Presence Of Parametric Uncertainties Research Articles

Adaptive sliding mode control with gravity compensation: Application to an upper-limb exoskeleton system

This paper presents a robust control algorithm with gravity compensation in presence of parametric uncertainties. The application deals with an upper limb exoskeleton system, aimed for a rehabilitation application. The treated system is an robot with two degrees of freedom acting on the flexion / extension movement of the shoulder and elbow. An adaptive sliding mode algorithm with gravity compensation has been developed to control the upper limb exoskeleton system. A Stability study is realized. Then, a robustness analysis in the presence of parametric uncertainties using Monte Carlo simulation is developed. To prove the performance of the gravity compensation approach, a comparison study is done. Simulation results are presented to highlight the performances and the effectiveness of the proposed controller using gravity compensation.

Nonlinear Robust Generalized Dynamic Inversion based Homing Guidance and Control of Aerial Interceptors

Abstract This paper presents the design of Robust Generalized Dynamic Inversion based Homing Guidance and Control (RGDI-HGC) methodology for highly maneuvering targets interceptors. In two-loops structured RGDI-HGC system, the outer RGDI based homing guidance loop generates the desired normal acceleration command to minimize the relative distance between the interceptor and the target. In the inner loop, RGDI based control law is engaged to follow the desired normal acceleration command while stabilizing the interceptor pitching rate dynamics. The proposed RGDI-HGC system is composed of the equivalent part and the robust part. The equivalent part is formulated by prescribing the dynamical constraints that encapsulate the interception kinematic and dynamic objectives, and the guidance and control variables are solved by inverting the constraint dynamics using dynamically scaled Moore-Penrose Generalized Inverse (MPGI). The robust part of the RGDI-HGC system is established by employing the discontinues term based on the theory of the sliding mode that will provide robustness against system nonlinearities, parametric variations, and external disturbances such that semi-global practically stable tracking performance is guaranteed. Numerical simulations are executed to illustrate the performance of the RGDI-HGC system for different interception scenarios. Additionally, the performance of RGDI-HGC system is compared with a guidance/control system that is made by replacing the outer guidance law by a conventional Augmented Proportional Navigation (APN) law. The test results illustrated that the proposed RGDI-HGC system supersedes the other by strongly accomplishing the hit-to-kill guidance interception requirements against agile target maneuvers in the presence of parametric uncertainties and measurement noise.

Fast terminal sliding mode tracking control of nonlinear uncertain mass–spring system with experimental verifications

In this article, a fast terminal sliding mode control technique is used for robust tracking control of a nonlinear uncertain mass–spring system in the existence of external perturbation. This system is considered as a benchmark problem in the flexible joint mechanisms. The joints flexibility in the robotic systems creates one of the most significant sources of parametric uncertainties. The theory of Lyapunov stability is used for the formulation of the proposed control method, and the presence of the sliding around the switching surface is satisfied in the finite time. Simulation results as well as the experimental verifications prove the efficiency and applicability of the suggested approach in the presence of parametric uncertainty, noise, and exterior disturbance.

Robust Ride Height Control for Active Air Suspension Systems With Multiple Unmodeled Dynamics and Parametric Uncertainties

This paper addresses the problem of ride height tracking for an electronically-controlled active air suspension (AAS) system in the presence of parametric uncertainties and unmodeled dynamics. A mathematical model of a quarter vehicle with AAS system is first built on the basis of thermodynamics to describe the dynamic characteristics. Then, by employing the backstepping technique, a novel height tracking controller is proposed in order to guarantee that (1) the ride height of a vehicle can converge on a neighborhood of the desired height, achieving global uniform ultimate boundedness (GUUB); (2) the controller is robust to the parametric uncertainties by designing parameter estimators and introducing some conservativeness in the control law to dominate the unmodeled dynamics. Moreover, a group of smooth projectors is used to ensure all estimates remain within predefined corresponding bounds. To validate the efficiency and performance of the proposed strategy, the simulation and experimental results are presented and analyzed, showing that the proposed control strategy is superior to the PID controller and the recently proposed hybrid model predictive controller.

H∞ Current Controller of WRIM Based Flywheel Storage System under Unbalanced Stator Voltage

Flywheel storage systems (FSSs) are commonly associated with wind farms to support them to provide services to the grid such as power smoothing, frequency control, and voltage control. Although FSSs are not concerned by the grid code requirements, their stability and availability under unbalanced stator voltages are very important to ensure both wind farm stability and supply quality. In this context, this paper proposes a robust H ∞ controller for wound rotor induction machine (WRIM) driven FSS under stator voltage unbalance. The controller purpose is to suppress rotor current oscillations resulting from the negative sequence as well as to guarantee the system robustness in the presence of parameter uncertainties. The robust controller design based on mixed-sensitivity H ∞ control that guarantees the robust stability (RS) and robust performance (RP) is presented in detail. The performance of the H ∞ controller has been evaluated with simulations in MATLAB/Simulink using simpower systems for both unbalanced stator voltage and parameter uncertainties.

An Implementation of Rotor Speed Observer for Sensorless Induction Motor Drive in Case of Machine Parameter Uncertainty

The paper describes observers using model reference adaptive system for sensorless induction motor drive with the pulse width modulator and the direct torque control under the circumstances of incorrect information of induction motor parameters. An approximation based on the definition of the Laplace transformation is used to obtain initial values of the parameters. These values are utilized to simulate sensorless control structures of the induction motor drive in Matlab-Simulink environment. Performance comparison of two typical observers is carried out at different speed areas and in presence of parameter uncertainty. A laboratory stand with the induction motor drive and load unit is set up to verify the properties of observers. Experimental results confirm the expected dynamic properties of selected observer.

Controller Design and Stability Analysis of Output Pressure Regulation in Electrohydrostatic Actuators

In this paper, a robust fixed-gain linear output pressure controller is designed for a double-rod electrohydrostatic actuator using quantitative feedback theory (QFT). First, the family of frequency responses of the system is identified by applying an advanced form of fast Fourier transform on the open-loop input–output experimental data. This approach results in realistic frequency responses of the system, which prevents the generation of unnecessary large QFT templates, and consequently contributes to the design of a low-order QFT controller. The designed controller provides desired transient responses, desired tracking bandwidth, robust stability, and disturbance rejection for the closed-loop system. Experimental results confirm the desired performance met by the QFT controller. Then, the nonlinear stability of the closed-loop system is analyzed considering the friction and leakage, and in the presence of parametric uncertainties. For this analysis, Takagi–Sugeno (T–S) fuzzy modeling and its stability theory are employed. The T–S fuzzy model is derived for the closed-loop system and the stability conditions are presented as linear matrix inequalities (LMIs). LMIs are found feasible and thus the stability of the closed-loop system is proven for a wide range of parametric uncertainties and in the presence of friction and leakages.

Iterative method for estimating the robust domains of attraction of non-linear systems: Application to cancer chemotherapy model with parametric uncertainties

In this paper, we present an iterative procedure method for estimating the robust domains of attraction of non-linear systems. This method is based on the approximation of the uncertain non-linear system with a parameters-dependent Convex Difference Inclusions (CDI) system and the classical iterative methods for linear systems, which are introduced in this paper. A robust one-step operator computing a sequence of convex sets is derived, and the polyhedral case is discussed. An algorithm summarizing the iterative procedure based on the robust one-step operator is given, which is the theoretical contribution of this paper. This method is applied to cancer chemotherapy model considering parametric uncertainties and it is shown that drastic reduction of the robust domain of attraction of the cancer chemotherapy model has happened and this is caused by the presence of parametric uncertainties. It is also proved that the aggressive chemotherapy is not the effective treatment for all the patients.

Robust lateral control of long-combination vehicles under moments of inertia and tyre cornering stiffness uncertainties

ABSTRACTA robust steering-based controller synthesis is presented for an A-double combination vehicle with a steerable dolly. The controller ensures robust stability and performance in the face of uncertainties in the cornering stiffness of the tyres and the moments of inertia of the semitrailers, which are treated as time-varying and time-invariant parameters respectively. A descriptor-type representation of the system is employed since a standard state-space model depends rationally on the moments of inertia. The controller synthesis is formulated as an -type static output feedback, which uses information from only one articulation angle. The driver steering input is also used by including a static feed-forward. The proposed synthesis method is based on linear matrix inequality (LMI) optimisation. The controller is verified based on the simulation results obtained from both (approximate) linear and (high-fidelity) nonlinear vehicle models. The results indicate significant improvement in the high-speed lateral performance of the A-double in the presence of parametric uncertainties.

Robust H∞ control for stability assessment in grid‐connected offshore wind and marine current hybrid system

The geographic suitability brings the offshore wind farm (OWF) and marine current farm (MCF) together with their aggregated power fed to grid simultaneously in most relevant energy harnessing infrastructures. However, stability assessment of the integrated system is a major concern due to the integration of stochastic and intermittent sources with parametric uncertainty. Bridge-type fault current limiter (BFCL) has consolidated their application for a suitable enhancement of stability margin for most modern supply systems. In this article, a detailed modelling of the integrated system is carried out in the presence of BFCL along with consideration of uncertainty as well. A robust H∞ controller design strategy for stability assessment of grid-connected OWF and MCF in the presence of parametric uncertainties is presented in this article. Linear matrix inequality (LMI) conditions are derived in the context of evaluating the robust controller gain with respect to desired robust stability margin. The efficacy of the controller design is compared with that of H∞ loop shaping and conventional P-I control through different case studies with simulation followed by real-time digital simulator (RTDS) validation.

Multi-Objective Pareto Robust Design of PID Controllers for Variable Compression Ratio Engines Using Genetic Algorithms

Modern automobile engines must satisfy the challenging and often conflicting goals of minimizing exhaust emissions, providing increased fuel economy and satisfying driver performance requirements over a wide range of operating conditions. An innovative mechanical design approach to achieve these goals has been the development of variable compression ratio (VCR) engines. A challenge with this new engine design is that the compression ratio has a direct influence on the output torque. This is a problem because the engine driver can feel it as a jerk in the movement. Therefore, in order to fully take the advantage of benefits of this engine design it is necessary to have some sort of torque control that can keep a constant torque regardless of changes in compression ratio. In this work a control-oriented engine model is developed to represent a variable compression ratio engine over a range of operating conditions. The model is validated with some available experimental data. Based on the mode, a robust PID controller is optimally designed to control the output torque for the step changes of compression ratio in the presence of parametric uncertainties.

Launch vehicle ascent flight attitude control using direct adaptive generalized dynamic inversion

This paper presents the attitude control design of satellite launch vehicle based on the direct adaptive generalized dynamic inversion approach. The proposed adaptive generalized dynamic inversion approach encompasses the equivalent and the adaptive control elements. The equivalent (continuous) control part of adaptive generalized dynamic inversion is based on the conventional generalized dynamic inversion approach that comprises two noninterfering control actions, i.e. the particular part and the auxiliary part. In the particular part, dynamical constraint is prescribed in the form of time differential equation, which is evaluated along the vehicle attitude trajectories that encapsulates the control objectives and is inverted by utilizing Moore Penrose Generalized Inverse (MPGI). The singularity problem is solved by augmenting a dynamic scaling factor in the involved MPGI. In the auxiliary part, the null control vector is designed using the proportionality gain matrix, constructed by employing the Lyapunov function that guarantees global closed-loop asymptotic stability of the angular body rate dynamics. The adaptive (discontinuous) control part of adaptive generalized dynamic inversion is based on the sliding mode control with adaptive modulation gain, that provides robustness against tracking performance deterioration due to generalized scaling, system nonlinearities, and uncertainties, such that semi-global practically stable attitude tracking is guaranteed. External guidance loop based on the trajectory following method is designed, which reshapes the predefined pitch and yaw attitude profiles based on the respective normal and lateral positional errors, for acquiring the desired orbital parameters such as height, injection angle, orbital velocity, etc. To analyze the ascent flight trajectory, a detailed six-degrees-of-freedom simulator of a four-stage satellite launch vehicle is developed. The intensive numerical simulations are performed, which demonstrate the stability, robustness and the tracking capability of the proposed control and guidance methods in the presence of parametric uncertainties and external disturbances.

How nonlinear control can enhance the automobile efficiency and reduce harmful emissions: China case study

China transport energy consumption grows greatly along with dramatically escalated carbon dioxide emissions. Saving energy in transportation is requested for both reducing energy pressure intensity and decreasing relevant emissions. Large scale energy conservation and emission reduction are Chinese automotive industrys’ fundamental objectives. This paper addresses a nonlinear hybrid fuzzy based proportional integral derivative (PID) control methodology to reduce the automobile fuel over-consumption and gases over-emission. After introducing the mathematical model of the automobile Pierburg mechatronic actuator of nonlinear character with parameter uncertainties, its angular displacement is controlled via the proposed PID-fuzzy logic control (FLC) approach. The outputs of the PID controller are the entries of the series-connected FLC. The hybrid topology merges the simplicity and robustness advantages of both the classical PID and the FLC methods respectively. The feedback controller, based on FLC technique, is designed to desirably maintain the angular displacement towards their desired reference values with possible least steady state errors. The proper steady state error elimination will lead to considerable gas emission reduction together with improved energy efficiency. Through Matlab/Simulink tools, the numerical simulations significantly illustrate that the hybrid PID-FLC technique can contribute efficiently in ameliorating the system dynamic behavior in presence of parameter uncertainties. The overall system behavioral analysis enhancement and the proposed controller robustness are experimentally validated.

Self-Tuning Proportional Double Derivative-Like Neural Network Controller for a Quadrotor

In this paper, a self-tuning proportional double derivative-like neural network nonlinear adaptive controller for attitude tracking control of an unmanned aerial vehicle (UAV) is presented. The proposed scheme consists of neural networks with two neural nodes in the hidden layer and includes activation feedback. The error between the desired angle set-point and the output as well as the change of error is selected as the controller input. The optimal initial weight parameters are obtained by employing an adaptive ant colony optimization. The proposed controller can online tune the weight parameters of the hidden layer with a stable learning rate based on the controller input. The effect of the learning rates on the stability of the neural network controller was analyzed. The designed controller was developed based on a nonlinear model of an UAV with quaternion representation in the presence of parametric uncertainties and external disturbances. Simulation results demonstrate the validity and effectiveness of the proposed algorithm with different reference attitude signals.

Robust Tracking Control Of The Variable Stiffness Actuator Based On The Lever Mechanism

AbstractThis paper is concerned with the design of a robust adaptive tracking control scheme for a class of variable stiffness actuators (VSAs) based on the lever mechanisms. For these VSAs based on the lever mechanisms, the AwAS‐II developed at Italian Institute of Technology (IIT) is chosen as the study object, and it is an enhanced version of the original realization AwAS (actuator with adjustable stiffness). Firstly, for the dynamic model of the AwAS‐II system in the presence of parametric uncertainties, unknown bounded friction torques, unknown bounded external disturbance and input saturation constraints, by using the coordinate transformations and the static state feedback linearization, the state space model of the AwAS‐II system with composite disturbances and input saturation constraints is transformed into an uncertain multiple‐input multiple‐output (MIMO) linear system with lumped disturbances and input saturation constraints. Subsequently, a combination of the feedback linearization, disturbance observer, sliding mode control and adaptive input saturation compensation law is adopted for the design of the robust tracking controller that simultaneously regulates the position and stiffness of the AwAS‐II system. Under the proposed controller, the semi‐global uniformly ultimately bounded stability of the closed‐loop system has been proved via Lyapunov stability analysis. Simulation results illustrate the effectiveness and the robustness of the proposed robust adaptive tracking control scheme.

Finite-time sliding mode and super-twisting control of fighter aircraft

The development of two nonlinear robust higher-order flight control systems for roll-coupled maneuvers of fighter aircraft with uncertain parameters is discussed in this article. The objective is to independently control the output variables (roll angle, pitch angle and sideslip angle) using aileron, elevator and rudder control surfaces. For a nominal model of aircraft, first a finite time stabilizing (FTS) control law, based on the notion of geometric homogeneity, is designed. Then for robust control in the presence of parameter uncertainties, (i) a discontinuous sliding mode (DSM) control law and (ii) a super-twisting (STW) continuous control law is designed. It is shown that in the composite closed-loop system consisting of either (a) the FTS and DSM control laws or (b) the FTS and STW control systems, the output trajectory tracking error and its first-order derivative converge to the origin in finite time. Digital simulation results for a swept-wing fighter aircraft, including the two composite control systems, are obtained. These results show that each of the designed flight controllers accomplishes precise simultaneous large longitudinal and lateral maneuvers, despite uncertainties in the aerodynamic and inertia parameters, turbulence, and partial loss of control surface effectiveness.

Impedance control of secondary regulated hydraulic crane in the water entry phase

During the water entry phase in heavy lift marine operations, the involved crane system must satisfy stringent safety requirements. A hydraulic crane driven by a secondary controlled unit that has the advantage of high dynamic behavior and energy efficiency is investigated in this paper. The detailed models of the crane system and the offshore operating conditions are established. To guarantee functionality of the crane system under harsh sea conditions, a cascade control structure is constructed. In the outer loop, an extended state observer is used to estimate the unmeasured payload states. Then, an impedance controller is designed to realize trajectory tracking and impedance regulation of the payload. In the inner loop, the reference trajectory is provided by the impedance controller. An indirect adaptive robust control approach is applied to maximize the achievable tracking performance and to obtain accurate parameter estimates of the secondary controlled unit in the presence of parametric uncertainties and unknown disturbances. The proposed controller can lower a payload to a desired position, and keep the values of the hydrodynamic forces and wire tension within acceptable bounds at the same time. Comparative simulation results verify the effectiveness of the proposed control method.

Robust Tuning of Cross-Directional Model Predictive Controllers for Paper-Making Processes

This paper studies automated tuning of cross-directional model predictive control for industrial paper-making processes under user-specified model parameter uncertainties. Automated parameter tuning algorithms are developed to reduce the variability of the actuator and measurement profiles in the spatial domain and to achieve satisfactory performance in terms of worst case settling times and worst case control signal overshoots in the temporal domain for given parametric uncertainties. Due to decoupling properties of the spatial and temporal frequency components, the controller design and parameter tuning can be realized separately. For the spatial design and parameter tuning in the presence of parametric uncertainties, the undesirable high-frequency components in the actuator profile are suppressed via an appropriate design of the weighting matrix $S_{b}$ using the real-valued Fourier matrix approach. For the temporal design, a temporal filter is adopted to smooth the reference trajectory, where the parameter in the temporal filter is carefully tuned to achieve a tradeoff between the worst case settling time and the worst case control signal overshoot. Finally, the effectiveness of the proposed tuning algorithms is verified using a system model extracted from the pulp and paper industry.

Observer based nonlinear control design for glucose regulation in type 1 diabetic patients: An LMI approach

Abstract This paper deals with the design of observer-based nonlinear control of blood glucose concentration (BGC) of Type 1 diabetes mellitus (T1DM) patients in a Linear Matrix Inequality (LMI) framework. The controller design relies on the information of the states obtained from a nonlinear observer. The control law is derived using feedback linearisation and regional pole placement technique. Further, a numerical optimisation method is proposed for the computation of the controller gains by capturing the relationship between transformed domain and original domain dynamics by iteratively tuning the circular LMI region parameters (‘q’ and ‘r’) such that the locations of closed-loop poles of the original nonlinear system are attained. The proposed controller can deliver robust closed-loop response of BGC within a specified range of parametric uncertainty and meal disturbances owing to the appropriately tuned bound of LMI region parameters. The performance of the proposed controller is tested for 100 virtual T1DM patients in the presence of parametric uncertainty and uncertain meal disturbance. Both severe hypoglycemia (

UDE-based current control of grid-connected photovoltaic inverters

PurposeThe purpose of this study is to improve the control performance of grid-connected photovoltaic (PV) inverters with inductive-capacitive-inductive (LCL) filters by proposing a new robust current control based on uncertainty and disturbance estimator (UDE).Design/methodology/approachThe control strategy combines the capacitor current feedback with a UDE-based control to solve robust stability issues in the presence of parametric uncertainties and disturbances.FindingsThis paper provides guidelines for tuning the controller parameters where it is shown to be easy to implement by simply selecting the appropriate feedback coefficient, the reference model and an approximate lumped disturbance bandwidth. Simulation and experimental results demonstrate the effectiveness of the proposed controller in terms of resonance damping, tracking performance and robust stability under grid uncertainties and disturbances.Practical implicationsThis paper offers a new approach for designing implementable robust controllers for LCL-filtered grid-connected PV inverters.Originality/valueA new UDE-based current control is proposed to improve the stability performance of grid-connected PV inverters. The advantages of UDE-based control are its simple structure, easy tuning and robustness under parameter uncertainties and disturbances. Simulation and experimental results support the theoretical findings.