Active Disturbance Rejection Approach Research Articles

Command-Filtered Backstepping Repetitive Control for a Class of Uncertain Nonlinear Systems Based on Additive State Decomposition

This paper presents a command-filtered backstepping repetitive control (RC) method for a class of uncertain nonlinear systems with multiple disturbances, which is based on additive state decomposition (ASD) technique and active disturbance rejection approach. First, the original nonlinear system is decomposed into a linear time-invariant (LTI) primary system with periodic inputs and a nonlinear secondary system with multiple, aperiodic disturbances. The original nonlinear tracking problem is accordingly decomposed into two subproblems: RC problem for an LTI periodic system and a robust stabilization problem for a nonlinear system. By making using of the known information of the model, a linear extended state observer is constructed to estimate the matched total disturbance together with the system states and then a command-filtered backstepping control law incorporating with the estimate of the equivalent input disturbance is developed for the secondary system that ensures the robust stability and compensates for the effects of the multiple disturbances and residual nonlinearity. Stability criterion for each subsystem is established. Moreover, a particle-swarm-optimization algorithm is adopted to simultaneously optimize the controller parameters of the system. Finally, simulations and comparative experiments demonstrate the validity and superiorities of this method.

An event-triggered active disturbance rejection approach to dual-hormonal artificial pancreas control

The home-use of a wearable artificial pancreas (AP) system requires an efficient and robust control algorithm. In this work, we propose a novel solution through an adaptive disturbance rejection approach. The controller features an observer that estimates the effect of improper clinical parameters and a feedback control law that builds on and compensates the estimated effect. Event-triggered data scheduling is designed for the state observer and the insulin-on-board estimate, to enable predictive control action for ascending and descending glucose traces. Besides, an event-triggered switching strategy is proposed to deliver insulin and glucagon separately. Glucose- and velocity-dependent parameter adaptation for the feedback control law are further introduced for each hormone infusion to address the asymmetric risks of hyperglycemia and hypoglycemia. The effectiveness and robustness of the controller are evaluated using the 10-adult cohort of the FDA-accepted UVA/Padova T1DM simulator. For scenarios with nominal basal rates and meal boluses, the proposed controller achieves satisfactory performance in terms of mean glucose and percent time in [70, 180] mg/dL without increasing the risk of hypoglycemia. The controller also behaves properly and safely with satisfactory performance for scenarios of moderate meal-bolus and basal rate mismatches. The results indicate the feasibility of achieving robust glucose regulation through an adaptive disturbance compensation approach for dual-hormonal AP systems.

Data-driven disturbance observer-based control: an active disturbance rejection approach

In this paper, a data-driven method for disturbance estimation and rejection is presented. The proposed approach is divided into two stages: an inner stabilization loop, to set the desired reference model, together with an outer loop for disturbance estimation and compensation. Inspired by the active disturbance rejection control framework, the exogenous and endogenous disturbances are lumped into a total disturbance signal. This signal is estimated using an on-line algorithm based on a data-driven predictor scheme, whose parameters are chosen to satisfy high robustness-performance criteria. The above process is presented as a novel enhancement to design a disturbance observer, which constitutes the main contribution of the paper. In addition, the control strategy is completely presented in discrete time, avoiding the use of discretization methods for its digital implementation. As a case study, the voltage control of a DC-DC synchronous buck converter affected by disturbances in the input voltage and the load is considered. Finally, experimental results that validate the proposed strategy and some comparisons with the classical disturbance observer-based control are presented.

Seizure control in a neural mass model by an active disturbance rejection approach

A closed-loop neuromodulation automatically adjusts stimuli according to brain response in real time. It is viewed as a promising way to control medically intractable epilepsy. A suitable closed-loop modulation strategy, which is robust enough to unknown nonlinearities, dynamics, and disturbances, is in great need in the clinic. For the specialization of epilepsy, the Jansen’s neural mass model is utilized to simulate the undesired high amplitudes epileptic activities, and active disturbance rejection control is designed to suppress the high amplitudes of epileptiform discharges. With the help of active disturbance rejection control, closed-loop roots of the system are far from the imaginary axis. Time domain response shows that active disturbance rejection control is able to control seizure no matter whether disturbances exist or not. At the same time, frequency domain response presents that enough stability margins and a broader range of tunable controller parameters can be obtained. Stable regions have also been presented to provide guidance to choose the parameters of active disturbance rejection control. Numerical results show that, compared with proportional-integral control, more accurate modulation with less energy can be achieved by active disturbance rejection control. It confirms that the active disturbance rejection control-based neuromodulation solution is able to achieve a desired performance. It is a promising closed-loop neuromodulation strategy in seizure control.

Water Pump Control: A Hybrid Data-Driven and Model-Assisted Active Disturbance Rejection Approach

Water pump control, prevalent in various industrial plants, such as wastewater treatment and steam generator facilities, plays a significant role in maintaining economic efficiency and stable plant operation. Due to its slow dynamics, strong nonlinearity, and various disturbances, it is also widely studied as a typical benchmark problem in process control. The current control strategies can be categorized into two aspects: one branch resorts to model-based design and the other to data-driven design. To merge the merits and overcome the deficiencies of each paradigm, this paper proposes a hybrid data-driven and model-assisted control strategy, namely modified active disturbance rejection control (MADRC). The model information regarding water dynamics is incorporated into an extended state observer (ESO), which is used to estimate and mitigate the limitations of slow dynamics, strong nonlinearity, and various disturbances by analyzing the real-time data. The tuning formula is given in terms of the desired closed-loop performance. It is shown that MADRC is able to produce a satisfactory control performance while maintaining a low sensitivity to the measurement noise under general parametric setting conditions. The simulation results verify the clear superiority of MADRC over the proportional-integral (PI) controller and the conventional ADRC, and the results also evidence its noise reduction effects. The experimental results agree well with the simulation results based on a water tank setup. The proposed MADRC approach is able to improve the control performance while reducing the actuator fluctuation. The results presented in this paper offer a promising methodology for the water control loops widely used in the water industry.

Linear active disturbance rejection control for a raceway photobioreactor

In this paper, the problem of pH regulation in photobioreactors has been addressed by using a robust Proportional–Integral controller in combination with a linear active disturbance rejection approach. This formulation is based on the Generalized Proportional–Integral (GPI) observers design to estimate online external disturbances and non-modeled dynamics. The methodology uses a model reference optimization procedure with tracking and regulatory target closed-loop transfer functions for first-order plus dead-time models. The proposed controller is validated on a full-scale Raceway photobioreactor, whose results show a significant improvement in the accuracy of pH regulation and, consequently, a positive influence on biomass production. Moreover, a classical feedforward approach has been used for comparison purposes. The performance of the robust technique is evaluated with different indexes, whose results confirm the good performance of the proposed active disturbance rejection control scheme.

Dynamic behavior investigations and disturbance rejection predictive control of solvent-based post-combustion CO2 capture process

Increasing demand for flexible operation has posed significant challenges to the control system design of solvent-based post-combustion CO2 capture (PCC) process: 1) the capture system itself has very slow dynamics; 2) in the case of wide range of operation, dynamic behavior of the PCC process will change significantly at different operating points; and 3) the frequent variation of upstream flue gas flowrate will bring in strong disturbances to the capture system. For these reasons, this paper provides a comprehensive study on the dynamic characteristics of the PCC process. The system dynamics under different CO2 capture rates, re-boiler temperatures, and flue gas flow rates are analyzed and compared through step-response tests. Based on the in-depth understanding of the system behavior, a disturbance rejection predictive controller (DRPC) is proposed for the PCC process. The predictive controller can track the desired CO2 capture rate quickly and smoothly in a wide operating range while tightly maintaining the re-boiler temperature around the optimal value. Active disturbance rejection approach is used in the predictive control design to improve the control property in the presence of dynamic variations or disturbances. The measured disturbances, such as the flue gas flow rate, is considered as an additional input in the predictive model development, so that accurate model prediction and timely control adjustment can be made once the disturbance is detected. For unmeasured disturbances, including model mismatches, plant behavior variations, etc., a disturbance observer is designed to estimate the value of disturbances. The estimated signal is then used as a compensation to the predictive control signal to remove the influence of disturbances. Simulations on a monoethanolamine (MEA) based PCC system developed on gCCS demonstrates the excellent effect of the proposed controller.

Seizure Control by a Learning Type Active Disturbance Rejection Approach

Epilepsy is one of the most common neurological disorders. Neuro-modulation becomes a promising way to address it. For an effective modulation, closed-loop mode is necessary but difficult. A control algorithm, which can adjust itself to get desired suppression of epileptic activity, is in great need. In this paper, active disturbance rejection control (ADRC) is utilized for its satisfied disturbance rejection and regulation performance. However, fixed observer parameters are difficult to fit the time-varying electrophysiological signals. Therefore, based on the estimation errors, an iterative learning approach is designed to get the parameters of an extended state observer (ESO). By combining the advantages of ADRC and the iterative learning, a learning type ADRC (LTADRC) is proposed to suppress the high amplitude epileptiform waves generated by the Jansen's neural mass model (NMM). For those variable parameters of an ESO, scalable bandwidths can be obtained to adapt to time-varying disturbance signals. It is of great significance for both ADRC and the neuro-modulation of epilepsy. Simulation results show that, compared with ADRC, much better performance can be obtained. It may provide a promising closed-loop regulation way for epilepsy in clinics.

An optimized active disturbance rejection approach to fan control in server

As more and more massive data storage drives are used in super high density, the power used to cool the servers has become an increasingly large component of the total power consumption. Therefore, improving server cooling efficiency has become an essential requirement in data centers. However, because the thermal dynamics of the server system has characteristics such as nonlinearity, significant inter-loop coupling, and continuously fast-changing/unknown workload disturbances, these pose huge challenges to control engineers and data center architect engineers. To address the above concerns, this paper presents an active disturbance rejection control based decoupling control algorithm for flash storage systems and CPUs in a one-unit (1U) server to simultaneously improve fan power consumption efficiency and regulate the server components’ temperature to avoid downgraded performance caused by overheating. In the study, a benchmark system is established based on the Samsung Mission Peak (MP) server where the thermal characteristics and existing solutions are both systematically evaluated. Performance of the design concept is proven in both simulation and a hardware testbed. With the proposed control solution, experiment results show that the temperature overshoot is greatly eliminated, temperatures are more tightly controlled, and the drive throttling rate are greatly decreased. Furthermore, the proposed method is shown to be able to save up to 45% energy versus a PID controller, save about 77% energy versus dynamic fan speed control method, and save about 98% energy versus native fan speed control.

Current sensorless finite-time control for buck converters with time-varying disturbances

DC–DC buck converters are widely adopted to feed power from renewable energy distributed generators into smart grids. Sliding mode control (SMC) schemes enable such converter systems to inject high-accuracy voltage and current into the connected devices or loads, which are of good robustness in dealing with matched disturbances and model uncertainties. However, the chattering phenomenon, caused by the discontinuous control law, leads to large ripples in output voltage and increases switching losses. Moreover, in current sensor failure cases, conventional state feedback control law is not available for higher control performance. In this research paper, a recursive design based universal finite-time observer (UFTO) is applied to reconstruct the current information and lumped disturbances simultaneously, which provides an active disturbance rejection approach. Then, a non-singular sliding mode control based current sensorless finite-time control strategy is developed for the converter system to improve the transmit behaviours, control accuracy, and fault tolerance ability in the presence of various time-varying disturbances. As compared with traditional PID and existing asymptotical current sensorless approaches, both finite-time convergence property of voltage tracking error and active suppression ability against time-varying disturbances are obtained. A rigorous analysis on robustness stability has been provided for the proposed current sensorless finite-time control method. Experimental results are explored to comprehensively illustrate the feasibility and effectiveness of the proposed strategy.

Spatial observer-based repetitive controller: An active disturbance rejection approach

Linear Repetitive Control has proven to be an effective strategy to compensate for periodic disturbances in mechatronic systems that operate at constant speed; however, it renders very poor performance in varying speed applications. In this work, a Repetitive Controller based on a Generalized Proportional Integral (GPI) observer under Active Disturbance Rejection approach is presented and formulated in spatial domain. The inclusion of the linear GPI observer makes possible to see the spatial non-linear system as a simplified linear one by means of an on-line estimated unified disturbance term. Experimental results show that the presented linear approach successfully rejects periodic disturbances under varying speed conditions.

Generalized proportional integral control for periodic signals under active disturbance rejection approach

Conventional repetitive control has proven to be an effective strategy to reject/track periodic signals with constant frequency; however, it shows poor performance in varying frequency applications. This paper proposes an active disturbance rejection methodology applied to a large class of uncertain flat systems for the tracking and rejection of periodic signals, in which the possibilities of the generalized proportional integral (GPI) observer-based control to address repetitive control problems are studied. In the proposed scheme, model uncertainties and external disturbances are lumped together in a general additive disturbance input that is estimated and rejected on-line. An illustrative case study of mechatronic nature is considered. Experimental results show that the proposed GPI observer-based control successfully rejects periodic disturbances even under varying speed conditions.

Maximización de captura de energía en turbinas eólicas de velocidad variable usando control proporcional integral generalizado

This paper proposes an alternative linear control technique to maximize the energy capture in a horizontal-axis wind turbine. The proposed strategy is based on Generalized Proportional Integral (GPI) controllers supported by the active disturbance rejection approach, which allows asymptotic tracking of a rotor speed reference trajectory without exact wind turbine model knowledge. The proposed methodology controls the tip-speed ratio, via the rotor angular speed, to an optimum point at which power coefficient is maximum. Several simulations are performed on a 4.8MW wind turbine benchmark model in order to validate the proposed control strategy and to compare it to a classical controller. The simulation results show that the proposed control strategies are effective in terms of power capture and robustness.

Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywheel is activated to counteract the fault effect and ensure that the satellite is working safely and reliably. The active disturbance rejection approach is employed to design the controller, which handles input information with tracking differentiator, estimates system uncertainties with extended state observer, and generates control variables by state feedback and compensation. The designed active disturbance rejection controller is robust to both internal dynamics and external disturbances. The bandwidth parameter of extended state observer is optimized by the artificial bee colony algorithm so as to improve the performance of attitude control system. A series of simulation experiment results demonstrate the performance superiorities of the proposed robust fault-tolerant control algorithm.

An Active Disturbance Rejection Approach to Leader‐Follower Controlled Formation

AbstractThis article describes the design of a linearizing, observer‐based, robust dynamic feedback control scheme for output reference trajectory tracking tasks in a leader‐follower non‐holonomic car formation problem. The approach is based on the cars' kinematic models. A radical simplification in the form of a global ultra‐model is proposed on the follower's exact open loop position tracking error dynamics obtained via flatness considerations. This results in a system described by an additively disturbed set of two, second order integrators with non‐linear velocity dependent control input gain matrix. The unknown additive disturbances are modeled as absolutely uniformly bounded time signals which may be locally approximated by arbitrary elements of a sufficiently high degree family of Taylor polynomials. Linear high‐gain Luenberger observers of the generalized proportional integral (GPI) type may be readily designed. These observers include the self updating internal model of the unknown disturbance input vector components in the form of generic, instantaneous, time‐polynomial models. The proposed (GPI) observers, which are the dual counterpart of GPI controllers [17], achieve a simultaneous disturbance estimation and tracking error phase variables estimation. This on‐line gathered information is used to advantage on the follower's feedback controller thus allowing for a simple, yet efficient, disturbance and control input gain cancelation effort. The results are applied to have the follower track a time‐delayed version of the actual leader's trajectory. Experimental results are presented which illustrate the robustness and viability of the proposed approach.

Robust Active Disturbance Rejection Control Approach to Maximize Energy Capture in Variable-Speed Wind Turbines

This paper proposes an alternative robust observer-based linear control technique to maximize energy capture in a 4.8 MW horizontal-axis variable-speed wind turbine. The proposed strategy uses a generalized proportional integral (GPI) observer to reconstruct the aerodynamic torque in order to obtain a generator speed optimal trajectory. Then, a robust GPI observer-based controller supported by an active disturbance rejection (ADR) approach allows asymptotic tracking of the generator speed optimal trajectory. The proposed methodology controls the power coefficient, via the generator angular speed, towards an optimum point at which power coefficient is maximum. Several simulations (including an actuator fault) are performed on a 4.8 MW wind turbine benchmark model in order to validate the proposed control strategy and to compare it to a classical controller. Simulation and validation results show that the proposed control strategy is effective in terms of power capture and robustness.

Active Disturbance Rejection Approach for Robust Fault-Tolerant Control via Observer Assisted Sliding Mode Control

This work proposes an active disturbance rejection approach for the establishment of a sliding mode control strategy in fault-tolerant operations. The core of the proposed active disturbance rejection assistance is a Generalized Proportional Integral (GPI) observer which is in charge of the active estimation of lumped nonlinear endogenous and exogenous disturbance inputs related to the creation of local sliding regimes with limited control authority. Possibilities are explored for the GPI observer assisted sliding mode control in fault-tolerant schemes. Convincing improvements are presented with respect to classical sliding mode control strategies. As a collateral advantage, the observer-based control architecture offers the possibility of chattering reduction given that a significant part of the control signal is of the continuous type. The case study considers a classical DC motor control affected by actuator faults, parametric failures, and perturbations. Experimental results and comparisons with other established sliding mode controller design methodologies, which validate the proposed approach, are provided.

Robust Passivity-Based Control of a Buck–Boost-Converter/DC-Motor System: An Active Disturbance Rejection Approach

This paper presents an active disturbance rejection (ADR) approach for the control of a buck-boost-converter feeding a dc motor. The presence of arbitrary, time-varying, load torque inputs on the dc motor and the lack of direct measurability of the motor's angular velocity variable prompts a generalized proportional integral (GPI) observer-based ADR controller which is synthesized on the basis of passivity considerations. The GPI observer simultaneously estimates the angular velocity and the exogenous disturbance torque input in an on-line cancellation scheme, known as the ADR control. The proposed control scheme is thus a sensorless one with robustness features added to the traditional energy shaping plus damping injection methodology. The discrete switching control realization of the designed continuous feedback control law is accomplished by means of a traditional PWM-modulation scheme. Additionally, an input to state stability property of the closed-loop system is established. Experimental and simulation results are provided.