Robust Hinfin Research Articles

Robust H-Infinity Dual Cascade MPC-Based Attitude Control Study of a Quadcopter UAV

Aimed at the stability problem of quadrotor Unmanned Aerial Vehicle (UAV) flight attitudes under random airflow disturbance conditions, a robust H-infinity-based dual cascade Model Predictive Control (MPC) attitude control method is proposed. Model Predictive Control itself has the capability to minimize the deviation between the prediction error and the control target by optimizing the control algorithm. The robust H-infinity controller can maintain stability in the face of system model uncertainty and external disturbances. The controller designed in this paper divides the attitude control loop into the following two parts: the angle loop and the angular velocity loop. The angle loop, serving as the main control loop of the attitude control, employs the robust H-infinity controller to process the angle of the quadrotor UAV and then transmits the processed value to the MPC controller. This approach reduces the computational load of the MPC controller. Simultaneously, by optimizing the algorithm, MPC minimizes the prediction error and the deviation from the control target. Simulation experiments confirm that the proposed algorithm improves the stability of the UAV attitude under random airflow disturbance conditions, while also achieving accurate tracking of the UAV’s position.

Robust H-infinity and μ-synthesis controllers to mitigate sub-synchronous control interaction in DFIG wind farms considering time delay

Robust H-infinity and μ-synthesis controllers to mitigate sub-synchronous control interaction in DFIG wind farms considering time delay

Cross-coupling indirect iterative learning control method for batch processes with time-varying uncertainties

For batch time-varying processeswith non-repetitive disturbances, a cross-coupling indirect iterative learning control (CC-iILC) is proposed. The set trajectory of the system on the single axis is accurately tracked by an indirect iterative learning control strategy with a PI controller for its time direction and a closed-loop feedback control strategy for the batch direction. Under the asymptotically stable condition of the two-dimensional (2D) dynamic model, the optimal control law is obtained by optimizing the H-infinity control function. To avoid the contour error during coupling, the cross-coupling technique is used to distribute the contour error to each axis for compensation. The stability condition of the indirect iterative learning controller is analyzed by a two-dimensional Fornasini-Marchesini (FM) batch dynamics model and two-dimensional robust H-infinity control theory. The feasibility and superiority of the proposed control method are verified by numerical simulation and experimental tests.

Robust H-Infinity Tracking Control for a Valve-Controlled Hydraulic Motor System with Uncertain Parameters in the Complex Load Environment.

A valve-controlled hydraulic motor system operating in a complex environment is subject to complex load changes. In extreme cases, the load can be regarded as a disturbance signal with complex frequency and strong amplitude fluctuations, which greatly affects the speed stability of the hydraulic motor and reduces the operating efficiency. In this paper, the structure of valve-controlled hydraulic motor systems is analyzed, and a valve-controlled hydraulic motor system model with uncertain parameters is established after considering the actual target parameter error and model linearization error. Different from the common H-infinity control, which regards the load disturbance as external disturbance, this paper presents a robust H-infinity tracking control strategy, which considers uncertain parameters and the load torque of the valve-controlled hydraulic motor system as internal disturbances. The simulation results show that the proposed control scheme has better control characteristics and robustness than the traditional PID control.

Investigation of the Robust H-Infinity Filter's Effectiveness on the Model Predictive Control and Linear Quadratic Regulator for Active Seismic Control of High-Rise Buildings

Investigation of the Robust H-Infinity Filter's Effectiveness on the Model Predictive Control and Linear Quadratic Regulator for Active Seismic Control of High-Rise Buildings

New Approach for Nonlinear Robust H-Infinity Control of an Induction Motor

New Approach for Nonlinear Robust H-Infinity Control of an Induction Motor

Robust H-infinity Fuzzy Output Feedback Control for Path Following of FWID-EVs with Actuator Saturation

Robust H-infinity Fuzzy Output Feedback Control for Path Following of FWID-EVs with Actuator Saturation

Robust Adversarial Reinforcement Learning with Dissipation Inequation Constraint

Robust adversarial reinforcement learning is an effective method to train agents to manage uncertain disturbance and modeling errors in real environments. However, for systems that are sensitive to disturbances or those that are difficult to stabilize, it is easier to learn a powerful adversary than establish a stable control policy. An improper strong adversary can destabilize the system, introduce biases in the sampling process, make the learning process unstable, and even reduce the robustness of the policy. In this study, we consider the problem of ensuring system stability during training in the adversarial reinforcement learning architecture. The dissipative principle of robust H-infinity control is extended to the Markov Decision Process, and robust stability constraints are obtained based on L2 gain performance in the reinforcement learning system. Thus, we propose a dissipation-inequation-constraint-based adversarial reinforcement learning architecture. This architecture ensures the stability of the system during training by imposing constraints on the normal and adversarial agents. Theoretically, this architecture can be applied to a large family of deep reinforcement learning algorithms. Results of experiments in MuJoCo and GymFc environments show that our architecture effectively improves the robustness of the controller against environmental changes and adapts to more powerful adversaries. Results of the flight experiments on a real quadcopter indicate that our method can directly deploy the policy trained in the simulation environment to the real environment, and our controller outperforms the PID controller based on hardware-in-the-loop. Both our theoretical and empirical results provide new and critical outlooks on the adversarial reinforcement learning architecture from a rigorous robust control perspective.

Robust H-infinity control for connected vehicles in lattice hydrodynamic model at highway tunnel

In this paper, a macro hydrodynamic model suitable for tunnel traffic in the network environment is proposed. Firstly, according to the characteristics of tunnel traffic, we establish the corresponding lattice hydrodynamics model, and design the corresponding control strategy according to the information obtained by connected vehicles. Through the theoretical analysis, the internal stability conditions of the traffic system are obtained. After the external disturbance caused by the tunnel is considered, a robust H-infinity (H∞) control strategy is proposed, and the corresponding robust stability conditions are obtained. The string stability is also studied to ensure that the instantaneous disturbance is not amplified. Numerical simulation compares the evolution of the traffic system with and without control. The results reflect that the control strategy proposed in this paper can effectively maintain the stability of tunnel traffic system.

Study and Application of the Advanced Frequency Control Techniques H∞ in the Voltage Automatic Regulator of Powerful Synchronous Generators (Application under Gui/Matlab)

This article presents a study of of the advanced frequency control techniques based on loop-shaping H∞ optimization method applied on automatic excitation control of powerful synchronous generators (AVR and PSS), to improve transient stability and its robustness of a single machine- infinite bus system (SMIB).The computer simulation results (static and dynamic stability), with test of robustness against machine parameters uncertainty (electric and mechanic), have proved that good dynamic performances, showing a stable system responses almost insensitive to large parameters variations, and more robustness using the robust H-infinity controller, in comparison with the classical Russian PID power system stabilizer . Our present study was performed using a GUI realized under MATLAB in our work.

Optimisation of robust and LQR control parameters for discrete car model using genetic algorithm

Active suspension systems are the main feature in modern cars and will be the main stream in the future. The optimisation of their performances requires many studies about the different types of controllers. Robust H-infinity and linear quadratic regulator (LQR) controllers are used to control the suspension system and to reduce the vibrations in the car and to improve handling. A half car discrete model is considered in this research to study the effects on passengers owing to different road profiles. The weights of robust H-infinity and LQR controllers are obtained using genetic algorithm on a half car model with two different types of common road disturbance. The design parameters of both the active controllers vary with various road profiles. This proves that particular design parameters in robust and LQR controller do not have the ability to adapt to the variations in road surface. Furthermore, active controllers significantly improve the performance of the system in all aspects when compared to passive systems.

A Robust Controller Design Methodology Addressing Challenges Under System Uncertainty

This paper proposes a generalized design methodology of a robust controller to mitigate the impact of system uncertainty on controller stability and performance which includes steady-state error, disturbance rejection, high-frequency noise attenuation and speed of dynamic response. The first step is to select the weighting functions that bound the transfer functions for the entire range of uncertainty. The second step is to form mathematical representation for both robust stability and robust performance. The third step is to conduct the robust H-infinity controller synthesis to generate the full-order controller, and then carry out order reduction and recheck of the design objectives. The last step is to select an optimized controller based on the multi-dimensional Pareto Front algorithm. The proposed method has been firstly applied to the current controller design of a grid-connected inverter with variable grid impedance, and secondly to the voltage controller design of an LLC resonant DC/DC converter with variable resonant capacitance. The results indicate that the selected optimal H-infinity controller has an overall more satisfactory performance in terms of stability, steady-state error, disturbance/noise rejection capability and dynamic performance, compared with conventional PI and PR controllers when there is a large variation of system parameters.

Attack isolation and location for a complex network cyber-physical system via zonotope theory

This paper investigates the attack isolation (AI) and attack location (AL) problems for a cyber-physical system (CPS) based on the combination of the H-infinity observer and the zonotope theory, where the real control plant in the physical layer is a nonlinear complex network system. Firstly, for actuator AI and AL purposes, two robust H-infinity observers are designed and the stabilities of them are analyzed based on linear matrix inequalities (LMIs). Secondly, the zonotope theory is used to the error dynamic system of the H-infinite observer such that it can calculate iteratively the interval state estimation if the CPS has no attacks. Third, two residuals are constructed and their interval estimates are also given, and furthermore, based on the residual interval estimates, both actuator AI and AL schemes are developed. Besides, sensor AI and AL issues are discussed by modifying the actuator AI and AL schemes. Finally, the effectiveness of the proposed methods is illustrated through a simulation example.

Closed Loop Performance Analysis of Classical PID and Robust H-infinity Controller for VTOL Unmanned Quad Tiltrotor Aerial Vehicle

Unmanned Aerial Vehicles (UAVs) guidance, control and navigation have directed the attention of many researchers in both aerospace engineering as well as control theory. Due to the unique rotor structure of Tiltrotor hybrid UAVs, they exhibit special application value. Quad Tiltrotor UAVs set up a distinctive platform that satisfies the needs of the varying mission requirements by combining the conventional features of high-speed cruise capabilities of an aircraft and hovering capabilities of a helicopter and by tilting its four rotors. The aim of this research article is to control the attitude and altitude of the UAV in the presence of uncertainty using two different control techniques. This paper addresses the comparative analysis of the robust H-infinity controller with classical PID control designs for the transition manoeuvre of a hybrid UAV: the VTOL Tiltrotor UAV. The proposed controllers achieve hover to cruise mode transition and vice-versa. The main idea behind the design of controller is to model and analyze the UAV’s position and attitude dynamics. The desired flight trajectory and the transition manoeuvre is achieved by controlling the tilt angle in 15° intervals from 90° to 0° and vice-versa. Performance index subjected to IAE is estimated and compared for both the controllers in the presence of noise, disturbances and uncertainties. The results of simulation illustrate that the robust H-infinity controller achieves better transition, good adaptability, robust performance and robust stability for the whole flight envelope when compared with the PID controller.

Comparative Study of Trajectory Tracking Control for Automated Vehicles via Model Predictive Control and Robust H-infinity State Feedback Control

A comparative study of model predictive control (MPC) schemes and robust H_{infty } state feedback control (RSC) method for trajectory tracking is proposed in this paper. The main objective of this paper is to compare MPC and RSC controllers’ performance in tracking predefined trajectory under different scenarios. MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire, which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode. RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison. Then, three test cases are built in CarSim-Simulink joint platform. Specifically, the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions. Besides, the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability. Furthermore, an extreme curve test is built where the road adhesion changes suddenly, in order to test the performance of both controllers under extreme conditions. Finally, the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.

Electrochemical-distributed thermal coupled model-based state of charge estimation for cylindrical lithium-ion batteries

State of Charge (SoC) is essential in a smart Battery Management System (BMS). Traditional SoC estimation methods consider the lithium battery cell as an isothermal body simplistically, which is not accurate. Due to the heat conduction and convection, the temperature distribution along the radius is nonuniform, which means the battery model parameters subject to temperature are not identical radially. This paper proposed a modified electrochemical-distributed thermal coupled model (MEDTM) for improving the accuracy of SoC estimation. The distributed thermal model is employed to design a robust H-infinity temperature observer for the estimation of the radial temperature distribution of battery cell, where a radial discretized method is used for the realization of the observer design. Based on the observed temperature, a SoC observer is developed with the backstepping method. Finally, experiments and simulation are implemented. The two constant discharging experiments indicate that MEDTM is more accurate than the single particle model with surface temperature (SPMST), and it can generate reliable temperature prediction. A comparative simulation and a constant discharging experiment verify the H-infinity temperature observer can obtain a more accurate estimation of the battery cell’s temperature than the luenberger observer, and the H-infinity temperature observer has an estimation error of 0.3 K below. Then, through a constant discharging experiment and a simulation with UDDS current, the proposed SoC observer is verified to accurately estimate the SoC by comparing with the true SoC, where the estimated error of SoC under the two cases is below 1.5% and below 0.4%, respectively. Therefore, the proposed SoC observer also has good performance.

H-Infinity Shifting Control in a Dual-Speed Transmission for Electric Vehicle

To improve the economic and comfort performance of pure electric vehicles (PEV), this paper proposes a novel H-infinity gear-shifting controller for dual-speed Transmissions (DST) to achieve a smooth and swift shifting when considering uncertain disturbances in system. Firstly, the structure as well as the working principle of the DST for PEV are introduced briefly and the mathematical model of the transmission is derived according to the Lagrange equation. Then the gear-shifting process is analyzed and the control problem is formulated according to the clutch status. Next, a robust H-infinity controller is proposed to attenuate the vehicle jerk as well as the clutch sliding energy loss. Simulation results under different working conditions indicate the controller presented have better performance in limiting the effect of unknown external disturbances comparing to a calibrated proportional-integral-derivative (PID) controller.

Application of robust H-infinity controller in transition flight modeling of autonomous VTOL convertible Quad Tiltrotor UAV

PurposeThis paper aims to provide a mathematical modeling and design of H-infinity controller for an autonomous vertical take-off and landing (VTOL) Quad Tiltrotor hybrid unmanned aerial vehicles (UAVs). The variation in the aerodynamics and model dynamics of these aerial vehicles due to its tilting rotors are the key issues and challenges, which attracts the attention of many researchers. They carry parametric uncertainties (such as non-linear friction force, backlash, etc.), which drives the designed controller based on the nominal model to instability or performance degradation. The controller needs to take these factors into consideration and still give good stability and performance. Hence, a robust H-infinity controller is proposed that can handle these uncertainties.Design/methodology/approachA unique VTOL Quad Tiltrotor hybrid UAV, which operates in three flight modes, is mathematically modeled using Newton–Euler equations of motion. The contribution of the model is its ability to combine high-speed level flight, VTOL and transition between these two phases. The transition involves the tilting of the proprotors from 90° to 0° and vice-versa in 15° intervals. A robust H-infinity control strategy is proposed, evaluated and analyzed through simulation to control the flight dynamics for different modes of operation.FindingsThe main contribution of this research is the mathematical modeling of three flight modes (vertical takeoff–forward, transition–cruise-back, transition-vertical landing) of operation by controlling the revolutions per minute and tilt angles, which are independent of each other. An autonomous flight control system using a robust H-infinity controller to stabilize the mode of transition is designed for the Quad Tiltrotor UAV in the presence of uncertainties, noise and disturbances using MATLAB/SIMULINK. This paper focused on improving the disturbance rejection properties of the proposed UAV by designing a robust H-infinity controller for position and orientation trajectory regulation in the presence of uncertainty. The simulation results show that the Tiltrotor achieves transition successfully with disturbances, noise and uncertainties being present.Originality/valueA novel VTOL Quad Tiltrotor UAV mathematical model is developed with a special tilting rotor mechanism, which combines both aircraft and helicopter flight modes with the transition taking place in between phases using robust H-infinity controller for attitude, altitude and trajectory regulation in the presence of uncertainty.

A pseudo-spectrum based characterization of the robust strong H-infinity norm of time-delay systems with real-valued and structured uncertainties

Abstract This paper provides a mathematical characterization of the robust (strong) H-infinity norm of an uncertain linear time-invariant system with discrete delays in terms of the robust distance to instability of an associated characteristic matrix. The considered class of uncertainties consists of real-valued, structured, Frobenius norm-bounded matrix uncertainties that act on the coefficient matrices. The robust H-infinity norm, defined as the worst-case value of the H-infinity norm over all admissible uncertainty values, is an important measure of robust performance to quantify the worst-case disturbance rejection of an uncertain dynamical system. For the considered system class, this robust H-infinity norm is however a fragile measure, as for a particular instance of the uncertainties, the H-infinity norm might be sensitive to arbitrarily small perturbations on the delays. Therefore, we introduce the robust strong H-infinity norm, inspired by the notion of strong stability of delay differential equations of neutral type, which takes into account both the uncertainties on the system matrices and infinitesimal delay perturbations. This quantity is a continuous function of both the elements of the system matrices and the delays. The main contribution of this work is the introduction of a relation between this robust strong H-infinity norm and the robust distance to instability of an associated characteristic matrix. This relation is subsequently employed in a novel algorithm for computing the robust strong H-infinity norm of uncertain time-delay systems.

Model-dependent Scheduling and H-infinity Control Co-design for Networked Control Systems

In this paper, a novel model-dependent scheduling scheme is proposed for the networked control systems with time-delay, disturbance, and medium access constraints. The scheduler calculates the error between the ideal dynamic and the real system, and selects the states that make the stability of the system better to access the network. In addition, two kinds of representative time-delays in the networked control systems, constant time-delay and random time-delay, are considered. A robust H-infinity and switched-system-based co-design strategy is introduced to deal with the disturbance in the system, and the system uncertainty introduced by the random time-delay as well. Finally, illustrative examples are given to demonstrate the effectivity of the proposed scheduling method and the co-design scheme.