HIL simulation tests were carried out to verify the validation of the controller. The HIL simulation results indicate that our strategy exhibited a superior performance compared to traditional controllers in terms of adaptability, ability to suppress anti-regulation, and robustness, which is hoped to fulfill VFDRs’ thrust control requirements for a wide range of altitudes and Mach numbers in future engineering applications. Full article