Disturbance Rejection Strategy Research Articles

Correction: Li et al. Attitude Control of UAVs with Search Optimization and Disturbance Rejection Strategies. Mathematics 2023, 11, 3794

In the original publication [...]

To what extent implanting single vs pairs of magnets per muscle affect the localization accuracy of the myokinetic control interface? Evidence from a simulated environment.

We recently proposed a new concept of human-machine interface to control hand prostheses which we dubbed the myokinetic control interface. Such interface detects muscle displacement during contraction by localizing permanent magnets implanted in the residual muscles. So far, we evaluated the feasibility of implanting one magnet per muscle and monitoring its displacement relative to its initial position. However, multiple magnets could actually be implanted in each muscle, as using their relative distance as a measure of muscle contraction could improve the system robustness against environmental disturbances. Here, we simulated the implant of pairs of magnets in each muscle and we compared the localization accuracy of such system with the one magnet per muscle approach, considering first a planar and then an anatomically appropriate configuration. Such comparison was also performed when simulating different grades of mechanical disturbances applied to the system (i.e. shift of the sensor grid). We found that implanting one magnet per muscle always led to lower localization errors under ideal conditions (i.e. no external disturbances). Differently, when mechanical disturbances were applied, magnet pairs outperformed the single magnet approach, confirming that differential measurements are able to reject common mode disturbances. We identified important factors affecting the choice of the number of magnets to implant in a muscle. Our results provide important guidelines for the design of disturbance rejection strategies and for the development of the myokinetic control interface, as well as for a whole range of biomedical applications involving magnetic tracking.

Attitude Control of UAVs with Search Optimization and Disturbance Rejection Strategies

This study aims to achieve rapid and stable control of quadrotor unmanned aerial vehicles’ (UAVs) attitude by using an Active Disturbance Rejection Control (ADRC) controller. Addressing the challenge of numerous and complex ADRC parameters, optimization algorithms are employed for parameter tuning. This paper draws on the group mechanism of the Ant Colony Optimization (ACO) algorithm and innovatively introduces population search into the Beetle Antennae Search (BAS) algorithm. The refined algorithm is then applied to tune the ADRC parameters, reducing complexity and human intervention while enhancing intelligence and efficiency. The advanced optimization algorithm exhibits an exceptional global optimization capacity, convergence speed, and stability. Ultimately, flight simulation and experimental results suggest that the optimized ADRC controller demonstrates superior control and antidisturbance capabilities.

Attitude Control of Ornithopter Wing by Using a MIMO Active Disturbance Rejection Strategy.

This work proposes a mathematical solution for the attitude control problem of an ornithopter wing. An ornithopter is an artificial bird or insect-like aerial vehicle whose flight and lift movements are produced and maintained by flapping wings. The aerodynamical drag forces responsible for the flying movements are generated by the wing attitude and torques applied to its joints. This mechanical system represents a challenging problem because its dynamics consist of MIMO nonlinear equations with couplings in the input variables. For dealing with such a mathematical model, an Active Disturbance Rejection Control-based (ADRC) method is considered. The cited control technique has been studied for almost two decades and its main characteristics are the use of an extended state observer to estimate the nonmeasurable signals of the plant and a state-feedback control law in standard form fed by that observer. However, even today, the application of the basic methodology requires the exact knowledge of the plant's control gain which is difficult to measure in the case of systems with uncertain parameters. In addition, most of the related works apply the ADRC strategy to Single Input Single Output (SISO) plants. For MIMO systems, the control gain is represented by a square matrix of general entries but most of the reported works consider the simplified case of uncoupled inputs, in which a diagonal matrix is assumed. In this paper, an extension of the ADRC SISO strategy for MIMO systems is proposed. By adopting such a control methodology, the resulting closed-loop scheme exhibits some key advantages: (i) it is robust to parametric uncertainties; (ii) it can compensate for external disturbances and unmodeled dynamics; (iii) even for nonlinear plants, mathematical analysis using Laplace's approach can be always used; and (iv) it can deal with system's coupled input variables. A complete mathematical model for the dynamics of the ornithopter wing system is presented. The efficiency of the proposed control is analyzed mathematically, discussed, and illustrated via simulation results of its application in the attitude control of ornithopter wings.

Active design of dynamic GP models for model predictive control using expected improvement

AbstractModelling is a basic and key requirement for model‐based controlling, monitoring, or other process strategies. In non‐linear model predictive control (NMPC), although data‐driven models can be more easily established than first‐principle ones, representative data may not be adequately included in advance to train a complete model, which is an attractive research topic. An actively improved Gaussian process (GP) model building strategy is developed, especially for incomplete models based on the idea of Bayesian optimization. The GP model can be used online as the internal model of model predictive control (MPC) directly. The model‐building objective is based on the expected improvement strategy, which can exploit information gained from the currently gathered data as well as explore uncharted regions. The proposed method is a real‐time design of experiments based on variance information of GP for efficient model building with insufficient initial training data for NMPC. Multi‐step ahead prediction model is considered to give full play to predicting features of NPMC. Besides, a novel disturbance rejection strategy is also proposed based on GP outputs. Two simulation results, including comparisons with some traditional algorithms, are presented to demonstrate the effectiveness of the proposed method.

Active Disturbance Rejection Strategy for Distance and Formation Angle Decentralized Control in Differential-Drive Mobile Robots

The important practical problem of robust synchronization in distance and orientation for a class of differential-drive mobile robots is tackled in this work as an active disturbance rejection control (ADRC) problem. To solve it, a kinematic model of the governed system is first developed based on the distance and formation angle between the agents. Then, a special high-order extended state observer is designed to collectively estimate the perturbations (formed by longitudinal and lateral slipping parameters) that affect the kinematic model. Finally, a custom error-based ADRC approach is designed and applied assuming that the distance and orientation between the agents are the only available measurements. The proposed control strategy does not need time-derivatives of the reference trajectory, which increases the practical appeal of the proposed solution. The experimental results, obtained in laboratory conditions with a set of differential-drive mobile robots operating in a leader–follower configuration, show the effectiveness of the proposed governing scheme in terms of trajectory tracking and disturbance rejection.

Optimal resource allocation for high‐order nonlinear uncertain multi‐agent systems

AbstractThis article investigates the optimal resource allocation of nonlinear high‐order multi‐agent systems with coupling uncertainties. The objective is to design an output‐feedback distributed algorithm for each agent to optimize the global cost function under network constraints. The global cost function is the sum of local cost functions. The available information to design the algorithm for each agent is only its own output and cost function, the outputs of its neighbors. To address the key technical challenge arising from the uncertainties and nonlinearities of network systems, a novel distributed resource allocation algorithm is proposed using active disturbance rejection strategy. The simulation results in the economic dispatch of a smart grid validate the effectiveness of the proposed method.

A Robust Dynamic Control Strategy for Standalone PV System under Variable Load and Environmental Conditions

Dual-stage standalone photovoltaic (PV) systems suffer from stability, reliability issues, and their efficiency to deliver maximum power is greatly affected by changing environmental conditions. A hybrid back-stepping control (BSC) is a good candidate for maximum power point tracking (MPPT) however, there are eminent steady-state oscillations in the PV output due to BSC’s recursive nature. The issue can be addressed by proposing a hybrid integral back-stepping control (IBSC) algorithm where the proposed integral action significantly reduces the steady-state oscillations in the PV array output under varying temperature and solar irradiance level. Simultaneously, at the AC stage, the primary challenge is to reduce both the steady-state tracking error and total harmonic distortion (THD) at the output of VSI, resulting from the load parameter variations. Although the conventional sliding mode control (SMC) is robust to parameter variations, however, it is discontinuous in nature and inherit over-conservative gain design. In order to address this issue, a dynamic disturbance rejection strategy based on super twisting control (STC) has been proposed where a higher order sliding mode observer is designed to estimate the effect of load disturbances as a lumped parameter which is then rejected by the newly designed control law to achieve the desired VSI tracking performance. The proposed control strategy has been validated via MATLAB Simulink where the system reaches the steady-state in 0.005 s and gives a DC–DC conversion efficiency of 99.85% at the peak solar irradiation level. The AC stage steady-state error is minimized to 0 V whereas, THD is limited to 0.07% and 0.11% for linear and non-linear loads, respectively.

Motion Control of Autonomous Underwater Vehicle Based on Fractional Calculus Active Disturbance Rejection

An active disturbance rejection control based on fractional calculus is proposed to improve the motion performance and robustness of autonomous underwater vehicle (AUV). The active disturbance rejection control (ADRC) method can estimate and compensate the total disturbance of AUV automatically. The fractional-order PID (proportional integral derivative) has fast dynamic response, which can eliminate the estimation error of extended state observer. The fractional calculus active disturbance rejection strategy combines the advantages of the above two algorithms, and it is designed for AUV heading and pitch subsystems. In addition, the stability of fractional calculus ADRC heading subsystem is proven by Lyapunov stability theorem. The numerical simulations and experimental results document that the superior performance has been achieved. The fractional calculus ADRC strategy has more excellent abilities for disturbance rejection, performs better than ADRC and PID, and has important theoretical and practical value.

Finite-Set Model Predictive Current Control of Induction Motors by Direct Use of Total Disturbance

Disturbance rejection strategies are very useful for the robustness improvement of the predictive control method. But they can only be used in the modulated-based predictive control methods such as continuous set model predictive control (CS-MPC) and deadbeat control. This paper presents a robust current prediction model based on total disturbance observer (TDO), which is applicable in the finite set model predictive current control (FS-MPCC). In the proposed method, the disturbance is directly used as a part of the prediction model instead of the disturbance rejection loop. So, the proposed method has two advantages over the disturbance rejection-based CS-MPC schemes. The first advantage is no need for a controller, which is an essential part of the disturbance rejection-based CS-MPC. Therefore, the proposed method is simpler and has fewer control parameters. The second feature is that the proposed model is in the stationary frame. In this way, the frame transformation is avoided in the prediction model. Moreover, to guarantee zero steady-state error in the current prediction model, this paper proposes a complete designing process for TDO based on the convergence analysis. The performance of the proposed control system is evaluated through simulations and experimental tests.

Line-of-sight stabilization of roll-pitch seeker using differentiator-based disturbance compensation control

A new control problem of roll-pitch seeker about the disturbance coupling is investigated in this work. Previous control strategies of roll-pitch seeker rarely considered the effects of the dynamic coupling disturbances from the missile angular motion, and because of the polar coordinate structure, the disturbance rejection strategies of yaw-pitch seeker cannot be utilized directly on roll-pitch seeker. Thus this article presents a new control strategy to improve the disturbance rejection ability of roll-pitch seeker. To analyze the disturbance coupling problem, the roll-pitch seeker model is derived with consideration of the missile body angular motion and torque disturbances. The motion equation of roll-pitch seeker shows that part of the dynamic coupling disturbance can be eliminated by certain choices of inertial parameters. The rest of disturbance is reduced by the stabilization loops using a differentiator-based disturbance compensation controller. Particularly, a missile body angular acceleration estimation method is designed for the compensator based on an adaptive differentiator. In addition, comparisons with other control strategies are carried out via numerical simulations, and the results confirm the effectiveness of the proposed method.

High-Accuracy Force Control With Nonlinear Feedforward Compensation for a Hydraulic Drive Unit

The hydraulic drive unit (HDU) applied in a hydraulic drive legged robot joints adopts an outer loop impedance control method based on the hydraulic control's inner loop during motion so that the entire system obtains certain compliance characteristics. There are two types of inner loops, namely, the position closed loop control and the force closed loop control; this paper studies a system in which the inner loop is a force closed loop control system and improves its accuracy in order to provide references for the outer loop impedance control. Therefore, designing a compensation method that improves the inner loop force control's accuracy has important research significance. In view of the above research significance, this paper first deduces a mathematical model for the force closed loop control and simplifies the sixth-order mathematical model to find the transfer function of each part. Second, combined with influence factors, such as pressure-flow nonlinearity, friction nonlinearity, and complex and variable loads on the system, the feedforward compensation controller of the force control input is derived. Considering the practical application in engineering, the controller order is reduced, and a partial compensation is achieved. Finally, on the HDU performance test platform, the force control performance is quantitatively analyzed by inputting typical signals and random signals. The experimental results show that the feedforward compensation controller can greatly improve the system force control performance with different input signals. The above research results can be combined with a corresponding disturbance rejection strategy for the force control system to provide an important reference and experimental basis for the hydraulic inner loop control strategy of force-based impedance.

Disturbance Rejection in Multi-DOF Local Magnetic Actuation for the Robotic Abdominal Surgery

The potential of multi-degrees-of-freedom (DOFs) local magnetic actuation (LMA) has been established in recent years for dexterous minimally invasive surgical manipulations. Nonetheless, having multiple magnetic based units, one for each DOF, within a close vicinity to each other leads to magnetic field interaction among the magnetic sources, hence, resulting in a disturbance to a given LMA unit. It is further realized that the disturbance is a result of actuation effort by the neighboring magnetic sources forming the LMA units, and that the actuation command to all LMA units is a known information to the controller. Therefore, partial information of the disturbance is known and can be exploited in a disturbance rejection strategy. In this letter, this disturbance is modeled and used to augment a simplified model of the systems dynamics of the LMA-based surgical manipulators. The internal model principle (IMP) strategy is selected in which an observer is designed to estimate the disturbance to be rejected. Numerical simulation as well as experimental validation were performed to validate the efficacy of the IMP. The results serve to remove a significant technical hurdle in bringing the new emerging technique of LMA into practical reality for abdominal surgeries.

Predictive sliding mode based cascade control for parametric uncertainty

In this paper, a predictive sliding mode control based cascade control strategy is proposed for improving system performance and to reduce the effect of uncertainty in model parameters such as varying time-delay and varying time constant of the system. The proposed structure has two controllers in the primary loop and one controller in the secondary loop. The disturbance rejection and delay compensation strategies are incorporated in the primary loop. The primary controller is designed with Smith predictor based sliding mode control to eliminate the effects of model parameter uncertainty, which occur due to modeling inaccuracies in identification of overall primary process model into first order plus dead-time model. The disturbance rejection control law is designed to reduce the effect of disturbances in steady state operating condition. The secondary controller is designed based on conventional sliding mode approach with first order sliding surface. A new control scheme has been proposed looking for superior performance and robustness improvement. Simulation example is given to illustrate the use of the proposed method and its superiority over some existing design methods.

Active disturbance rejection control based on weighed-moving-average-state-observer

In this work, we are concerned with the boundary stabilization of a one-dimensional anti-stable wave equation corrupted by a boundary disturbance. We firstly propose, by weighed moving average technique, a state observer to make an estimation of the disturbance. Secondly, we design a control by the active disturbance rejection strategy to stabilize the system.

Modeling and Control of Heave-Induced Pressure Fluctuations in Managed Pressure Drilling

Automatic managed pressure drilling is an advanced pressure-control method which is intended to meet the increasingly high demands in drilling operations in the oil and gas industry. In this method, the circulating drilling fluid, which takes the cuttings out of the well, is released at the surface through a controlled choke. This choke is used for active control of the fluid pressure in the well. The corresponding automatic control system keeps the pressure at the bottom of the well at a specified setpoint despite various disturbances. One such disturbance, i.e., the vertical motion of the drill string, causes severe pressure fluctuations which need to be actively attenuated. In this paper, we present two different disturbance rejection strategies based on discretized partial differential equations for the well hydraulic system. The performance of the controllers is shown through simulations both under idealized conditions and on a high-fidelity drilling simulator.

A Disturbance Rejection Strategy for Asynchronous Motor of the Electric Vehicle in Speed-Open-Loop Operating Mode

For any electric vehicle on the road, it is inevitable to be influenced by parameter uncertainties and some kinds of disturbance torques, which present challenge for the controller design in the electric vehicle. Therefore, control of the electric vehicle to achieve the safety running requirement becomes important. In this paper, we investigate the control method for electric drive system of the electric vehicle from both theoretical and applied perspectives, then, speed loop inverse based disturbance rejection control strategy is proposed. The proposed approach is illustrated by implementing it into an experimental platform. The experimental results demonstrated that the proposed control method can achieve rapid response to current variation at operating frequency of electric vehicle, and substantially suppress the adverse effect of current variation at high frequency.

Disturbance rejection control based on acceleration projection method for walking robots

This paper presents a disturbance rejection scheme for walking robots under unknown external forces and moments. The disturbance rejection strategy, which combines the inverse dynamics control with the acceleration projection onto the ZMP (zero moment point)-plane, can ensure the overall dynamic stability of the robot during tracking the pre-computed trajectories. Under normal conditions, i.e., the system is dynamically balanced, a primary inverse dynamics control is utilized. In the case that the system becomes unbalanced due to external disturbances, the acceleration projection control (APC) loop, will be activated to keep the dynamic stability of the walking robot through modifying the input torques. The preliminary experimental results on a robot leg demonstrate that the proposed method can actually make the robot keep a stable motion under unknown external perturbations.

Control of a III-V MOCVD process using ultraviolet absorption and ultrasonic concentration monitoring

Metalorganic chemical vapor deposition (MOCVD) is a key technology for the growth of compound semiconductors. This process has traditionally lacked real-time growth monitoring and control, which limits the precise reproducibility needed for high performance devices. Two complementary control approaches for the MOCVD process are investigated experimentally. The first one is a feedforward disturbance rejection strategy using ultrasonic concentration measurements to reject source gas bubbler disturbances. The second one is a feedback system using an ultraviolet absorption sensor for real-time monitoring of reaction chamber gas concentrations. Post-growth X-ray diffraction and photoluminescence of InP/GaInAs superlattice test devices are used to evaluate the control system performance.