Robust Control Performance Research Articles

Design of Model-based Controller with Disturbance Estimation in Steer-by-wire System

The steer-by-wire system is a next generation steering control technology that has been actively studied because it has many advantages such as fast response, space efficiency due to removal of redundant mechanical elements, and high connectivity with vehicle chassis control, such as active steering. Steer-by-wire system has disturbance composed of tire friction torque and self-aligning torque. These disturbances vary widely due to the weight or friction coefficient change. Therefore, disturbance compensation logic is strongly required to obtain desired performance. This paper proposes model-based controller with disturbance compensation to achieve the robust control performance. Targeted steer-by-wire system is identified through the experiment and system identification method. Moreover, model-based controller is designed using the identified plant model. Disturbance of targeted steer-by-wire is estimated using disturbance observer(DOB), and compensate the estimated disturbance into control input. Experiment of various scenarios are conducted to validate the robust performance of proposed model-based controller.

Adaptive Recurrent Neural Network Enhanced Variable Structure Control for Nonlinear Discrete Mimo Systems

AbstractThe stability and performance of robust control for a nonlinear complex dynamic system deteriorates due to large uncertainties. To address this, a discrete variable structure control (DVSC) outside of a convex set is designed to force the operating point into a convergent set, which is verified by Lyapunov stability theory. Due to the dynamic features of the lumped uncertainties, they are learned on‐line by a recurrent neural network (RNN) in a specific convex set containing the convergent set of the DVSC. Between this convergent set and the convex set, a switching mechanism determines whether a learning RNN for the lumped uncertainties is executed. An adaptive recurrent‐neural‐network enhanced discrete variable structure control is then established to improve both transient and steady performances. Simulations, including compared examples and application to the trajectory tracking of a mobile robot, validate the effectiveness and robustness of the proposed control.

Model Following Adaptive Sliding Mode Tracking Control Based on a Disturbance Observer for the Mechanical Systems

A model following adaptive sliding mode tracking control (MFASMTC) with the adjustable control gain based on a disturbance observer (DOB) for the mechanical system is proposed in this paper. The control gains of the proposed controller are automatically adjusted to compensate the unknown time-varying disturbances by the DOB. First, the unknown variables and uncertainties are lumped as the disturbance terms and the system dynamic model consist of the nominal matrix and disturbances vector. The desired model and sliding mode controller (SMC) are integrated by using the Lyapunov function candidate to obtain the general model following sliding mode tracking control (MFSMTC) with the fixed control gain. To stabilize and compensate the unknown time-varying disturbances for the control system, a DOB is combined with the MFSMTC to obtain the MFASMTC to automatically adjust the control gains. The mass-spring-damper system and two-link manipulator robot system are both used as examples system to demonstrate the proposed control scheme, respectively. The comparisons between MFSMTC with the fixed control gain and MFASMTC with the adjustable control gain based on a DOB are performed in this paper. From the simulation results, the proposed MFASMTC with the adjustable control gain based on a DOB demonstrates the stable and robust control performance for the unknown uncertainties and external disturbances. The proposed control method also can be applied to the other mechanical systems with the desired model to find the desired model following adaptive sliding mode tracking control.

A comparative study of high performance robust PID controller for grid voltage control of islanded microgrid

This paper presents the design of a robust proportional–integral–derivative controller for grid voltage control of an islanded microgrid. The microgrid consists of several distributed generation units and local loads. The loads are parametrically unknown and uncertain which ensure the variation of microgrid performance. The controller is designed to achieve fast transient response, zero steady-state error and robust performance in the presence of un-modeled loads, dynamic loads, nonlinear loads and harmonic loads. The performance of the controller is tested using MATLAB/Simulink SimPowerSystems. The simulation results show that the proposed controller is robust and provides high performance for voltage control of the islanded microgrid system by achieving the rise time, peak time, percentage of OS, and settling time of 0.00492, 0.018, 2.19, and 0.0271 ms.

이동형 플랫폼에 탑재된 포탑 시스템의 모션 안정화 제어기 설계

The motion stabilization have been a critical interest in various mechanical fields. It, especially, plays a key role in maintenance of the Line of Sight (LOS) for weapons such as turret’s precise targeting performance. For high mobility, turrets are typically located on various moving platforms, either ground-base or ocean-base. The base motion affects LOS through the mechanical friction via bearing structure. Thus, this paper proposes dual-stage control architecture for two Degrees of Freedom DOF) turret on a ground-base moving platform for robust position tracking performance. Proposed control structure possesses a real-time disturbance observer in order to compensate disturbances including friction caused from the moving base. The structure consists a conventional outer-loop position controller for robust position tracking performance and inner-loop disturbance observe for effective disturbance cancellation. The validity of the algorithm is confirmed via simulation by observing that the resulting position tracking error satisfies the target performance.

Neural network robust tracking control with adaptive critic framework for uncertain nonlinear systems

In this paper, we aim to tackle the neural robust tracking control problem for a class of nonlinear systems using the adaptive critic technique. The main contribution is that a neural-network-based robust tracking control scheme is established for nonlinear systems involving matched uncertainties. The augmented system considering the tracking error and the reference trajectory is formulated and then addressed under adaptive critic optimal control formulation, where the initial stabilizing controller is not needed. The approximate control law is derived via solving the Hamilton–Jacobi–Bellman equation related to the nominal augmented system, followed by closed-loop stability analysis. The robust tracking control performance is guaranteed theoretically via Lyapunov approach and also verified through simulation illustration.

IMPROVEMENT OF QUADROTOR PERFORMANCE WITH FLIGHT CONTROL SYSTEM USING PARTICLE SWARM PROPORTIONAL-INTEGRAL-DERIVATIVE (PS-PID)

The rapid development of microprocessor, electrical, sensors and advanced control technology make a quadrotor fast expansion. Unfortunately, a quadrotor is unstable and impossible to fly in fully open loop system. PID controller is one of methodology that has been proposed to control the flight control system. Unfortunately, adjustment of PID parameters for robust control performance is not easy and still problems. The paper proposed a flight controller system based on a PID controller. The PID parameters are tuned automatically using Particle Swarm Optimization (PSO). Objective of this method is to improve the flight control system performance. Several experiments have been performed. According to these experiments the proposed system able to generate optimal and reliable PID parameters for robust flight controller. The system also has 41.57 % improvement in settling time response.

A two-stage robust-intelligent controller design for efficient LFC based on Kharitonov theorem and fuzzy logic

This paper proposes an efficient load frequency control (LFC) approach based on robust and intelligent methods. Practically speaking, proportional-integral (PI) controller is widely deployed in LFC structure. Basically, the parameters of PI controller are adjusted based on trial-and-error or classic control methods. In such manners, robust performance of PI controller cannot be guaranteed in disturbances including load changes or parameter variations. In this research, at the first stage, the gain values of PI controller are tuned in an offline manner based on Kharitonov theorem which strengthens the validity of the controller against the variations in time constants of turbine and governor. As another aspect of uncertainty, power system loading demand is changed ceaselessly. To accommodate such conditions, at the second stage, the initial gain values based on Kharitonov theorem are adapted in an online manner based on fuzzy logic approach. The fuzzy controller, as an aspect of intelligence, adapts the proportional and integral gains through appropriate membership functions in an online fashion. Frequency deviation and its derivative are selected as efficient input signals for the fuzzy controller. Detailed numerical studies are conducted to assess performance of the proposed approach. Results demonstrate a reliable frequency performance against different uncertainties.

Evaluating the performance of robust controllers for a nanopositioning platform under loading.

Piezoactuated nanopositioners are an integral component in Scanning Probe Microscopes (SPM). The imaging application of SPMs necessitate the loading of the nanopositioning platform with various samples. This causes an increase in mass thereby altering the dynamics of the system. Various methods have been proposed to control uncertain systems such as H∞ robust control, µ-synthesis and mixed µ-synthesis. Additionally, low-order damping controllers, such as Integral Resonance Control (IRC) and Positive Position Feedback (PPF), have been shown to be robustly stable via the negative imaginary lemma. In this paper, IRC is used as a benchmark for robust performance, and robust controllers are developed using the aforementioned methods. It is found that the best performance, in terms of the H∞ norm over the range of uncertainty, is achieved using the IRC control scheme. In addition, IRC provides more accurate tracking of a reference signal.

Event-Based Constrained Robust Control of Affine Systems Incorporating an Adaptive Critic Mechanism

This paper focuses on establishing an event-based constrained robust control strategy for a class of continuous-time affine nonlinear systems by incorporating the adaptive critic mechanism (ACM). The main objective is to integrate the event-based framework, the constrained optimal control method, and the neural network learning ability, thereby achieving the nonlinear robust state feedback of input-constrained nonlinear systems under event-based environment. Through theoretical analysis, it is shown that the nonlinear robust control law subject to input limitations can be obtained by designing an event-based constrained optimal controller with respect to the nominal system. Then, the ACM is adopted to facilitate the constrained optimal control implementation, where a critic neural network is constructed to serve as the learning approximator. The system stability issue is proved by employing the Lyapunov theory and the constrained robust control performance is illustrated through simulation experiments of several dynamical plants.

Robust task-space control of an autonomous underwater vehicle-manipulator system by PID-like fuzzy control scheme with disturbance estimator

This paper presents, a robust nonlinear proportional-integral-derivative (PID)-like fuzzy control scheme for a task-space trajectory tracking control of an autonomous underwater vehicle-manipulator system (AUVMS) employed for deep-sea intervention tasks. The effectiveness of the proposed control scheme is numerically demonstrated on a planar underwater vehicle manipulator system (consisting of an underwater vehicle and two link rotary (2R) serial planar manipulator). The actuator and sensor dynamics of the system are also incorporated in the dynamical model of an AUVMS. The proposed control law consists of two main parts: first part uses a feed forward term to reinforce the control activity with extravagance from known desired acceleration vector and carries an estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics and the second part uses a PID-like fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system. The primary objective of the proposed control scheme is to track the given end-effector task-space trajectory despite of external disturbances, system uncertainties and internal noises associated with the AUVMS system. To show the effectiveness of the proposed control scheme, comparison is made with linear and nonlinear PID controllers. Simulation results confirmed that with the proposed control scheme, the AUVMS can successfully track the given desired spatial trajectory and gives better and robust control performance.

A self-learning disturbance observer for nonlinear systems in feedback-error learning scheme

This paper represents a novel online self-learning disturbance observer (SLDO) by benefiting from the combination of a type-2 neuro-fuzzy structure (T2NFS), feedback-error learning scheme and sliding mode control (SMC) theory. The SLDO is developed within a framework of feedback-error learning scheme in which a conventional estimation law and a T2NFS work in parallel. In this scheme, the latter learns uncertainties and becomes the leading estimator whereas the former provides the learning error to the T2NFS for learning system dynamics. A learning algorithm established on SMC theory is derived for an interval type-2 fuzzy logic system. In addition to the stability of the learning algorithm, the stability of the SLDO and the stability of the overall system are proven in the presence of time-varying disturbances. Thanks to learning process by the T2NFS, the simulation results show that the SLDO is able to estimate time-varying disturbances precisely as distinct from the basic nonlinear disturbance observer (BNDO) so that the controller based on the SLDO ensures robust control performance for systems with time-varying uncertainties, and maintains nominal performance in the absence of uncertainties.

Output Feedback Stabilization for Discrete-Time Systems Under Limited Communication

This paper addresses the output feedback stabilization problem for discrete-time networked control systems with imperfect input channels, i.e., the controller-actuator channels, where both quantization error and packet dropout are involved. A stabilizability condition is first derived for the single-input-single-output (SISO) case. It is shown that stabilization over quantized lossy channel actually involves a trade-off between robust stability control and robust performance control. Furthermore, the results are expanded to triangularly decoupled multiple-input-multiple-output (MIMO) systems and a necessary and sufficient condition is deduced, which also exhibits a compromise between robust stability control and robust performance control in the individual channel as echoing the SISO case.

Finite-time output feedback attitude control for spacecraft using “Adding a power integrator” technique

This paper investigates the problem of finite-time output feedback control for spacecraft attitude stabilization with attitude-only measurement. First, a finite-time filter is proposed to generate the pseudo-angular-velocity signal, which is fed to the controller, and then a continuous finite-time attitude controller is designed based on the proposed filter. The overall finite-time stability of entire filter-controller closed-loop system is given through the adding a power integrator technique. The rigorous proof shows that the attitude will converge to its equilibrium states in the absence of disturbance. When considering disturbance, states will be eventually stabilized to a residual set of equilibrium in a finite time. Numerical simulation results illustrate the proposed method can provide the fast transient response, energy-efficient and robust attitude control performance.

Construction and experimental verification of a novel flexible thermal control system configuration for the autonomous on-orbit services of space missions

This paper proposed a novel flexible thermal control system (F-TCS) configuration for realizing thermal management for spacecrafts autonomous on-orbit service (A-OOS) demands. With a dual-ring topology which composes of a heat collecting bus, a heat dissipating bus, connection brunches and inter-platform service interfaces, the F-TCS may realize not only self-reconfiguration operations but also providing heat dissipation resources for other spacecrafts or cabins. The F-TCS hydraulic and thermal dynamics were modeled, a verification testbed was also established to validate the F-TCS thermal control performance. Focused on investigating the self-reconfiguration and thermal control cooperative operations, several typical A-OOS cases were imposed on the F-TCS, numerical simulations and experimental validations were respectively implemented. Both results demonstrated that the meticulously designed F-TCS is capable of offering self-topological reconfiguration with fast time response and robust temperature control performances, high systemic heat transfer efficiency is also recommended from the point of view of energy saving. The F-TCS is suggested as a promising solution for A-OOS owing to its higher reliability and promising autonomous maintenance potential which is suitable for future spacecrafts thermal management requirements.

Control of underground blast induced building vibration by shape-memory-alloy rubber bearing (SMARB)

Summary This paper focuses on the performance of shape-memory-alloy rubber bearings (SMARBs) compared to conventional lead-plug or New-Zealand (N-Z) bearings in control of building vibration due to underground blast induced ground motion (BIGM). The performance is evaluated with regard to maximum acceleration and isolator displacement obtained by nonlinear time history analysis. In doing so the Bouc–Wen's model is used to represent the nonlinear behaviour of the N-Z bearing and the superelastic behaviour of nickel–titanium-based shape-memory alloy is represented by the Graesser–Cozzarelli model. The underground BIGM input is modelled by exponentially decaying function. It is observed that though the N-Z bearing is fairly effective in controlling the structural accelerations due to BIGM without excessive bearing displacements, there remains a problem with the residual bearing displacements. The latter, however, is found to be dealt with very effectively by the SMARB. Furthermore, the procedure to obtain the optimum design parameters of the base isolators under study is obtained by optimizing two mutually conflicting objective functions, that is, the minimization of peak acceleration as well as peak bearing displacement by converting the multiobjective optimization problem to a single composite objective function. The improved and robust control performance of SMARB compared to N-Z bearing is elucidated through numerical study by considering a five-storied shear building frame.

Optimal Decentralized Supplementary Inverter Control Loop to Mitigate Instability in an Islanded Microgrid with Active and Passive Loads

Abstract: The growing penetration levels of passive and rectifier interfaced active loads can cause instability in an islanded inverter based microgrid. This may be due to the dynamics associated with passive loads and interaction between the control loops of active loads and inverter-interfaced DGs. This paper proposes a decentralized supplementary control loop around each inverter-interfaced distributed generation (DG) unit to mitigate the instability caused by both the active as well as passive loads. The proposed control loop is based on a robust linear quadratic regulator with prescribed degree-of-stability (LQRPDS). In order to obtain the optimal values of the state and control weighting matrices of LQRPDS, a bi-objective optimization problem has been formulated and solved using a fast and elitist multi-objective non-dominated sorting genetic algorithm (NSGA-II). The proposed decentralized supplementary control loop does not interfere with the steady state performance and provides robust control performance under various load configurations as well as step load disturbances. Eigenvalue analysis and time-domain simulations have been used to validate the effectiveness of the proposed decentralized supplementary control loop.

A Multi-Model Approach to Design a Robust SVC Damping Controller Using Convex Optimization Technique to Enhance the Damping of Inter-Area Oscillations Considering Time Delay

This paper introduces a multi-model approach to design a robust supplementary damping controller. The designed fixed-order supplementary damping controller adjusts the voltage reference set point of SVC. There are two main objectives of the controller design, damping low frequencies oscillations and enhancing power system stability. This method relies on shaping the closed-loop sensitivity functions in the Nyquist plot under the constraints of these functions. These constraints can be linearized by choosing a desired open-loop transfer function. The robust controller is designed to minimize the error between the open-loop of the original plant model and the desired transfer functions. These outcomes can be achieved by using convex optimization methods. Convexity of the problem formulation ensures global optimality. One of the advantages of the proposed approach is that the approach accounts for multi-model uncertainty. In contrast to the methods available in the literature, the proposed approach deals with full-order model (i.e., model reduction is not required) with lower controller order. The issue of time delay of feedback signals has been addressed in this paper for different values of time delay by applying a multi-model optimization technique. The proposed approach is compared to other existing techniques to design a robust controller which is based on H2 under pole placement. Both techniques are applied to the 68-bus system to evaluate and validate the robust controller performance under different load scenarios and different wind generations.

Load Management of Modular Battery Using Model Predictive Control: Thermal and State-of-Charge Balancing

Thermal and state-of-charge (SOC) imbalances are well known to cause nonuniform aging in batteries. This paper presents the electrothermal control of a multilevel converter-based modular battery to address this issue. The modular battery provides a large redundancy in synthesizing terminal voltage, which gives extra degrees of freedom in control on cell level. There are multiple tightly coupled control objectives including the simultaneous thermal and SOC balancing as well as battery terminal voltage control. The main purpose of this paper is to devise an electrothermal control scheme for cases where full future driving information is not accessible. The control scheme is based on decomposition of controller into two orthogonal components, one for voltage control and the other for balancing control. This problem decomposition enables the application of constrained linear quadratic model predictive control scheme to solve the balancing problem elegantly. The control scheme is thoroughly evaluated through simulations of a four cell modular battery. The results show that a rather short prediction horizon is sufficient to achieve robust control performance.

A novel strategy to design enhanced performance robust controller for standalone VSI

A novel methodology for enhanced performance robust controller design is presented in this paper. The proposed method provides an efficient way to design a controller with an improved performance in terms of higher convergence rate of the system for the allowable uncertainties. The method is applied for the control design of standalone voltage source inverter. The control objective is to regulate its output voltage and frequency with an uncertain RL load. The dynamic equations of the system are used for uncertainty structure modelling. Then using Sylvester’s criterion, new uncertainty conditions are developed. Assisting with these conditions and intelligent technique differential evolution (DE), the optimum robust controller is designed. For reference tracking, this robust control law is augmented with integral control, which is also designed using DE. Furthermore, to guarantee the robustness of the augmented control law, a numerical approach is proposed. The effectiveness of the methodology is illustrated by means of simulations and real time hardware in the loop experiments. A comparison of the proposed method with existing robust control design method is also presented to demonstrate the improvement in performance.