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This paper presents the equivalence between generalized proportional integral observer (GPIO) and disturbance observer (DOB), which is applicable to reduced-order GPIO (ROGPIO), full-order GPIO (FOGPIO), and extended state observer (ESO). From this equivalence, established in frequency-domain, comprehensive analyses are performed regarding the influence of the system order, the number of extended states, the uncertain control gain, and the tuning method on the robustness and performance of GPIO. In addition, the equivalence allows a detailed comparison between ROGPIO and FOGPIO in the active disturbance rejection control (ADRC) framework. Finally, experimental validation of the main results is presented for the study case of a synchronous buck converter.

This paper explored different alternatives for fault diagnosis based on algebraic identification methods. As a novelty, the use of Extended State Observers (ESO) is proposed to estimate time-derivatives related to nonlinear complex terms, which have a difficult analytical handling from the perspective of the classic algebraic framework. In this context, three fault diagnosis schemes focused on residual generation, fault identification and parameter estimation are presented and compared. These strategies estimate as few parameters as possible, making their implementation simpler. To validate the proposed approach, a twin-rotor aerodynamic system affected by multiple, intermittent and simultaneous actuator faults was considered as case study. Finally, experimental results that show the effectiveness and robustness of the proposed strategies are provided.

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.

An adaptation of the active disturbance rejection control (ADRC) approach is applied to a fractional-order system with a flat output. Albeit the rather scarce information about the system, the conditions to establish an ultimate bound for a specific configuration of the system are found and compiled in a guideline for the tuning of the observer implemented in the ADRC.

This paper presents an adaptation of the Active Disturbance Rejection Control (ADRC) method within the fractional calculus context. This ADRC version is characterized by a single active cancellation of the lumped effects of all the unmodeled dynamics, external disturbances and parameter uncertainty associated with the linear model of commensurate fractional order. This methodology proposes suitable simplifications to fit the resulting system to one of appropriate commensurate fractional order. The design is reduced to a linear observer-based control of fractional order that estimates the unified disturbance. A numerical stability analysis is presented to quantify the tracking and estimate errors bounds and provide guidelines in the parameters of observer-based controller configuration. The proposed control strategy is experimentally validated in linear and nonlinear cases of fractional order by means of approximate analog implementations.

Wind turbines are complex mechatronic systems subject to different kinds of disturbances. Among all disturbance sources, those from periodic nature are the most relevant and important for maintaining the structural health of the entire wind turbine. However, periodic disturbances in wind turbines, mainly given by wind shear, tower shadow and rotational sampling of turbulence, have a variable fundamental frequency that changes as function of the turbine angular speed. In consequence, conventional controllers have issues to mitigate such varying-frequency periodic loads. This paper proposes two individual pitch control schemes to attenuate the main periodic load components of blade flap-wise and hub yaw/tilt-wise bending moments in horizontal-axis wind turbines under varying-frequency conditions. Both proposals are founded on the paradigm of Active Disturbance Rejection Control (ADRC): the former is formulated in the time-domain using a Linear-Time-Invariant (LTI) standard controller, while the latter is designed in the angular position domain using a Linear-Position-Invariant (LPI) approach. Several realistic simulations with different wind turbulence intensities and average wind speeds are performed using a 5 MW three-bladed horizontal-axis wind turbine implemented in the FAST code by NREL. Simulation results of the proposed control schemes show improved load reductions compared with other control techniques.

This paper explores the techniques based on Generalized Proportional Integral Observers (GPI), under the approach of active disturbance rejection, applied to the control of multivariable nonlinear systems with the same number of inputs and outputs (square). As a central axis, a sliding mode control scheme assisted by GPI observers is proposed. These observers are responsible for estimating the disturbances associated with the dynamics of the sliding surfaces produced by non-linearities, not modeled elements, parameter uncertainty and external disturbances. This process allows the creation of sliding regimes under the point of view of decoupled control. As a case study, the position control of a small-scale 2-DOF helicopter affected by adverse operating conditions, such as unknown external disturbances and actuator faults, is considered. Finally, experimental results that validate the proposed control strategy and a comparison with a linear GPI observer-based active disturbance rejection control scheme are presented.

This paper presents a robust compound control strategy to produce a stable gait in dynamic bipedal robots under random perturbations. The proposed control strategy consists of two interactive loops: an adaptive trajectory generator and a robust trajectory tracking controller. The adaptive trajectory generator produces references for the robot controlled joints without a-priori knowledge of the terrain features and minimizes the effects of disturbances and model uncertainties during the gait, particularly during the support-leg exchange. The trajectory tracking controller is a non-switching robust multivariable generalized proportional integral (GPI) controller. The GPI controller rejects external disturbances and uncertainties faced by the robot during the swing walking phase. The proposed control strategy was evaluated on the numerical model of a five-link planar bipedal robot with one degree of under-actuation, four actuators, and point feet. The results showed robust performance and stability under external disturbances and model parameter uncertainties on uneven terrain with uphills and downhills. The stability of the gait was proven through the computation of a Poincare return map for a hybrid zero dynamics with uncertainties (HZDU) model, which shows convergence to a bounded neighborhood of a nominal orbital periodic behavior.

Microalgae have been explored as a promising alternative energy source over the last few years, and several control strategies have been developed to maintain their operational conditions. However, these bioprocesses still pose difficult challenges, due to the nonlinearity and uncertainties of microalgal dynamics. This paper addresses the problem of biomass regulation in a continuous culture of the microalga Dunaliella tertiolecta. Our strategy is based on a Proportional-Integral (PI) controller assisted by a Generalized Proportional Integral (GPI) observer, in order to mitigate the impact of disturbances on biomass levels. The proposed design was tested via numerical simulation, using MATLAB/Simulink™ 2020a environment. The robustness of the controller was demonstrated by subjecting the simulated bioreactor to disturbances and changes in reference biomass densities. The proposed strategy effectively tracked the reference within an insignificant deviation ±0.5%. Furthermore, our proposal effectively rejected disturbances that classical PI was unable to counter.

Microalgal cultures are developing into a promising ecofriendly technology for a host of applications. In this paper we investigate the response of the biomass (XSS), computed from a photo-bioreactor (PBR) algal growth numerical model, to its nine input variables. We explored this response using a Monte Carlo (MC) sensitivity analysis (SA) and Spearman’s Rho concordance coefficient method (MC-Rho). The model represented a continuous culture of the green microalgae Chlorella vulgaris. The photo-bioreactor was simulated using MATLAB as a steady state operation. Four important control variables were selected to represent different states of operation: dilution rate (D), incident light intensity (Im), hydrogen ion potential (pH), and partial pressure of CO2 \( (P_{{CO_{2} }} ) \). For each test point, a statistical array of values was generated of all the input variables with a 2% relative standard deviation. The output values were computed using the model, and then correlated with the input values. The model output turned out to be very sensitive to the four input variables that directly affect the carbon uptake and retention: dilution rate (D), partial pressure of CO2 \( (P_{{CO_{2} }} ) \), mass conversion yield (Yr), and gas-liquid mass transfer coefficient (kLa), in that order. The magnitude of the output relative standard deviation decreased as the output biomass (XSS) increased. However, the ratio of the output standard deviation to the input standard deviation was strongly non-linear and essentially unpredictable outside of a MC simulation.

This paper presents a disturbance rejection control strategy for hybrid dynamic systems exposed to model uncertainties and external disturbances. The focus of this work is the gait control of dynamic bipedal robots. The proposed control strategy integrates continuous and discrete control actions. The continuous control action uses a novel model-based active disturbance rejection control (ADRC) approach to track gait trajectory references. The discrete control action resets the gait trajectory references after the impact produced by the robot’s support-leg exchange to maintain a zero tracking error. A Poincare return map is used to search asymptotic stable periodic orbits in an extended hybrid zero dynamics (EHZD). The EHZD reflects a lower-dimensional representation of the full hybrid dynamics with uncertainties and disturbances. A physical bipedal robot testbed, referred to as Saurian, is fabricated for validation purposes. Numerical simulation and physical experiments show the robustness of the proposed control strategy against external disturbances and model uncertainties that affect both the swing motion phase and the support-leg exchange.

Microalgae are used for the industrial production of high value compounds. The aim in continuous bioreactors is to obtain the highest biomass production. It is necessary to guarantee that the bioprocesses attain and maintain the optimal reference biomass CX*(t), despite endogenous and exogenous disturbances. This paper describes the numerical simulation of the application of active disturbance rejection control (ADRC) to control the dilution rate (D(t)) in a continuous culture of the microalga Chlorella vulgaris. To reduce the bioprocess to a “SISO” system, the authors chose the dilution rate, D(t), to be the only control signal. The control proposal was illustrated and evaluated through a numerical simulation using MATLAB/Simulink™ environment. The performance of the ADRC was tested by the application of external perturbations and variation of parameters over a nominal case. At nominal conditions, D(t) was always maintained within the physical limits imposed by the bioprocess. Step and smooth type signals, at 96.4%·|Dmax(t)|, were imposed as external perturbation on the control signal input, D(t). The controller response kept the output signal CX(t) within an insignificant 0.0043%·|CXmax(t)|. The algal culture had a strongly asymmetric response to variations of the ideal maximum growth rate, μmax(t) ± 30%·|μmax(t)|, and of the nominal light intensity, Iin(t) ± 30%·|Iin(t)|. Nonetheless, the controller promptly returned the output signal to its reference value, CX(t)*. The numerical test of the control proposal, in summary, showed that the ADRC strategy ensures excellent reference tracking capability and robustness towards parametric uncertainties, un-modeled dynamics, and external disturbances.

This article presents the development of a strategy to enhance the Low-Voltage Ride-Through capability (LVRT) of Doubly Fed Induction Generator (DFIG)-based Wind Turbines (WTs). The developed control scheme proposes a trajectory generation system and a high-performance rotor current controller. First, the rotor current trajectories are obtained according to the grid codes requirements. These codes introduce suitable values for the electromagnetic torque and the active and reactive power during operation in normal and fault modes. A detailed analysis of controllability and stability aims to find out how to pair the control inputs and the controlled outputs according to the suggested operation conditions. As a result, a comprehensive study of the required rotor current trajectories to enhance the LVRT capability is developed. Second, the design of the rotor current controller is based on Active Disturbance Rejection Control (ADRC) approach. This controller accomplishes two main objectives: (1) it guarantees a robust tracking of the proposed trajectories, despite uncertainties, disturbances and symmetrical and asymmetrical faults in the grid; and (2) it keeps the rotor voltages and currents in their allowed ratings. Finally, the proposed scheme and the theoretical analysis are validated with simulation studies and laboratory tests.

In this work we propose a two-stage observer-based feedback control approach to automatically stabilizing a riderless bicycle in its upright position when moving forward at a constant speed. Our strategy uses a modern control approach called Active Disturbance Rejection Control (ADRC), based on Generalized Proportional Integral (GPI) extended observers, to estimate a unified signal that groups all the discrepancies between an adopted linear model and the actual behavior of the plant. These estimations are used in the feedback controller as an additive, close cancellation and terms devising proper output feedback control laws that linearly regulate the lean angle with respect to its upright position. From a control-design perspective, the bicycle is a perturbed, uncertain system with an unstable and non-linear behavior that is strongly forward speed dependent. The ADRC scheme allows one to solve this problem easily by using a control strategy based on an acceptable mathematical model derived from lumped-parameter analysis, and its effectiveness has been validated by the successful results from real implementation experiments on an instrumented bicycle prototype. A detailed description of all the stages of the mechatronics process design is included for a proper reference.

This paper proposes a method to find an optimal decision curve to manage the incident light intensity ( q 0 ) that is applied to microalgae cultivation to maximize biomass concentration ( C X ) . Microalgae are characterized by the production of high value compounds of interest to industry; the challenge is to obtain the highest biomass concentration. Optimization of the performance of microalgae culture systems is important to guarantee the viability of the economical process. The advantages of this optimization proposal are to attain to CX maximum productivities, as well as its simplicity and its robustness against perturbations. The optimization proposal is illustrated and evaluated on a numerical simulation in a batch culture of microalga Chlamydomonas reinhardtii. Additionally, it was compared to a conventional constant light operation and with an optimization approach based on finding the ratio between q0 and CX (light-to-microalga ratio). In the analysis, the performance of the optimal decision curve was contemplated in presence of the perturbations and variation of parameters. The simulations of proposal in this paper shows an optimal behavior in terms of a maximum production CX · In addition, this would have a better behavior in front of robustness and disturbance rejection capabilities, compared to both, constant light operation and light-to-microalga ratio.

This paper proposes a feedback method for the control of uncertain systems with unknown external disturbances, which includes an algebraic estimator and relies on the Active Disturbance Rejection Control (ADRC) approach. The proposed estimator considers a generalized disturbance in order to deal with systems which may simultaneously present time varying parameters, external disturbances, un-modeled dynamics, and process noise. The on-line estimated disturbance is obtained by means of differential algebraic methods and it is used as the major part of an on-line feedback cancellation scheme aiming at linearization and uncertainty suppression. The algebraic estimator proposed in the paper makes unnecessary the use of classical extended state observers, which are widely used in ADRC. The speed of response and reliability of the proposed algebraic disturbance estimator-based control scheme was experimentally tested on three laboratory systems, including a system of directly-coupled DC motors, a roto-magnet system, and a disc and beam system, showing that the experimental results are in excellent agreement with the predictions of the theory.

This paper introduces a nonlinear disturbance observer for hybrid dynamical systems with continuous and discrete dynamics. The hybrid dynamical system considered in this work is a bipedal robot. The robot is modeled by a continuous mathematical model connected to a discrete reset functions. The continuous and discrete dynamics are exposed to model parameter uncertainties and external disturbances. The uncertainties and disturbances in the continuous dynamics are lumped into a total disturbance signal, which is estimated through a nonlinear extended state observer (NESO). The disturbance estimation is used to design an active disturbance rejection control (ADRC). To address the reset function uncertainties on the discrete dynamics, a reference trajectory generator is designed to achieve zero tracking error after each reset function using a smooth transition function from the system state to the nominal references. The control strategy proposed in this work is applied to the gait control of a planar, dynamic bipedal robot with point feet, five degrees of freedom, and one degree of underactuation. The gait stability is tested through a linearized Poincare return map.

This document presents an application of Active Disturbance Rejection Control (ADRC) in a secondary frequency regulation problem with an active participation of renewable photovoltaic and wind generators. This problem is known as Load Frequency Control (LFC). The ADRC technique uses a reduced set of information of the model by grouping the effects of non-modeled dynamics, exogenous disturbances, and parameter uncertainties into a generalized equivalent disturbance, which in this case is estimated by an Extended-State Observer. This makes it possible to design a decentralized controller that achieves the bifold control objective of a secondary LFC strategy in each area. The proposed controller is able to regulate the frequency of each area and the tie-line power exchanges in presence of several load disturbances. The simulation scenarios validate the control proposal and show the flexibility and advantages of the application of ADRC-based control techniques as decentralized solutions to an LFC problem.

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.

[ES] Se introducen los ultra-modelos como un paradigma para la simplificación substancial del diseño de leyes de control por realimentación de salida, basadas en observadores, para el seguimiento de trayectorias en una amplia clase de sistemas planos inciertos. Un ultramodelo simplemente agrega, en la forma de una perturbación desconocida variante en el tiempo, los efectos combinados de todas las no-linealidades dependientes del estado (endógenas) aśı como también todas aquellas perturbaciones externas (exógenas) presentes en el modelo de entrada-salida plana del sistema. Como resultado, el diseño de un controlador basado en el ultramodelo global solo requiere del conocimiento de 1) los órdenes de Kronecker del sistema y 2) la matriz de funciones de ganancias de la entrada. Se propone un esquema de control basado en un observador extendido de alta ganancia para el Control por Rechazo Activo de Perturbaciones en sistemas no lineales diferencialmente planos. Se incluye un ejemplo ilustrativo, con simulaciones reaĺısticas consistente en el control de un motor śıncrono de imanes permanentes., [EN] Global ultra-models are introduced as a paradigm for vastly simplifying the design of observer-based linear output feedback control laws in output trajectory tracking problems for a large class of uncertain nonlinear flat systems. An ultra-model simply lumps, as an unknown time-varying disturbance, the combined effects of all uncertain state-dependent (i.e., endogenous) nonlinearities as well as those of external (i.e., exogenous) perturbation inputs present in the input-to-flat output model of the system. As a result, a global ultra-model based controller design only requires knowledge of the system order and of the nonlinear control input gain function. An extended high gain observer based control scheme is proposed for linear Active Disturbance Rejection (ADRC) for nonlinear differentially flat systems. An Illustrative case study example is presented.

A discrete time, on-line approach is proposed for the simultaneous identification of the frequency, the amplitude and the phase parameters in continuous noisy sinusoidal signals. The proposed technique takes the exact discretization of a continuous sinusoidal signal and generates exact computation formulas for the frequency, bias, amplitude and phase parameters, calculated in terms of quotients involving functions of the output and of some of its delayed values. The formula yields exact parameter calculations in the noiseless case, and it can be synthesized by means of time-varying filters whose outputs are obtained on-line. When the treated signal is affected by additive noises, a least squares-based “invariant filtering” is proposed, resulting in an enhancement of the signal to noise ratio of the factors conforming the basic algorithm. The scheme is proven and analysed by means of a laboratory experiment, a noise analysis and a comparison against other existing methods, where the proposed method shows accurate results with fast convergence rates.

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.

Correction to: Multibody Syst Dyn (2019) 45:7–35 In the original publication the affiliation of author John Cortes-Romero was given in its translated form (National University of Colombia). It is a legal requirement of this university that its name be given in the original Spanish in publications (Universidad Nacional de Colombia) and this correction article is published to amend this.

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.

An input–output based feedback controller is proposed for the sliding mode control of a large class of switched systems. The method avoids state measurements, or the use of observers, and it extends the sliding mode control design methodology to input–output descriptions of the plant. The approach regards the average Generalized Proportional Integral (GPI) output feedback controller as a guide for defining the switched implementation of the average sliding mode features via a Sigma–Delta modulation strategy. The considerations are circumscribed to the class of differentially flat systems. Experimental results are presented for a trajectory tracking problem on a DC-to-DC switched power supply of the “buck” type with unknown loads subject to abrupt variations.

[ES] Este trabajo propone una estrategia de Control por Rechazo Activo de Perturbaciones (ADRC), usando observadores extendidos de perturbación, para estabilizar una bicicleta en movimiento, sin conductor y con una velocidad de avance variable. Aunque la bicicleta tiene una dinámica inestable y no lineal alrededor de su posición vertical, que puede modelarse como un sistema Lineal de Parámetros Variantes (LPV) dependientes de la velocidad, el diseño del controlador usa un modelo simplificado de parámetros concentrados invariantes en el tiempo y una velocidad nominal constante. El esquema ADRC agrupa las discrepancias entre el modelo simplificado y la planta, junto con las perturbaciones externas en una señal aditiva unificada, que es estimada a través del observador y realimentada mediante una ley de control lineal para rechazarla. La efectividad de la estrategia es validada mediante una co-simulación entre ADAMS y MATLAB, la cual exhibe un alto desempeño y robustez sobre un modelo dinámico virtual de la bicicleta, sometida a perturbaciones externas severas y variaciones de parámetros., [EN] This work proposes an ADRC (Active Disturbance Rejection Control) strategy by disturbance extended observers to stabilize a moving riderless bicycle with a variant forward speed. Although the bicycle has an unstable and non-linear dynamics when in its upright position, which can be modeled as a LPV (Linear-Parameter-Varying) system that depends on the forward speed, a simplified time-invariant and lumped-parameter model, with an nominal constant forward speed is used in the controller design. ADRC scheme groups discrepancies between the simplified model and the plant, with external disturbances into an equivalent additive unified disturbance signal at input, which is estimated via the observer and rejected through a linear control law. The effectiveness of this strategy is validated by a co-simulation between ADAMS and MATLAB, which exhibits a high performance and robustness in a virtual dynamic model of the bicycle, submitted to severe external disturbances and parameter variations.

The problem of active disturbance rejection control of induction motors is tackled by means of a generalized PI observer based discrete-time control, using the delta operator approach as the methodology of analyzing the sampled time process. In this scheme, model uncertainties and external disturbances are included in a general additive disturbance input which is to be online estimated and subsequently rejected via the controller actions. The observer carries out the disturbance estimation, thus reducing the complexity of the controller design. The controller efficiency is tested via some experimental results, performing a trajectory tracking task under load variations.

In this arcicle, a linear observer-linear controller approach is proposed for the robust trajectory tracking task in a large class of nonlinear differentially flat systems, including multi-variable nonlinear flat systems. A non-phenomenological model of the input-to-flat-output dynamics is proposed which only retains the orders of the Kronecker integration subsystems and, the control input gain matrix, as key controller design elements. The additive influence of the rest of the nonlinear state dependent dynamics, including exogenous unknown perturbation inputs, is considered as unknown but uniformly absolutely bounded disturbance that is shown to be algebraically observable and it can, hence, be approximately determined, to any desired degree of accuracy, by means of a set of linear observers with suitable, self-updating, time-polynomial internal models of the unknown disturbances. The controller design task is reduced to that of canceling the additive disturbances while imposing a desired linear dynamics, via estimated state feedback, obtained from the proposed observer itself. A convincing simulation example dealing with rather complex nonlinear physical system is provided. Two experimental implementations on laboratory prototype systems are also reported.

In this article, an output feedback discrete time sigma delta-modulation based sliding mode controller is proposed for the stabilization and trajectory tracking of output voltages in a Buck power converter model. The average dynamic output feedback control scheme is realized by a means of a generalized proportional integral (GPI) controller.

A digital signal processing approach to estimate and reject disturbances under an active disturbance rejection control (ADRC) methodology is presented. In this paper a technique to assess the current values of the disturbance based on the previous input and output signals is developed. The on-line disturbance estimation is made through the use of a polynomial least squares regression. An excess in the number of data over the order of the polynomial regression is proposed in order to obtain a low pass filter. This estimation allows to simplify the control design in to a linear one. Corresponding performance, stability and robustness are analyzed. The propose approach is tested via numerical simulation in a trajectory tracking task under perturbed linear and nonlinear differentially flat systems. The simulations showed that the technique presented to estimate disturbances is successful in its application to active disturbance rejection control on linear and nonlinear systems.

This work proposes an ADRC (Active Disturbance Rejection Control) for parallel robotic platform, namely the Stewart-Gough configuration. The platform is intended for CNC machining processes where repeatability and accuracy requirements of the robot's motion are of utmost importance. The proposed approach makes use of linear high gain disturbance observation, where model uncertainties and external disturbances are lumped together into a general additive disturbance input that is estimated by Generalized Proportional Integral (GPI) observers and rejected on-line. The GPI control strategy replaces the more common PID controller in the joint control framework, and is used in order to better reject disturbances and non-linearities related with the robot configuration. Simulation results obtained by a co-simulation between Matlab and NX software, where the interaction dynamics and actuator non-linearities of the platform (i.e. saturation and headbands) were taking into account, closely approximate real robot operation and shows that the GPI observer-based linear control presents a better performance tracking trajectories compared with other control schemes, i.e. mixed sensitivity H∞ control.