Model Control Design Research Articles

Integral barrier Lyapunov function-based three-dimensional low-order integrated guidance and control design with seeker's field-of-view constraint

As the strap-down seeker with its detector is fixed onto the body of the flight vehicle, its measurement is coupled with the information of the attitude motion of the vehicle's body, which results that the inertial line-of-sight (LOS) angular rate used in the traditional guidance laws cannot be measured. Besides, the process that the vehicle adjusts its attitude to realize the instantaneous overload command may cause the target to be outside the field-of-view (FOV) of the seeker. To deal with the FOV constraint and the lack of the inertial LOS angular rate, the novel body-LOS coordinate system based relative motion equations are derived, in which the derivative of attitude angular rates appears. Combined with the dynamics of attitude angular rates, the original low-order integrated guidance and control (IGC) design model with FOV constraint and the roll channel IGC design model are established. Furthermore, an integral Barrier Lyapunov function (IBLF) based three-dimensional low-order IGC scheme with the FOV constraint is proposed in this paper. Meanwhile, the adaptive algorithms are employed to estimate the square of the upper bound of the disturbance, which would be compensated in the IGC scheme to improve the robustness of the control system. Both system order and tuning parameters of the proposed low-order IGC algorithm dramatically decrease, and the design procedure is significantly simplified. With the aid of Lyapunov stability analysis, states of the IGC closed-loop system are proved to be uniformly ultimate bounded. Finally, extensive numerical simulations are carried out to validate the effectiveness and robustness of the newly proposed IGC scheme.

Parameter estimation based robust liquid level control of quadruple tank system — Second order sliding mode approach

This article proposes a liquid level control scheme for a quadruple tank process (QTP) plant. A robust control is proposed using higher order sliding mode (HOSM) control. The four tank setup has opposite tanks actuated by a single pump and unmeasured liquid outflow from upper tanks affecting the levels in the lower tanks. This renders nonlinearity in the dynamics with uncertain behavior. A novel experimentation based estimator is proposed for identification of the unknown control valve ratios of the plant. The estimated parameter is used for robust control design and state observer model. The unmeasurable states are estimated using a sliding mode observer and the required derivatives of liquid levels in the tanks are evaluated using a HOSM differentiator. The complete schema is tested in simulation and validated experimentally on a QTP setup.

Embedded model control for underactuated systems: An application to Furuta pendulum

The main goal of the paper is to test the Embedded Model Control (EMC) design and implementation on a typical underactuated apparatus, like the Furuta pendulum, by comparing experimental results with a Linear Quadratic Regulator (LQR). EMC can be considered as a disturbance rejection control strategy, since the state predictor is extended to explicitly include disturbance dynamics, in charge of predicting the uncertainty to be rejected by control law. Essential in EMC design is the separation between controllable and not controllable dynamics, a task which allows us to find the controllable channel of underactuated systems from the low-dimensional command to the whole system degrees of freedom (DF). Pursuing this objective, a rather generic method is shown, which is applicable to other underactuated systems. The result is a very simple controllable dynamics from the single pendulum command to pendulum DF arranged in a single series of controllable integrators. The neglected feedback channels, including the unstable gravity feedback, are treated as unknown thus posing a challenge to disturbance prediction and closed loop stability. Typical in EMC, closed loop eigenvalues are chosen to guarantee stability, a pre-requisite to performance. Experimental results point out effectiveness and advantage, with respect to LQR, of design and implementation under adverse conditions, due to a disturbance pulse, in which command saturates.

Hover flight control of X-shaped flapping wing aircraft considering wing–tail interactions

The dynamic modelling and attitude controller design of a flapping wing aircraft, Beihawk, were investigated in this study. The aircraft features of an X-shaped flapping wing configuration, tail control surfaces installed downstream of the main flapping wings for roll and pitch control, and a tail rotor for yaw control. Unsteady effects including partial leading edge suction, induced flow, and post-stall behaviour, were considered in the aerodynamic modelling. Flapping-wing-induced flow was found to be crucial to the tail control force generation for the utilized aircraft layout. A periodically time-varying wing–tail interaction model was thus established, based on which a double-loop controller was designed to enable stable hovering of the aircraft. The stability of the nonlinear hovering-based manoeuvre was studied by manifold theory, based on the proposed wing–tail interaction model. Simulations and flight experiments on Beihawk were conducted to verify the proposed theory. It was found that the controller considering wing–tail interaction effect enabled more stable hover flight compared with traditional PD controller. In addition, it was found a wider stability region can be obtained by a higher flapping-wing-induced flow velocity. The functions between this velocity and the influencing factors, such as thrust force, wing span and tail installation position, are also presented. Besides, a visual parameter stability boundary between the vertical and pitching velocity is given. Relevant conclusions are vital in active flight envelope protection.

Model development and controller design for DC–DC Boost converters in BCM with parallel cellular architecture

This paper deals with the development and evaluation of mathematical models related with Boost type DC–DC converters operating in Boundary Conduction Mode, including the expansion to a parallel cellular architecture considering the interleaved technique. Initially, an average value-based approach was applied to derive the mathematical models for the three available modes of operation (CCM, DCM and BCM), employing its classic form, which considers the duty cycle disturbance while maintaining a constant switching frequency, and its adherences in describing the behavior due to the BCM’s frequency variation. Afterward, an innovative model based on the disturbance in the switching period is proposed for BCM condition. The proposed models were analyzed in different complexity levels, divided into two transfer function orders, referred as reduced and full order. The developed models considering the operation of a single converter were extended to a parallel architecture of N converters. The modes of operation in DCM and BCM were adopted to allow the developed models’ analysis, as well as evaluate and design the converter’s operation, where PI controllers were employed. The simulations were executed in the MATLAB software’s Simulink environment, with the system implemented by models through subsystems and embedded functions and by switching circuits with assistance of the SymPowerSystems toolbox.

Asymptotic tracking position control with active oscillation damping of a multibody Mars vehicle using two artificial augmentation approaches

The Valles Marineris Explorer Cooperative Swarm navigation, Mission and Control research project aims to explore the Valles Marineris canyon system on Mars with, among others, multibody rotary-wing unmanned aerial vehicles (UAVs) comprising of a hexrotor system and a helium-filled balloon being attached to it by means of a rope. In this paper, we develop a high-fidelity closed-loop control system in MATLAB® and Simulink™ to present the application of an adequate flight controller guaranteeing (1) asymptotic tracking position control of the multibody flight system, (2) suppression of the balloon’s swinging motion in forward flight case, and (3) stabilization of the rope angle around its equilibrium for steady-state conditions. Applying feedback linearization for the outer loop and analytical backstepping for the inner loop of a nonlinear cascaded control design model of the hexrotor system, we propose an extension of the baseline flight controller by two artificial augmentation approaches to cope with the balloon dynamics. Basically, by utilizing oscillation damping feedbacks of the uncertain plant which are applied as additional commands to either the inner or the outer loop’s reference model. Simulation results are presented for an eight-shaped flight maneuver at the bottom of Valles Marineris proving that the augmentation units increase the flight controller capabilities to suppress modeling errors artificially—without changing the baseline control laws. The augmentation units actively damp the balloon motion in the forward flight case for non-steady-state conditions to counteract the rope oscillations and finally stabilize the rope angle around its equilibrium, so that the Mars vehicle is able to reach a steady-state in position when its extraterrestrial mission profile is successfully completed.

Internal model control design based on approximation of linear discrete dynamical systems

In this paper, a new direct discrete approximation based internal model control design is proposed to the linear discrete dynamical systems. The approximation method is used to determine an accurate and stable reduced-order model for the considered original higher-order discrete-time system. The method involves an enhanced Differential Evolution algorithm to ascertain the stable denominator polynomial coefficients, and the preferable reduced numerator polynomial coefficients are evaluated by using the improved discrete multi-point Padé approximation approach. The method deploys on discrete step integral square error minimization between the original dynamical system and the approximated model, together with retaining their discrete impulse response energy values. The approximated model has been considered an internal (predictive) model and proceeds with an optimal internal model controller design to improve the discrete dynamical system behaviour according to the reference input/the set point. The controller's best performance is attained by tuning the single filter parameter ′λ′ by minimizing the integral square error between the reference input and the actual output of the dynamical system using the enhanced differential evolution algorithm. The acceptability and applicability of the proposed process reduction-based controller design have been validated on a single-input single-output supersonic jet engine inlet dynamical model. The controller robust study is conducted by inserting 10% disruption uncertainty in the system dynamical model poles and zeros. The method has also been extended to the discrete multi-input multi-output dynamical model of the single machine infinite bus power system to develop an optimal internal model control-based power system stabilizer. The simulation results showing better reference input tracking, comparison of performance indices, and also highlight the efficacy of the proposed controller design.

Fractional order sliding mode control based on single parameter adaptive law for nano‐positioning of piezoelectric actuators

A fractional order sliding mode control (FOSMC) based on single parameter adaptive law for nano-positioning of Piezoelectric Actuators (PEAs) is proposed. First, the Bouc–Wen (B–W) model is used to describe the hysteresis of the nano-position platform based on PEAs, which provides a mathematical model for the subsequent controller design. Then, theoretical support is provided to design the FOSMC based on adaptive law of different parameters, which are proposed for the displacement tracking problem of PEAs, and the position error convergence is also proved. Moreover, the core parameters of FOSMC based on single parameter adaptive law are identified by hybrid differential evolution (HDE) and adaptive differential evolution (ADE), which require considering the relationship between the scaling factor and the cross-probability factor. Finally, experiments have been conducted with the displacement signals mixed with multiple frequencies and multiple amplitudes and the results obtained from them show that the proposed control scheme can produce a faster response and smaller tracking errors in PEAs system as compared to traditional control algorithms.

Regional Pole Placers of Power Systems under Random Failures/Repair Markov Jumps

This paper deals with a discrete-time stochastic control model design for random failure prone and maintenance in a single machine infinite bus (SMIB) system. This model includes the practical values of failure/repair rate of transmission lines and transformers. The probability matrix is, therefore, calculated accordingly. The model considers two extreme modes of operations: the most reliable mode and the least reliable contingency case. This allows the control design which stochastically stabilizes the system under jump Markov disturbances. For adequate transient response, the proposed state feedback power system stabilizer (PSS) achieves a desired settling time and damping ratio by placing the closed-loop poles in a desired region. The control target should also be satisfied for load variations in either mode of operation. A sufficient condition is developed to achieve the control objectives via solving a set of linear matrix inequalities (LMI). Using simulation, the performance of the designed controller is tested for the system that prone to random failure/maintenance under various loading conditions. Simulation results reveal that the closed-loop poles reside within the desired region satisfying the required settling time and damping ratio under the aforementioned disturbances. The contributions of the paper are summarized as follows: (1) modeling of transition probability matrix under Markov Jumps using practical data, (2) designing a controller by compelling the closed poles into the desired region to achieve adequate dynamic performance under different load varying conditions.

VIRTUAL COMMISSIONING, DIGITAL TWIN AND CONTROL STRATEGIES APPLIED IN THE INDUSTRIAL ROBOT PUMA 560

The objective of this work is the evaluation, through computational simulation, of the performance and behavior of the PUMA 560 robot under different types of motion controllers. Nominal models for control design were obtained through linearization of the robot dynamic model considering selected points of operation through Denavit-Hartenberg (DH) modeling and convention. In addition to a PID joint decentralized control law and a computed torque control law that had already been implemented in the simulator, it was implemented a predictive control law and a robust control law as well. Tuning of the parameters of these control laws were performed for the Puma 560 robot and each control system was evaluated through simulation. Results about the controller design and the control system simulation were collected and discussed. Completing this study aimed to analyzing a six degree of freedom robot manipulator motion control taking in account performance and robustness aspects, it was chosen a particular structure and introduced a force control loop; this controller design and simulator extension allowed an evaluation of some force control aspects and digital twin.

Analysis of Transient Interactions between a PWR Nuclear Power Plant and a Faulted Electricity Grid

This paper presents the transient stability analysis of a pressurised water-type nuclear power plant following faults and disturbances affecting the electricity grid to which it is connected. The modelled nuclear plant consists of various integrated subsystems, such as core neutronics and thermal-hydraulics, piping and plenum, pressuriser, steam generator, turbine, governor, and dynamics shaft, in addition to the turbine-speed controller. The nonlinear nuclear power plant model is linearised at the operating point to acquire a linear model for controller design. The turbine-speed control loop effectively enacts a closed-loop implementation of the nuclear power plant connected to the electric grid. The various transient stability enhancement components such as the power system stabiliser, static var compensator, and static synchronous compensator are employed to test performance during severe contingencies. The interaction between the nuclear power plant, electric grid, and protection system is studied under various scenarios such as single-phase fault, three-phase fault, and permanent load loss. The performance of the nonlinear plant is further observed during load-following operation. The dynamic behaviour of the overall system is analysed using simulations in the MATLAB/Simulink/Simscape environment.

Identification, Uncertain Modelling, and Robust Control of Embedded Systems

This paper presents a methodology embodying identification procedures, uncertain modeling, and robust control design of embedded multivariable control systems. Concerning the identification, this methodology involved the determination of probabilistic uncertainty bounds for multivariable plants based on the black box or gray box identification. The bounds obtained were used in the derivation of an uncertain model in the form of upper Linear Fractional Transformation (LFT). This model was used in the robust control design implementing μ-synthesis. The problems arising on the different design stages were illustrated by an example presenting the embedded robust control of a two-input two-output analog model. The plant was identified by using black box and gray box identification methods that produced the necessary information to develop the corresponding uncertainty models. Two discrete-time robust controllers relevant to the two types of identification were designed and embedded in the physical system. Simulation results for the embedded closed-loop system and experimental results obtained by using the robust controllers were compared.

A simple active carbody roll scheme for hydraulically actuated railway vehicles using internal model control

The paper presents the first classical internal model control (IMC) design in the context of railway carbody roll control. We propose a simple control approach for a recent hydraulically actuated vehicle body roll concept that offers limited carbody roll. The IMC approach addresses both preview- and nulling-type tilt setups, highlighting related benefits and limitations. The design provides a model simplification process that facilitates PI and PID-type control structures without the need for complex optimization. A simple, yet practical, tool for the industrial rail rolling stock engineer in vehicle control design is offered. Vehicle roll performance is rigorously studied on the deterministic (curving acceleration response) and stochastic (ride quality) trade off. Simulations are performed on an in-house multibody dynamics software package employing a realistic nonlinear railway vehicle model and allow to appropriately assess the performance of preview and nulling type tilt performance. The results obtained confirm that preview tilt control offers the better tilt performance as it utilizes a tilt command reference, and highlighted that nulling-type tilt performance remains at a relatively comparable level with the former.

Reactive control of wave energy devices – the modelling paradox

The implementation of energy maximising control systems (EMCSs) in wave energy converter (WEC) devices is an important step towards commercially viable operation of WECs. During the design stage of such EMCSs, linear hydrodynamic models are commonly used and are, in fact, the most viable option due to the real–time computational requirements of optimisation routines associated with energy-maximising optimal control techniques. However, the objective function of EMCSs, i.e. maximising the generated power by exaggerating WEC motion, inherently violates the underlying assumption of the linear hydrodynamic control design models, i.e. small amplitude device motion (compared to the device dimensions). Consequently, the linear models, used as a basis for EMCSs, in fact conspire to violate the very assumption upon which they were built - hence leading to a modelling paradox. It is important to evaluate WEC controllers in realistic physical or numerical environments, to gain knowledge of the disparity between the performance prediction from the EMCS design and performance evaluation models. This paper presents a comprehensive assessment of the performance prediction by a linear and non–linear hydrodynamic model of three different EMCSs, implemented in two different WEC structures, in an attempt to quantify the severity of this modelling disparity, or paradox.

Steering model identification and control design of autonomous ship: a complete experimental study

ABSTRACT Steering ship models are important for the study of autonomous ship manoeuverability and design of ship motion control system. It is always a difficult task to find the mathematical model by first principle as it needs prior knowledge of hydrodynamic derivatives. The input–output-based system identification theory can be used to establish system mathematical models. A solution is offered by developing a Wi-Fi-based self-propelled, autonomous system for a ship model with Internet of Things (IoT) capabilities to perform manoeuvering and seakeeping tests in indoor environment without any complex mechanical structure, viz. following bridge. The developed autonomous on-board system equipped with main computer, suitable electronics, sensors, data acquisition system and Wi-Fi-based communication system. The developed system offers a cost effective, modular and portable solution to perform hydrodynamic studies of different hull form without incorporating major changes in the system. The use of IoT makes the data accessible to a naval architecture in real-time to analyse the motion response of the ship in different wave conditions and enables to implement the digital twin to simulate the real field scenario. Input–output-based model identification experiments such as turning circle and zig-zag tests are conducted to estimate the first-order steering model parameters and is further extended to design and implementation of a classical proportional–derivative-based steering control. The design is described in this paper with details of implementation on a demonstration oceanographic coastal research vessel. It illustrates the excellent communication between shore station computer and the on-board system on a wire-free model with robust control and exhibiting all the motion behaviour and dynamic effects. Experiments performed in wave basin in different wave conditions validate the efficacy of the proffered method.

A global optimization technique for modeling and control of permanent magnet synchronous motor drive

In this paper, model order reduction and controller design of permanent magnet synchronous motor (PMSM) drive has been carried out with the help of a firefly-based hybrid metaheuristic algorithm in the complex delta domain. Two relatively new algorithms, namely, the firefly technique and an adaptive version of the flower pollination method are combined to develop an effective global optimization approach. Originally, the permanent magnet synchronous motor drive constituting speed and current controllers yields a higher-order system reduced to a lower-order model via an identification approach applied in signal processing techniques. The reduced-order model, cascaded with a PI controller is then matched with a reference model approximately to estimate the unknown controller parameters. The tuned controller parameters using the delta operator method almost resemble those obtained by the continuous-time system. Thus, a unified framework of controller design for the drive system is also established. Thus, the hybrid intelligent algorithm is employed for order reduction and controller parameter estimation of PMSM drives. A case study can also be considered for the speed control of switched reluctance and brushless motor drives are widely predominant in several domestic and industrial applications.

Coordination of low-power nonlinear multi-agent systems using cloud computing and a data-driven hybrid predictive control method

This paper studies the coordinated control issue for low-power nonlinear multi-agent systems (LNMASs). To improve the calculation ability of the LNMAS for massive real-time data and alleviate the communication burden of individual agents, cloud computing systems are employed to establish the multi-agent system instead of low-power microprocessors. To reduce the adverse effects caused by the network delays and data loss in all communication channels and coordinate the outputs of all agents, a novel data-driven networked hybrid predictive control (DDNHPC) method using only input and output information of the system is proposed. In the DDNHPC method, the nonlinear agents are described as dynamic data models for controller design. Based on the dynamic data models, the hybrid predictive method including direct output predictions and further switching output predictions is designed to establish the active outputs coordination relationship among all agents. Simulation and cloud-based experimental examples are performed to illustrate the effectiveness and applicability of the proposed method. The achievement also provides a solution to implement the coordination of large-scale intelligent manufacturing.

Adaptive Individualized Modeling From Limited Clinical Data for Precise Anemia Management

It is challenging in practice to achieve a steady-state value for external human recombinant erythropoietin (EPO) dosage to be administrated to maintain Hemoglobin (Hb) level within the desired range of 11–12 g/dl based on population-based models for anemia management due to inter-and intra-variability of the patients. On the other hand, Pharmacokinetic (PK) and Pharmacodynamic (PD) characteristics can vary for the patients over the course of treatment due to aging and other life changes. To address the inter-and intra-variability in anemia management, the semi-blind robust identification approach is proposed to obtain individualized patient models using limited number of clinical patient data. Semi-blind robust identification utilizes the effect of the initial condition during system identification to reduce the identification error. To reflect the patient’s true dose-response relation as time passes and ensure the suitability of the individualized model for the controller, the model (In)validation technique is discussed to provide appropriate mathematical evidence about the suitability of the individualized model for dose prediction and controller design via testing it on new clinical data of the particular patient. One-step-ahead prediction results are shown for identified individualized patient models. The individualized patient models provide decision support to the clinicians about EPO dosage to avoid undershoot or overshoot of Hb level. Minimum mean squared error (MMSE) is calculated for the predicted values obtained by the models identified using semi-blind robust identification with and without the model (In)validation against clinically acquired EPO-Hb data.

Simulation and Arduino Hardware Implementation of DC Motor Control Using Sliding Mode Controller

The research proposed an alternative controller to control the Direct Current (DC) Motor using a sliding mode controller (SMC) in Matlab Simulink simulation and Arduino hardware implementation. The proposed controller, SMC, was designed using the system model (equivalent control) and Lyapunov control design (also to prove the stability). The sliding mode controller had a better response than PID Controller, with no overshoot response in the simulation result. In the Arduino hardware implementation result, the augmented system could reach the reference but has an oscillation and chattering effect in the control signal. The chattering could be reduced by modifying the switching control. Comparing with PID, SMC had a better response with no overshoot. Thus, the SMC could be used as an alternative controller for the DC Motor.

Simulation and Arduino Hardware Implementation of DC Motor Control Using Sliding Mode Controller

The research proposed an alternative controller to control the Direct Current (DC) Motor using a sliding mode controller (SMC) in Matlab Simulink simulation and Arduino hardware implementation. The proposed controller, SMC, was designed using the system model (equivalent control) and Lyapunov control design (also to prove the stability). The sliding mode controller had a better response than PID Controller, with no overshoot response in the simulation result. In the Arduino hardware implementation result, the augmented system could reach the reference but has an oscillation and chattering effect in the control signal. The chattering could be reduced by modifying the switching control. Comparing with PID, SMC had a better response with no overshoot. Thus, the SMC could be used as an alternative controller for the DC Motor.