Linear Quadratic Integral Control Research Articles

A Novel LQI Control Technique for Interleaved-Boost Converters

Hybrid electric vehicles (HEVs) and fuel cell electric vehicles (FCEVs) utilize boost converters to gain a higher voltage than the battery. Interleaved boost converters are suitable for low input voltage, large input current, miniaturization, and high-efficiency applications. This paper proposes a novel linear quadratic integral (LQI) control for the interleaved boost converters. First, the small-signal model of the interleaved-boost converter is derived. In the proposed method, an output voltage and a current signal error between two-phase input currents are selected to control not only the output voltage but also a balance between two-phase input currents. Furthermore, steady-state characteristics in terms of the output voltage and the input current are demonstrated by experiments and simulations using an experimental apparatus with a rated power of 700 W. The validity of the proposed method’s tracking performance and load response is demonstrated by comparing it with that of the conventional PI control. The tracking performance of the LQI control for the 40 V step response has a ten times faster response than that of the PI control. Also, the experimental results demonstrate that the proposed method maintains a constant output voltage for a 300 W load step while the PI control varies by 10 V during 70 ms. Additionally, the proposed method has an excellent disturbance rejection.

An advanced secondary voltage control strategy for future power systems

The network voltage control together with the regulation of reactive power, has always been recognized as vital feature of power systems. It is aimed at containing the bus voltage within acceptable limits for guaranteeing system security, first and then assessing power quality. The voltage control is a key field in which several Transmission System Operators are currently investing resources to be well prepared in managing power systems with a high share of renewable energy sources, overcoming the drawbacks of the existing architectures. As is well known the voltage control is realized through a hierarchical structure, which is based on classical primary control, secondary control, and tertiary optimization. The secondary control is concerned with the regional level, implying proper coordination at both the geographical and temporal level. Due to its central role in power system operation, the secondary voltage control cannot be excluded from the effects of the dramatic changes that power systems are experiencing worldwide, even though regulators work by implementing well consolidated methodologies and strategies which show excellent performances. The motivation for this study in fact relies on the observation of some oscillatory phenomena in some areas of the Italian power system characterized by a high number of regulating resources highly coupled each other on the basis of the grid topology: despite these oscillatory phenomena are not so frequent, with the increasing of regulating resources enslaved by secondary regulation (such as renewable-based power plants) could potentially be worsened in the near future. Thus, in this paper, an optimal control strategy is proposed by tailoring a proper linear quadratic integral control which allows guaranteeing the desired profile for pilot buses voltage, ensuring a time response of aperiodic type without any oscillations. The aim of the proposed approach is to preserve the strengths of the existing secondary voltage regulation while enhancing the overall stability so enabling the progressive large penetration of renewable energy sources-based power plants and minimize the occurrence of oscillatory phenomena especially in highly electrically coupled areas. The robustness of the proposed regulation is verified first with respect to the WSCC 9-bus test system and successively on an actual regional area of Italian transmission network.

Closed-loop control of anesthetic state in nonhuman primates.

Research in human volunteers and surgical patients has shown that unconsciousness under general anesthesia can be reliably tracked using real-time electroencephalogram processing. Hence, a closed-loop anesthesia delivery (CLAD) system that maintains precisely specified levels of unconsciousness is feasible and would greatly aid intraoperative patient management. The US Federal Drug Administration has approved no CLAD system for human use due partly to a lack of testing in appropriate animal models. To address this key roadblock, we implement a nonhuman primate (NHP) CLAD system that controls the level of unconsciousness using the anesthetic propofol. The key system components are a local field potential (LFP) recording system; propofol pharmacokinetics and pharmacodynamic models; the control variable (LFP power between 20 and 30 Hz), a programmable infusion system and a linear quadratic integral controller. Our CLAD system accurately controlled the level of unconsciousness along two different 125-min dynamic target trajectories for 18 h and 45 min in nine experiments in two NHPs. System performance measures were comparable or superior to those in previous CLAD reports. We demonstrate that an NHP CLAD system can reliably and accurately control in real-time unconsciousness maintained by anesthesia. Our findings establish critical steps for CLAD systems' design and testing prior to human testing.

Model-based linear–quadratic–integral controller for simultaneous regulation of the current profile and normalized beta in NSTX-U

Achieving advanced scenarios that are characterized by steady-state operation, stable plasma confinement, and high-performance plasmas is one of the primary objectives of the National Spherical Tokamak eXperiment-Upgrade (NSTX-U). Active control of the plasma may be necessary to achieve these conditions. In particular, control algorithms that can simultaneously optimize the shapes and values of plasma profiles and scalars, respectively, may play a critical role in robustly achieving and sustaining these advanced scenarios. In this work, a model-based optimal control algorithm is developed for feedback control of the current profile in NSTX-U. The linear, finite-dimensional, control model is derived by discretizing and linearizing the magnetic diffusion equation in combination with empirical correlations for electron density, electron temperature, and noninductive current drives. The linear, time-variant model is then used for designing a linear–quadratic–integral (LQI) controller that is capable of regulating both the safety factor and the normalized beta around desired targets. The controller determines the neutral beam injection powers and the overall plasma current that are needed to achieve the desired current profile and normalized beta. The proposed controller is tested in higher-fidelity nonlinear simulations that employ 1D models for the evolutions of both current and temperature profiles using the Control Oriented Transport SIMulator (COTSIM). The closed-loop simulations show the effectiveness of the controller at shaping the safety factor in NSTX-U while achieving the desired normalized beta.

A robust variable-structure LQI controller for under-actuated systems via flexible online adaptation of performance-index weights.

This article presents flexible online adaptation strategies for the performance-index weights to constitute a variable structure Linear-Quadratic-Integral (LQI) controller for an under-actuated rotary pendulum system. The proposed control procedure undertakes to improve the controller's adaptability, allowing it to flexibly manipulate the control stiffness which aids in efficiently rejecting the bounded exogenous disturbances while preserving the system's closed-loop stability and economizing the overall control energy expenditure. The proposed scheme is realized by augmenting the ubiquitous LQI controller with an innovative online weight adaptation law that adaptively modulates the state-weighting factors of the internal performance index. The weight adaptation law is formulated as a pre-calibrated function of dissipative terms, anti-dissipative terms, and model-reference tracking terms to achieve the desired flexibility in the controller design. The adjusted state weighting factors are used by the Riccati equation to yield the time-varying state-compensator gains.

Experimental Validation of Adaptive Augmented LQI Control for a 2 DoF Helicopter

This paper presents a novel adaptive augmented linear quadratic integral (LQI) controller for a 2 degrees of freedom (DoF) helicopter to improve the closed-loop performance of the baseline controller even when the system contains unmodeled dynamics and exogenous disturbances. Although the LQI controller is widely used in aircraft control applications for its excellent reference-tracking capability and inherent robustness, the performance of the baseline LQI controller degrades when the aircraft model has unmodeled dynamics and external disturbances, which are inevitable in aircraft applications. Hence, to deal with the parameter uncertainty and unmeasured disturbances, we present an adaptive control framework using a model reference adaptive control (MRAC) scheme combined with the baseline LQI controller. The key aspect of the proposed control scheme is that the robustness of the closed-loop control system to deal with the matched uncertainty is enhanced by tracking error augmentation with the control law. Moreover, this work proves the asymptotic stability of the closed-loop system using the inverse Lyapunov function and Barbalat’s lemma. The efficacy of the adaptive augmented LQI is experimentally validated through hardware in loop (HIL) implementation on a laboratory scale 2 DoF helicopter workstation for several real-time test cases. Experimental results accentuate that the adaptive augmented control scheme can significantly improve not only the reference-tracking capability but also the robustness of the closed-loop system.

Bond graph modeling with linear quadratic integral control synthesis of a robotic digit in a human impaired hand for anthropomorphic coordination

The movement coordination of the robotic digit(s) with the central nervous system (CNS) and the natural digit(s) is a complex task that needs to be executed successfully in an anthropomorphic hand. The task is challenging to resolve because of the CNS. We developed a theoretical framework for the biomechanical model of a partially impaired human hand utilizing the bond graph modeling technique by incorporating inertia, muscle, and visco-elastic dynamics. The research presents a partially impaired human hand model with a robotic digit and four natural digits having 21 degrees of freedom. We formulated a linear quadratic Gaussian (LQG) integral control technique for the 21st-order model to regulate the flexion and extension movement of the robotic digit while considering the disturbances. We have simulated the modeling scheme in MATLAB/Simulink. The flexion and extension movement and the angular velocity of the robotic finger are shown to be following all the physiological constraints of a natural finger. The settling time is achieved at 1.6 seconds, with a maximum flexion angle of 0.135 rad. The sensitivity analysis shows that the model is robust against disturbances. The simulation results exhibit the application of this scheme toward upper limb rehabilitation and improvement in prosthetic and exoskeleton designs.

Data-Driven Model-Free Adaptive Control of Z-Source Inverters.

The universal paradigm shift towards green energy has accelerated the development of modern algorithms and technologies, among them converters such as Z-Source Inverters (ZSI) are playing an important role. ZSIs are single-stage inverters which are capable of performing both buck and boost operations through an impedance network that enables the shoot-through state. Despite all advantages, these inverters are associated with the non-minimum phase feature imposing heavy restrictions on their closed-loop response. Moreover, uncertainties such as parameter perturbation, unmodeled dynamics, and load disturbances may degrade their performance or even lead to instability, especially when model-based controllers are applied. To tackle these issues, a data-driven model-free adaptive controller is proposed in this paper which guarantees stability and the desired performance of the inverter in the presence of uncertainties. It performs the control action in two steps: First, a model of the system is updated using the current input and output signals of the system. Based on this updated model, the control action is re-tuned to achieve the desired performance. The convergence and stability of the proposed control system are proved in the Lyapunov sense. Experiments corroborate the effectiveness and superiority of the presented method over model-based controllers including PI, state feedback, and optimal robust linear quadratic integral controllers in terms of various metrics.

Robust real-time feedback algorithms for plasma kinetic control in advanced tokamak scenarios

Robust real-time control algorithms for tracking plasma kinetic parameters in advanced tokamak scenarios are developed based on linear state-space (LSS) dynamic models. The real-time control algorithms under study comprise the robust control, the linear quadratic integral control and the internal model control. The plasma models used in this work are restricted to LSS models identified from dedicated simulation/experimental data, though the proposed control algorithms can conveniently be extrapolated to broadly incorporate linear models obtained from first-principles plasma theory. The control objective is to track plasma kinetic parameters of interest to desired operating points in advanced tokamak scenarios by actuating additional heating & current drive systems in real-time. Plasma kinetic parameters involve the poloidal pressure parameter β p , the internal inductance , the average toroidal rotation angular speed and the electron temperature on axis while the actuators are the ion cyclotron resonance heating and lower hybrid current drive systems. In order to achieve enhanced control performance, two control layers are designed. The outer layer, i.e. an internal model-based proportional-integral actuator controller, operating on a fast timescale ( the energy confinement time τ E ) aiming at tracking the commands requested by the inner kinetic controllers, while the inner layer, i.e. a kinetic controller chosen from various alternatives, running on a slow timescale () is dedicated to tailoring plasma kinetic parameters. Simulation results for the experimental advanced superconducting tokamak (EAST) tokamak are provided and compared to show the capabilities of each control approach. Dedicated kinetic control experiments conducted in an H-mode scenario on EAST are reported as well. The advantages and limits of these control algorithms are discussed and summarised.

A comparative study of different active heave compensation approaches

Heave compensation is a vital part of various marine and offshore operations. It is used in various applications, including the transfer of cargo between two vessels in the open ocean, installation of topsides of an offshore structure, offshore drilling and for surveillance, reconnaissance and monitoring. These applications typically involve a load suspended from a hydraulically powered winch that is connected to a vessel that is undergoing dynamic motion in the ocean environment. The goal in these applications is to design a winch controller to keep the load at a regulated height by rejecting the net heave motion of the winch arising from ship motions at sea. In this study, we analyze and compare the performance of various control algorithms in stabilizing a suspended load while the vessel is subjected to changing sea conditions. The KCS container ship is chosen as the vessel undergoing dynamic motion in the ocean. The negative of the net heave motion at the winch is provided as a reference signal to track. Various control strategies like Proportional-Derivative (PD) Control, Model Predictive Control (MPC), Linear Quadratic Integral Control (LQI), and Sliding Mode Control (SMC) are implemented and tuned for effective heave compensation. The performance of the controllers is compared with respect to heave compensation, disturbance rejection and noise attenuation.

Linearized Quadratic Integral Control for Single-Phase Single-Stage Symmetric SLCHBC for Residential Solar PV Grid-Tied Applications

This paper deals with a single-phase single-stage seven-level cascaded H-bridge converter (SLCHBC) with LCL filter for residential solar photovoltaic (PV)-based grid-tied applications using linear quadratic integral control. An incremental conductance technique is used for maximum power point technique of PV array in the SLCHBC topology. The design of control is incorporated in direct and quadrature reference frame. The system performance is studied at different conditions to adhere the limit of the IEEE-519 standard and IEC-61727 standard.

Performance enhancement of multivariable model reference optimal adaptive motor speed controller using error-dependent hyperbolic gain functions

The main contribution of this paper is to formulate a robust-adaptive and stable state-space speed control strategy for DC motors. The linear-quadratic-integral (LQI) controller is utilized as the baseline controller for optimal speed-regulation, accurate reference-tracking and elimination of steady-state fluctuations in the motor’s response. To reject the influence of modelling errors, the LQI controller is augmented with a Lyapunov-based model reference adaptation system (MRAS) that adaptively modulates the controller gains while maintaining the asymptotic stability of the controller. To further enhance the system’s robustness against parametric uncertainties, the adaptation gains of MRAS online gain-adjustment law are dynamically adjusted, after every sampling interval, using smooth hyperbolic functions of motor’s speed-error. This modification significantly improves the system’s response-speed and damping against oscillations, while ensuring its stability under all operating conditions. It dynamically re-configures the control-input trajectory to enhance the system’s immunity against the detrimental effects of random faults occurring in practical motorized systems such as bounded impulsive-disturbances, modelling errors, and abrupt load–torque variations. The efficacy of the proposed control strategy is validated by conducting credible hardware-in-the-loop experiments on QNET 2.0 DC Motor Board. The experimental results successfully validate the superior tracking accuracy and disturbance-rejection capability of the proposed control strategy as compared to other controller variants benchmarked in this article.

A New Approach of EV Modeling and its Control Applications to Reduce Energy Consumption

Efficient energy usage of electric vehicles (EVs) is an important concern, especially in relation to the use of battery energy. This paper presents a strategy to make the use of battery energy more economical by employing a new modeling approach. One of the existing EV models, called the motor-vehicle model, considers the motor and the longitudinal vehicle dynamics. In this study, the motor-vehicle model is further simplified by ignoring the drag force, which will be referred to as the simple model. In addition, we propose a new approach of EV modeling by including the battery dynamics into a motor-vehicle model and taking into account the drag force. This model is named the Integrated Battery-Electric Vehicle (IBEV) model. In order to demonstrate the usefulness of the proposed model, controllers are designed using linear quadratic integral (LQI) control. Each controller is designed for several test cases based on a linearized integrated model, after which specific test cases are carried out on a nonlinear IBEV model. From these models, the energy consumption is analyzed based on several performance indices under a number of combinations of settings, i.e. battery type (lithium-ion or lead-acid battery) and shaft model (rigid or flexible shaft). Further, an LQI controller with a Kalman filter is designed and its performance is compared to LQI controllers with 4 th and 5 th order Luenberger observers. The simulation results shows that the use of IBEV model reduces energy consumption compared to the use of simple model in controller design, and that the LQI controller with Kalman filter can reduce the noise effect and is more economical than the controllers with other observers.

Designing optimal speed control with observer using integrated battery-electric vehicle (IBEV) model for energy efficiency

This paper develops an optimal speed control using a linear quadratic integral (LQI) control standard with/without an observer in the system based on an integrated battery-electric vehicle (IBEV) model. The IBEV model includes the dynamics of the electric motor, longitudinal vehicle, inverter, and battery. The IBEV model has one state variable of indirectly measured and unobservable, but the system is detectable. The objectives of this study were: (a) to create a speed control that gets the exact solution for a system with one indirect measurement and unobservable state variable; and (b) to create a speed control that has the potential to make a more efficient energy system. A full state feedback LQI controller without an observer is used as a benchmark. Two output feedback LQI controllers are designed; including one controller uses an order-4 observer and the other uses an order-5 observer. The order-4 observer does not include the battery state of charge as an observer state whereas the order-5 observer is designed by making all the state variable as the observer state and using the battery state of charge as an additional system output. An electric passenger minibus for public transport with 1500 kg weight was used as the vehicle model. Simulations were performed when the vehicle moves in a flat surface with the increased speed from stationary to 60 km/h and moves according to standard NEDC driving profile. The simulation results showed that both the output feedback LQI controllers provided similar speed performance as compared to the full state feedback LQI controller. However, the output feedback LQI controller with the order-5 observer consumed less energy than with the order-4 observer, which is about 10% for NEDC driving profile and 12% for a flat surface. It can be concluded that the LQI controller with order-5 observer gives better energy efficiency than the LQI controller with order-4 observer

Gear-shifting in a novel modular multi-speed transmission for electric vehicles using linear quadratic integral control

The efficiency of electric vehicles (EVs) can be improved by applying multi-speed transmissions (MSTs), while ensuring that gear-shifting is swift and smooth. This paper establishes a gear-shifting control algorithm for a novel MST, with the advantages of simplicity and modularity, designed for EVs. Firstly, the mathematical model of the proposed MST is derived. Next, the control algorithm developed for gear-shifting is clarified, which guarantees seamlessness and swiftness. The system under study is over-actuated, with end constraints on some control inputs. Therefore, for acceleration and jerk continuity, while satisfying the input terminal constraints, one input is suggested to be changed independently, based on a 2-3 blending polynomial. Then, the new fully-actuated system is controlled using a linear quadratic integral (LQI) controller, which is an extension of the linear quadratic regulator (LQR) for tracking problems. Simulation results indicate the effectiveness of the proposed control algorithm in the presence of unknown external disturbances.

Gain scheduling LQI controller design for LPV descriptor systems and motion control of two-link flexible joint robot manipulator

This paper proposes a gain scheduling linear quadratic integral (LQI) servo controller design, which is derived from linear quadratic regulator (LQR) optimal control, for non-singular linear parameter varying (LPV) descriptor systems. It is assumed that state space matrices are non-singular since many mechanical systems do not have any non-singular matrices such as the natural state space forms of robotic manipulator, pendulum and suspension systems. A controller design is difficult for the systems due to rational LPV case. Therefore, the proposed gain scheduling controller is designed without the difficulty. Accordingly, the motion control design is implemented for two-link flexible joint robotic manipulator. Finally, the control system simulation is performed to prove the applicability and performance.

(Basic Study by Control Simulation)

In order to improve running speed at the curving section, tilting control systems have been developed. As the tilting control system, there are the pendulum type and air spring type. In the research field of the tilting control using air springs, there are very few researches of simultaneous control between tilting and vibration. In this research, simultaneous control between tilting and vibration using air springs are aimed. For the simultaneous control, the linear quadratic integral control theory was used.

1A2-Q08 A Study of Force Control by Using Dual Arm Robot(Robots for Works (1))

A seven -link dual-manipulator robot with three-fingered hands is proposed with application of vision and impedance controls to produce human-like skills capability for the manipulation of automatic works. First, a stereo camera fixed on top of the robot provides an overview of position of objects placed on a worktable to move the arm closer to the objects. Two case studies have been assigned; in the first case study, the control system of robot hand based on LQI (Linear quadratic integral) control was designed to operate the hand for autonomous work, while the second case, a task of opening a beer bottle was designed to apply this method in the position based impedance control.

2C12 Adaptive Cruise Control in Consideration of Trade-off between Following Capability to a Leading Vehicle and Reduction of Fuel Consumption

This study aims at proposing a control method for an Adaptive Cruise Control (ACC) to improve not only following capability to a leading vehicle but also suppression of fuel consumption. It is said that a low acceleration drive contributes suppression of fuel consumption, but an excessive low acceleration drive causes worsening following capability. They should be considered all together because there is trade-off between them. A control law for an ACC to balance the following capability and the suppression of fuel consumption using Linear Quadratic Integral control is designed. To verify the control law, two ways of simulations are carried out. One is the simulation of two vehicles consisting of a leading vehicle and an ACC vehicle. The other is the simulations of a platoon of ten vehicles. It is demonstrated that the control law is effective for suppression of fuel consumption by comparison to the existing Two Degree Freedom (TDF) Control.

1A1-G08 双腕組立作業ロボットのマスタ・スレーブ制御(作業をするロボット)

In this paper, we propose Master-slave control of Dual-Arm Robot. The purpose of the study is developing a autonomous dual-arm assembler robot. The first of goal as assembly work is tightening up nut to bolt. In order to do the work, we work out a design of the end effector. The end effector is a robot hand having three fingers. The control system of the three-fingered robot hand is designed LQI control (linear quadratic integral control system). In addition, we operate Dual-Arm Robot which we use a master-slave system for. By using the master-slave system, we are able to operate Dual-Arm Robot even if we do not create complicated trajectory program. It is presented the master-slave system is effective for operability and following capability. The control system of the Dual-Arm Robot is designed PID control.