Closed-loop Proportional-integral-derivative Research Articles

Self-tuning speed and flow control of micro turbojet engines based on an improved evolutionary strategy

At present, the controllable parameters of micro turbojet engines in engineering applications are mainly speed-fuel flow (hereinafter referred to as flow) control, in which closed-loop proportional–integral–derivative (PID) control is mostly used to achieve a stable control of engine speed under slow engine conditions. For the optimal adjustment of PID parameters, this paper designs an improved evolutionary strategy for the self-tuning of control parameters in the engine speed and flow control system and formulates an improved PI controller based on a neural network. The simulation experimental results show that the method can realistically achieve stable and fast control of the engine under above slow conditions.

FusionCPP: Cooperative fusion of infrared and visible light images based on PCNN and PID control systems

The imaging results of infrared and visible light sensors are highly complementary. Thus, combining the two images can compensate for the shortcomings of a single sensor. However, previous fusion methods have not fully utilized the collaborative guidance of infrared and visible images in the fusion process, leading to a poor correlation between extracted features and cannot guarantee feature fusion accuracy. In order to address these challenges, this paper proposes a collaborative fusion method for infrared and visible images based on pulse-coupled neural networks (PCNN) and proportional-integral-derivative (PID) control systems, called FusionCPP. First, a coupled neural network with a dual pulse structure is designed for the feature extraction section. Unlike traditional PCNN, this network includes two pulse generators, one of which is utilized to extract the salient features of the image, while the other is employed to extract the common pulse layer of the source image and multiply the pulse layer by the coupling iteration value to obtain the base layer. Second, a detail layer is obtained by subtracting the base layer from the source image. This method accurately extracts salient and detailed features based on the coupling between source images. Finally, a closed-loop PID control system is utilized as the fusion strategy in the image fusion task, which judges the difference between the fusion result and the source image in real-time through the feedback effect of the system. The controller adaptively adjusts the fusion weight based on the difference to fuse image features into the new image accurately. Experimental results indicate that the proposed FusionCPP can maintain significant contrast and rich textures. Besides, the proposed FusionCPP has extended to multi-focus image fusion and target detection tasks to verify its effectiveness.

Development and Validation of an Active Muscle Simplified Finite Element Human Body Model in a Standing Posture.

Active muscles play an important role in postural stabilization, and muscle-induced joint stiffening can alter the kinematic response of the human body, particularly that of the lower extremities, under dynamic loading conditions. There are few full-body human body finite element models with active muscles in a standing posture. Thus, the objective of this study was to develop and validate the M50-PS+Active model, an average-male simplified human body model in a standing posture with active musculature. The M50-PS+Active model was developed by incorporating 116 skeletal muscles, as one-dimensional beam elements with a Hill-type material model and closed-loop Proportional Integral Derivative (PID) controller muscle activation strategy, into the Global Human Body Models Consortium (GHBMC) simplified pedestrian model M50-PS. The M50-PS+Active model was first validated in a gravity standing test, showing the effectiveness of the active muscles in maintaining a standing posture under gravitational loading. The knee kinematics of the model were compared against volunteer kinematics in unsuited and suited step-down tests from NASA's active response gravity offload system (ARGOS) laboratory. The M50-PS+Active model showed good biofidelity with volunteer kinematics with an overall CORA score of 0.80, as compared to 0.64 (fair) in the passive M50-PS model. The M50-PS+Active model will serve as a useful tool to study the biomechanics of the human body in vehicle-pedestrian accidents, public transportation braking, and space missions piloted in a standing posture.

Spherical Indoor Coandă Effect Drone (SpICED): A Spherical Blimp sUAS for Safe Indoor Use

Even as human–robot interactions become increasingly common, conventional small Unmanned Aircraft Systems (sUAS), typically multicopters, can still be unsafe for deployment in an indoor environment in close proximity to humans without significant safety precautions. This is due to their fast-spinning propellers, and lack of a fail-safe mechanism in the event of a loss of power. A blimp, a non-rigid airship filled with lighter-than-air gases is inherently safer as it ’floats’ in the air and is generally incapable of high-speed motion. The Spherical Indoor Coandă Effect Drone (SpICED), is a novel, safe spherical blimp design propelled by closed impellers utilizing the Coandă effect. Unlike a multicopter or conventional propeller blimp, the closed impellers reduce safety risks to the surrounding people and objects, allowing for SpICED to be operated in close proximity with humans and opening up the possibility of novel human–drone interactions. The design implements multiple closed-impeller rotors as propulsion units to accelerate airflow along the the surface of the spherical blimp and produce thrust by utilising the Coandă effect. A cube configuration with eight uni-directional propulsion units is presented, together with the closed-loop Proportional–Integral–Derivative (PID) controllers, and custom control mixing algorithm for position and attitude control in all three axes. A physical prototype of the propulsion unit and blimp sUAS was constructed to experimentally validate the dynamic behavior and controls in a motion-captured environment, with the experimental results compared to the side-tetra configuration with four bi-directional propulsion units as presented in our previously published conference paper. An up to 40% reduction in trajectory control error was observed in the new cube configuration, which is also capable of motion control in all six Degrees of Freedom (DoF) with additional pitch and roll control when compared to the side-tetra configuration.

Design of a closed-loop autotune PID controller for three-phase for power factor corrector with Vienna rectifier

A closed-loop auto-tuner proportional integral derivative (PID) controller for tuning the DC-link voltage, voltage neutral controllers, and DQ axis current for a power factor corrector with Vienna rectifier is developed and discussed in this study. In traditional tuning of these control loops, it is needed to tune one loop at a time manually, which tends to be a difficult and time-consuming process. In this work, we add a closed-loop PID auto-tuner in the control design will help to simplify and speed up this process by tuning all the 4 PID controllers in a single simulation running in a closed loop. Essentially, it runs auto-tuning experiments for the DQ axis -current, output voltage, and neutral point voltage loops by injecting perturbations; recording the output; estimating the plant frequency response, and tuning the PI controller parameters. In DQ-axis control, projections are used to convert time-based3-phase currents into a time invariant 2-coordinate vector. The results after adding the auto-tuner show that the response time improved considerably when the balanced load was introduced with the individual loads being connected. The results show that the neutral point voltage controller did a good job of keeping the voltage neutral point stable compared to the older controller gains.

Modelling and proportional-integral-derivative controller design for position analysis of the 3-degree of freedom

A closed-loop system or which can also be known as a feedback system helps the system to achieve the desired output by comparing the input and the output values. If any difference is detected, the closed-loop system will create an error signal and automatically responds to it. Other than that, the proportional-integral-derivative (PID) controller has a feedback mechanism. Thus, this creates the curiosity whether the closed-loop system and PID which both have the characteristic of a feedback system, can give the same. In this paper, the comparison of the model of 3 degree of freedom (DOF) Mitsubishi RV2-AJ is being made between two models of a robot arm that has a closed-loop system but only one that is embedded with PID controller while the other one is not, these two are simulated for different positions. The new model is created by using Solidworks which is later exported to Matlab-Simulink. The results from MATLAB-Simulink show that the model which is equipped with a PID controller has better results in terms of the rise time and percentage of overshoot. These results confirm the effectiveness of PID controller in producing smaller errors in the systems even when both models are created together with closed-loop systems.

Integrated Physical Modeling and Optimal Control Method of Limited-Angle Torque Motor in Fuel Metering Apparatus

Limited-angle torque motor (LATM) is a critical component to precisely drive the valve angle of an engine’s fuel metering apparatus and accurately measure the fuel flow, and research on it is of great significance. Thus, the LATM of a certain kind is regarded as the research object in this paper. Firstly, a Simscape-based LATM integrated physical modeling method is proposed, which can better demonstrate the real operational characteristics of a motor, compared with the current mathematical model. Secondly, a Proportional-Integral-Derivative (PID) parameter self-tuning method based on a constriction factor particle swarm optimization (CPSO) algorithm is broached since it is difficult to tune due to a large number of multi-loop cascade PID control parameters. Simulation and experimental results showed that the control performance increases by 40% in the triple closed-loop PID control system with a stronger disturbance rejection, simpler design, and quickly responds when compared with the previous empirical tuning method. The triple closed-loop PID control system comprises an angle loop + angle velocity loop + current loop and technically supports the engineering application design of motors.

Performance Comparison of PID and NARX Neural Network for Attitude Control of a Quadcopter UAV

ABSTRACT: In this study, two different types of controllers have been designed and tested for altitude and motion control of an autonomous quadrotor to compare the control performance under the influence of parametric uncertainty and disturbances. The first controller is a proportional-integral-derivative (PID) controller which is a conventional linear controller. The closed-loop PID algorithms calculate the results of the system by using the error values that consist of the difference between the sensor values measured by the closed-loop feedback method and the reference inputs. The second method that has been used is artificial neural network (ANN) algorithms, which provide both advantages and convenience in defining and controlling linear systems and non-linear systems with the closed-loop feedback method used in PID. The most important feature of the ANN algorithms is their high performance as a result of training with different input values. Therefore, the ANN control system has been trained with the input data used with Gaussian noise and the desired target data. A dynamic time series non-linear autoregressive with Exogenous input (NARX) neural network has been chosen as an ANN controller because of the time-delayed backpropagation learning performance. In this study, PID, and NARX NN control algorithms to control the maneuvers and altitude of the quadcopter and the mathematical model have been designed on Matlab Simulink. Motion control performances of the PID and NARX controllers are tested on the model. The design was tested on a real-time simulation environment with a one-millisecond fixed-step size. This paper proposes an alternative approach to control attitude and altitude on a quadcopter with the NARX NN algorithm.

An efficient PID-based optimizer loop and its application in De Jong’s functions minimization and quadratic regression problems

The Proportional–Integral–Derivative (PID) control law has been commonly used for process control in control engineering applications. However, it has potential to work as a solver in optimization problems. This study introduces a PID-based optimizer loop that is designed to solve nonlinear, unconstrained, multi-parameter optimization problems. To achieve the minimization of multi-parameter positive real objective functions by using a closed loop PID control loop, a slope sentient objective function model is suggested to allow zero-crossing of the error signal. Thus, this objective function model enhances the convergence efficiency of the PID-based optimizer loop by indicating slope direction of the objective function and operating in both positive and negative error regions. The boundedness and convergence theorems for the proposed PID optimizer loop are presented, and a theoretical background for the PID-based minimization is established. To demonstrate practical minimization performance, numerical applications of the proposed PID optimizer loops are illustrated in the solution of two fundamental optimization problems. These are the minimization of 30 parameters De Jong’s functions and the solution of quadratic regression problems. Also, an experimental study is presented for the quadratic regression modeling of measurement data from a hole-drilling experiment. Optimization results reveal that the proposed PID-based optimizer system can improve convergence speed and accuracy compared to performances of fundamental nonlinear optimization techniques. • A novel closed loop PID-based optimizer system is proposed to solve optimization problems. • The proposed PID optimizer loop uses a slope sentient objective function model. • The slope sentient objective function model provides slope direction info. • The PID optimizer loop is compared with gradient-based optimization methods. • Test results indicate improved minimization performance of PID optimizer loops.

Adaptive Fuzzy Neural Network PID Algorithm for BLDCM Speed Control System

Because of its simple structure, high efficiency, low noise, and high reliability, the brushless direct current motor (BLDCM) has an irreplaceable role compared with other types of motors in many aspects. The traditional proportional integral derivative (PID) control algorithm has been widely used in practical engineering because of its simple structure and convenient adjustment, but it has many shortcomings in control accuracy and other aspects. Therefore, in this paper, a fuzzy single neuron neural network (FSNNN) PID algorithm based on an automatic speed regulator (ASR) is designed and applied to a BLDCM control system. This paper introduces a BLDCM mathematical model and its control system and designs an FSNNN PID algorithm that takes speed deviation e at different sampling times as inputs of a neural network to adjust the PID parameters, and then it uses a fuzzy system to adjust gain K of the neural network. In addition, the frequency domain stability of a double closed loop PID control system is analyzed, and the control effect of traditional PID, fuzzy PID, and FSNNN PID algorithms are compared by setting different reference speeds, as well as the change rules of three-phase current, back electromotive force (EMF), electromagnetic torque, and rotor angle position. Finally, results show that a motor controlled by the FSNNN PID algorithm has certain superiority compared with traditional PID and fuzzy PID algorithms and also has better control effects.

Microscale creep and stress relaxation experiments with individual collagen fibrils

Nanoscale macromolecular biological structures exhibit time-dependent mechanical behavior, yet a quantitative understanding of their creep and stress relaxation behavior remains elusive, largely due to experimental challenges in attaining sufficient spatial and temporal resolution and control of stress or strain in conditions that guarantee their molecular integrity. To address this gap, an experimental methodology was developed to conduct creep and stress relaxation experiments with individual mammalian collagen fibrils. An image-based edge detection method, implemented with high magnification optical microscopy and combined with closed-loop proportional–integral–derivative (PID) control, was implemented and calibrated to apply constant force or stretch ratio to individual collagen fibrils via a Microelectromechanical Systems (MEMS) device. This experimental methodology allowed for real-time control of uniaxial tensile stress or strain with ~25 nm displacement accuracy. The overall experimental system was tuned to apply step inputs with rise times below 0.5 s, less than 5% overshoot, and steady-state error smaller than 1%. Three collagen fibrils with diameters in the range 101–121 nm were subjected to creep and stress relaxation tests in the range 4–20% engineering strain, under partially hydrated conditions. The collagen fibrils demonstrated non-linear viscoelastic behavior that was described well by the adaptive quasi-linear viscoelastic model. The results of this study demonstrated for the first time that mammalian collagen fibrils, the building blocks of connective tissues, exhibit nonlinear viscoelastic behavior in their partially hydrated state.

Rotation Speed Control of the Rotary Valve in MWD Tools Based on Speed Feedforward Compensation

The rotary valve speed control, seriously affected by the nonlinear characteristic of rotary valve load torque, affects the generation of drilling fluid pressure phase shift keying (PSK) signal and its quality. The calculation model feedforward of the load torque acts on the speed control system and enables the motor voltage to change according to the law of calculation model, and the linearization correction of the speed system is performed. Additionally, the flow measurement is introduced into the calculation model of the load torque to track the load torque change with the flow, suppressing the influence of large changes in flow rate on open-loop control of rotary valve speed. The closed-loop proportional-integral-derivative (PID) control is formed by negative feedback of speed, and the PID parameter value rule is established based on the rapid decay control of transient component in the rotary valve speed step response, which speeds up the tracking of the rotary valve speed following the control voltage pulse and reduces the distortion of the drilling fluid pressure PSK signal, increasing the frequency of the drilling fluid pressure carrier and improving the transmission rate of downhole information. Simulink simulation indicates that the closed-loop PID control of rotary valve speed can track the change of control voltage pulse quickly and strongly suppress the interference influences from flow measurement error and load torque calculation model deviation.

Determination of optimal PID control parameters by response surface methodology

Proportional–Integral–Derivative (PID) controllers are the most widely used systems in industrial applications and in academic research regarding control engineering. In this study, the optimal PID control parameters of a liquid level control system were determined with Response Surface Methodology. Dynamic analysis was carried out on the liquid level control system to prepare the reaction curve. Accordingly, dead time, time constant and process gain values were determined as 16s, 261s and 0.842, respectively. Based on the dynamic analysis, PID parameters were calculated in accordance with the Cohen-Coon, Ziegler-Nichols, Yuwana-Seborg methods, which are the commonly used tuning methods. The Kp, τI, τD parameters were calculated as 30.77, 29.15 and 5.4 with the Cohen-Coon method, as 0.453, 30.0 and 7.5 with the Ziegler-Nichols method and as 1.63, 686.3 and 117.7 with the Yuwana-Seborg method, respectively. The PID control parameters applied for the 40cm, 50cm and 60cm set points and ISE and IAE control performance values after experiments were calculated. The Kp, τI and τD values were selected as the independent parameters, while the ISE and IAE values were chosen as the dependent variables. The numerical values of the responses for the runs in the design matrices were determined with a closed-loop PID controller with the liquid level system block diagram that was designed in MATLAB/Simulink. The simulations proposed by the trial version of Design Expert 7.0 program were performed in order and the IAE and ISE values were calculated after the simulations were processed. In this study, minimum ISE and IAE values were selected to determine the best PID parameters of a liquid level control system. The optimal PID control parameters of the liquid level system required to obtain the lowest ISE and IAE values were determined as 23.14, 28.31 and 11.50 for Kp, τI and τD, respectively.

Parameter optimization of nanosilver colloid prepared by electrical spark discharge method using Ziegler-Nichols method

This study adopted a self-developed real-time monitoring micro electrical discharge machine (micro-EDM) system for nanosilver colloid preparation through the electrical spark discharge method (ESDM). The developed system relies on the parameters modulated through a closed-loop proportional-integral-derivative (PID) controller and optimized through the Ziegler–Nichols method to get modulated PID parameters, affect the process duration of ESDM. In the present study, samples were prepared under varying process durations and pulse modulation (TON–TOFF) duty cycles. Various instruments were applied to compare the absorbance values, discharge success rates, and particle size distributions of these samples. The results indicated that, compared with the samples prepared through the closed-loop PID controller, the samples prepared through the modulated PID parameters exhibited substantially higher absorbance, discharge success rates, and smaller particle size distribution. The improved discharge success rate is increased to an average of 129% compared to the original parameters. The particle size distributions of samples based on the empirical data averaged 10–20 nm, whereas the samples based on the parameters modulated through the Ziegler–Nichols method were primarily smaller than 10 nm, with the averaged size being 7.068 nm. These confirmed the effectiveness of the Ziegler–Nichols method in optimizing ESDM nanosilver colloid preparation.

Vehicle Path Generation and Tracking in Mixed Road Traffic

Given the condition of mixed road traffic, few models exist that can predict the motion of a vehicle in it. Mixed road traffic can be defined as being both, lane indisciplined and heterogeneous. This study aims at developing a model that can analyze a given traffic condition, generate a safe trajectory and provide a control input to the vehicle to follow it. The paper explains the flow of the model, starting with traffic interaction, leader detection, and waypoint derivation. Post this, the trajectory is generated, the tracking errors are discussed and a controller is designed to navigate the trajectory by minimizing the discussed errors. Since the assumption of low speed is made, a kinematic model is used when generating feasibility criteria for the trajectory. Once the trajectory is determined to be feasible, a closed-loop Proportional Integral Derivative (PID) controller provides steering input to the vehicle to follow the trajectory. The controller tuning is performed using a dynamic bicycle model considering the error with respect to the trajectory. The trajectory generation model and the controller for trajectory following are implemented in independent simulator environments. The resulting output is a collision-free trajectory as followed by the subject vehicle (SV) to meet the generated waypoints which are based on the traffic scenario.

Modeling and Control Design for an Inlet Metering Valve-Controlled Pump Used to Control Actuator Velocity Via H-Infinity and Two-Degrees-of-Freedom Methods

Using a unique inlet metering pump with fixed displacement and speed, this work introduces a new way to control a linear hydraulic actuator velocity. The inlet metering system consists of an inlet metering valve that adjusts the hydraulic fluid flow that enters the pump and a fixed displacement pump. Fluid is supplied to the inlet metering valve at a fixed pressure. Energy losses associated with flow metering in the system are reduced because the pressure drop across the inlet metering valve can be small compared to a traditional valve-controlled system. A velocity control system is designed using the inlet metering pump to control the fluid flow into a hydraulic cylinder. First, the valve dynamic model is ignored, the open-loop response is studied, and closed-loop proportional and proportional derivative controllers are designed. Next, the valve dynamic model is included and closed-loop proportional integral derivative, H∞, and two-degrees-of-freedom controllers are designed. Designs with the goals of stability and performance of the system are considered so that a precise velocity control system for the hydraulic cylinder is achieved. In addition to the potentially high efficiency of this system, there is potential for low-cost, fast-response, and less complicated dynamics compared to other systems. The results show that the velocity control system can be designed so that the system is stable for all cases and with 0% overshoot and no oscillation depending on valve dynamics using the two-degrees-of-freedom controller for tracking the desired velocity.

Application of response surface methodology as a new PID tuning method in an electrocoagulation process control case.

In this work the application of response surface methodology (RSM) to proportional-integral-derivative (PID) controller parameter tuning for electrocoagulation (EC) treatment of pulp and paper mill wastewater was researched. Dynamic data for two controlled variables (pH and electrical conductivity) were obtained under pseudo random binary sequence (PRBS) input signals applied to manipulated variables (acid and supporting electrolyte flow rates). Third order plus time delay model parameters were evaluated through System Identification Toolbox™ in MATLAB®. Four level full factorial design was applied to form a design matrix for three controller tuning parameters as factors and to evaluate statistical analysis of the system in terms of integral of square error (ISE), integral of absolute error (IAE), integral of time square error (ITSE) and integral of time absolute error (ITAE) performance criteria as response. Numerical values of the responses for the runs in the design matrices were determined using closed-loop PID control system simulations designed in Simulink®. Optimum proportional gain, integral action and derivative action values for electrical conductivity control were found to be 1,500 s, 0 s and 16.4636 s respectively. Accordingly, the same optimization scheme was followed for pH control and optimum controller parameters were found to be -8.6970 s, 0.0211 s and 50 s, respectively. Theoretically optimized controller parameters were applied to batch experimental studies. Chemical oxygen demand (COD) removal efficiency and energy consumption of pulp and paper mill wastewater treatment by EC under controlled action of pH at 5.5 and electrical conductivity at 2.72 mS/cm was found to be 85% and 3.87 kWh/m3 respectively. Results showed that multi input-multi output (MIMO) control action increased removal efficiency of COD by 15.41% and reduced energy consumption by 6.52% in comparison with treatment under uncontrolled conditions.

Development of an electric-driven control system for a precision planter based on a closed-loop PID algorithm

This study presented the design of an electric-driven control system for the seed meter of a precision planter to avoid the issues of poor planting quality and low travel speed limitations associated with conventional ground wheel and chain driven planters. A closed-loop proportional-integral-derivative (PID) algorithm was deployed to control the seed plate rotation speed. The performance of three PID tuning methods (Ziegler-Nichols step response method (ZNM), Cohen-Coon method (CCM), and Chien–Hrones–Reswick method (CHRM)) was compared by Matlab-Simulink simulation, and results testified that the CCM had a better performance with smallest rise time of 0.018s, settling time of 0.082s and maximum overshoot of 26.1%. Field experiments indicated that a four-row planter equipped with the developed electric-driven control system had significantly better quality of feed index (QFI), miss index (MI), and precision index (PREC) values compared with those of a ground wheel and chain driven planter under equivalent working conditions. For a travel speed of 8.6km/h, the average values of the four rows for the QFI, MI, and the PREC were 98.62%, 1.29%, and 14.51%, respectively. For a high travel speed of 13.0km/h, the average QFI still achieved a value of 97.09%. Most of the components employed in the system were made in China, and the overall system cost was much less than similar systems obtained from abroad. As such, the proposed system is accessible to precision planters in developing countries.

Robust PID based indirect-type iterative learning control for batch processes with time-varying uncertainties

Based on the proportional-integral-derivative (PID) control structure widely used in engineering applications, a robust indirect-type iterative learning control (ILC) method is proposed for industrial batch processes subject to time-varying uncertainties. An important merit is that the proposed ILC design is independent of the PID tuning that aims primarily to hold robust stability of the closed-loop system, owing to the fact that the ILC updating law is implemented through adjusting the setpoint of the closed-loop PID control structure plus a feedforward control to the plant input from batch to batch. According to the robust H infinity control objective, a robust discrete-time PID tuning algorithm is given in terms of the plant state-space model description to accommodate for time-varying process uncertainties. For the batchwise direction, a robust ILC updating law is developed based on the two-dimensional (2D) control system theory. Only measured output errors of current and previous cycles are used to implement the proposed ILC scheme for the convenience of practical application. An illustrative example from the literature is adopted to demonstrate the effectiveness and merits of the proposed ILC method.

Compound Velocity Synchronizing Control Strategy for Electro-Hydraulic Load Simulator and Its Engineering Application.

An electro-hydraulic load simulator (EHLS) is a typical case of torque systems with strong external disturbances from hydraulic motion systems. A new velocity synchronizing compensation strategy is proposed in this paper to eliminate motion disturbances, based on theoretical and experimental analysis of a structure invariance method and traditional velocity synchronizing compensation controller (TVSM). This strategy only uses the servo-valve's control signal of motion system and torque feedback of torque system, which could avoid the requirement on the velocity and acceleration signal in the structure invariance method, and effectively achieve a more accurate velocity synchronizing compensation in large loading conditions than a TVSM. In order to facilitate the implementation of this strategy in engineering cases, the selection rules for compensation parameters are proposed. It does not rely on any accurate information of structure parameters. This paper presents the comparison data of an EHLS with various typical operating conditions using three controllers, i.e., closed loop proportional integral derivative (PID) controller, TVSM, and the proposed improved velocity synchronizing controller. Experiments are conducted to confirm that the new strategy performs well against motion disturbances. It is more effective to improve the tracking accuracy and is a more appropriate choice for engineering applications.