Keywords: Fractional order systems, Control applications, Modeling and simulation
Abstract: In this work, we newly introduce a holistic approach to lung cancer therapy management by means of model-based predictive control. We propose a theoretical framework to link the proposed combination therapy pharmacological model (angiogenesis, immuno-, and radiotherapy) for characterizing the tumor volume dynamics with the fractional order impedance model for respiratory tissue properties. This is part of a model-based predictive control system technology, used to gather insight into therapy outcomes. The complete paradigm is using data-driven model estimations to update therapy management. Multiple layers of sampled information are used to accommodate various dynamics into the proposed holistic approach.

Keywords: Fractional order systems
Abstract: The usual approach to the integration of fractional order differential equations is based on fractional derivatives, mainly on the Caputo derivative and its renowned initial conditions. In this paper, thanks to an elementary counter example, we demonstrate that this usual methodology leads to wrong free response transients. The solution of this fundamental problem is to use the frequency distributed model of the fractional integrator and its distributed initial conditions. Based on this model, we solve the previous counter example and propose a methodology which is the generalization of the integer order approach.

Keywords: Estimations and identification, Fractional order systems, Signal processing
Abstract: This paper deals with wind turbulence modeling by using spectral analysis, in order to have a real-time wind simulator for dynamic models of parabolic tracking antennas. Indeed, such a realistic wind speed is needed to make dynamic models more complete and to design robust controls. The wind speed can be decomposed into two components: a long-term one representing the wind mean speed and a short-term one corresponding to the wind turbulence. Fast wind turbulence is a stochastic process and is difficult to model in time domain. For this reason, the models presented in this paper are based on the wind spectral characteristics. The most used Von Karman model well approximates the power spectral density of the wind turbulence. However, this model lacks precision in middle range frequency. Indeed, the Von Karman model was originially designed for aircrafts, and consequently for high altitudes and moving systems. In our case, tracking antennas are used under different conditions: low altitude and slow moving systems. Therefore, there is a need in more precisely modeling wind turbulence under these specific conditions. As Von Karman's model expression uses fractional calculus, other models with the same range of parameter number are proposed to better approximate the wind power spectral density by using Cole-Cole and Havriliak-Negami fractional models. The proposed fractional models will enable generating realistic random wind speed turbulence from a random white noise input.

Keywords: Fractional order systems, Linear and nonlinear systems
Abstract: This paper deals with the dynamic behavior of an acoustic tube of constant radius including the effect of visco-thermal losses due to the boundary layers in the vicinity of the walls. The knowledge model used in this work, called Webster-Lokshin 1D, is mono-spatial dependent. It characterizes the linear propagation of acoustic waves in axially symmetrical tubes taking into account visco-thermal losses. Thus, in an axisymmetric tube of constant section, the sound pressure and the sound flow rate are governed by the horn equation, known as Webster-Lokshin, and the Euler equation. This dissipative model includes a term that involves a fractional derivative. Two main contributions are presented in this paper. The first is an extension of the fractional expression used to take into account visco-thermal losses. The second is a development of a method allowing to pass from the initial fractional form of the input impedance Yin(s) of the acoustic tube, where the modes of the resonator appear implicitly through the periodicity from the tanh(.) function, to another fractional form YN(s) where, on the contrary, the modes of the resonator appear explicitly through the product of N fractional cells of order 2.

Keywords: Fractional order systems, Modeling of complex systems
Abstract: Fractional order models have proven to be a very useful tool for the modeling of the mechanical behaviour of viscoelastic materials. Traditional numerical solution methods exhibit various undesired properties due to the non-locality of the fractional differential operators, in particular regarding the high computational complexity and the high memory requirements. The infinite state representation is an approach on which one can base numerical methods that overcome these obstacles. Such algorithms contain a number of parameters that influence the final result in nontrivial ways. Based on numerical experiments, we initiate a study leading to good choices of these parameters.

Keywords: Estimations and identification, Control applications, Modeling and simulation
Abstract: In this paper, a hybrid adaptive observer is proposed for the alternating activated sludge process which belongs to a large class of nonlinear hybrid systems. Precisely, our goal is to estimate conjointly the unmeasured state: the ammonia concentration and the unknown parameter: the coefficient of performance of heterotrophic biomass. Numerical simulations are dedicated to highlight the good performances of the designed observer in the aerobic (nitrification) and the anoxic (denitrification) phases.

Keywords: Robust control and Hinfty control, Control applications, Robotics
Abstract: In this paper, a robust continuously implemented sliding mode controller is developed for the tracking control of two wheeled self balancing robot subject to terrain inclination and disturbances. Our design is based on the boundary layer approximation around the switching surface in order to reduce the chattering phenomenon. The proof of the closed loop system stability is illustrated through Lyapunov analysis. Simulation results highlight the efficiency of the designed controller applied on two wheeled robot in the presence of disturbances and terrain inclination.

Keywords: Estimations and identification, Control applications, Robotics
Abstract: In this paper, we deal with the problem of joint states and faults estimation for a quadcopter model. To solve this issue, appropriate state transformations are made to allow the decoupling of faults. A singular sliding mode observer is proposed for the subsystem containing the faulty measurements, in order to estimate the sensor faults. By using the latter estimated signals, we deduce the correct measurements which are subsequently exploited by a first order sliding mode observer whose the objective is to reconstruct states and actuator faults. Numerical simulations are carried out to show the effectiveness and the good performances of the proposed faults estimation method.

Keywords: Estimations and identification, Fault detection and Diagnostics
Abstract: In this paper, a novel fault reconstruction and estimation (FRE) approach is developed for a class of linear systems corrupted simultaneously by sensor and actuator faults. Contrary to standard strong detectability criteria usually considered in the literature, the FRE scheme that we propose is designed under weakened assumptions. Indeed, we assume that the considered system has less outputs than faults and more relaxed ``rank matching'' and ``minimum phase'' assumptions are made for the considered system. First, we apply a filter on the faulty outputs to obtain an appropriate extended state model for which we apply the technique of auxiliary outputs generation to relax the rank matching condition and we design a novel high gain sliding mode observer whose the role is to reconstruct conjointly auxiliary outputs and sensor faults. Then, we design an unknown input observer in cascade with the latter observer to estimate system state and finally we deduce an estimation approach to reconstruct actuator faults based on all estimated signals by the designed cascaded observers. Numerical simulations are carried out to illustrate the good performances of the proposed FRE scheme through an example of a steer-by-wire vehicle system.

Keywords: Fault detection and Diagnostics, Estimations and identification, Control applications
Abstract: This paper deals with the fault tolerant tracking multimodel control for nonlinear systems. The considered nonlinear system is modeled by an uncoupled state multimodel where its activation fonctions are depending on a new decision variable. The proposed active multimodel control strategy needs basically an actuator fault informations module and a control reconfiguration bloc. Therefore, a proportional multi-integral multiobserver, based on the uncoupled multimodel, is designed allowing a simultaneous state variables and actuator fault estimation. Sufficient conditions are developed and formulated by Linear Matrix Inequalities (LMIs) to study the stability of the proposed multiobserver. Then, a fault tolerant control strategy based on multicontrollers is elaborated to accommodate the actuator fault effect. Finally, a numerical example is performed to prove the performance of the proposed multiobserver and to evaluate the effectiveness of the proposed multimodel control strategy.

Keywords: Linear and nonlinear systems, Estimations and identification, Time-delay systems
Abstract: This note is devoted to a high gain observer design for a class of disturbed multi-input/multi-output uniformly observable systems with multirate sampled outputs exhibiting multiple long time-varying delays. The observer design is first carried out in the case where the outputs are sampled with the same sampling partition and long time-varying delay using an appropriate cascade observer design approach. The observer design is then extended to the case of multirate sampling with multiple time-varying output delays by using a high gain observer chained to a cascade predictor. There are two main contributions that are worth to be pointed out. Firstly, new sampling time instants are introduced in order to cast the problem of multiple arbitrarily long time-varying delays into a suitable problem dealing with arbitrarily long constant timedelays. Secondly, the exponential convergence of the observation error is established, up to a well-defined condition on the upper bound of the sampling partition diameters, in the free disturbance case. In the presence of bounded disturbances, an ultimate bound of the observation error is exhibited. The performance of the proposed observer and its main properties are highlighted through an example dealing with a flexible joint robot arm.

Keywords: Control algorithms implementation, Fuzzy and neural systems, Power systems
Abstract: Large frequency fluctuations are caused by the highly intermittent energy from renewable energy sources (RES) as well as the load disturbances of an autonomous microgrid (MG). In this paper, an isolated micro-grid comprising both controllable and uncontrollable sources is adopted. Fluctuation power of renewable sources and load influence in power balance then in frequency deviation. In order to minimize frequency deviation, a new hybrid algorithm based on grey wolf optimizer and cuckoo search (GWO-CS) is implemented for optimal tuning of Fuzzy PI controller gains in an autonomous microgrid. This study considers a variety of scenarios to illustrate the efficiency of the suggested controller. In this paper, a mathematical model of the studied microgrid was developed in MATLAB /SIMULINK. The simulation results in different scenarios confirm that the accuracy of the proposed strategy comparing results to some algorithms for optimal gains values of PI controller.

Keywords: Manufacturing systems, Autonomous Ssystems, Industrial control
Abstract: The manufacturing of customised products is a driver in the trend of incorporating intelligence in the system. This intelligence is required to enable the system to self-configure processes to meet the requirements of unique products. This work deals with the quality testing phase in a production system. A method of controlling testing functionality for the leak test process is presented utilising a multi-agent approach. A means of controlling agent execution by expressions is discussed. Two types of expressions; operational and conditional expressions are conceptualised. An experimental use case is demonstrated to validate the approach.

Keywords: Optimization, Control applications, Intelligent and AI based control
Abstract: Most swarm-based optimization algorithms rely on tens of agents and thousands of iterations to achieve a satisfactory level of optimization accuracy, which means that the number of Fitness Evaluations (FEs) is large. Usually, the FE operation for the Proportional-Integral-Derivative (PID) controller tuning task requires us to integrate the error signal for a step response, which is time-consuming. Thus, using swarm-based algorithms to tune PID controllers requires a large amount of time and cannot be implemented in online tuning or real-time tuning required for machines working in dynamic environments. This paper utilizes our recently proposed improved version of the Particle Swarm Optimization (PSO) algorithm enhanced by the PID architecture to tune PID controllers. To validate the efficiency of this new application, we compare its tuning performances with 7 other state-of-the-art swarm-based optimization algorithms on 4 different kinds of systems with the requirement that the time usage is less than 1 second. The experimental results show that the new algorithm achieves the best trade-off between accuracy and time consumption and could be employed as a potential candidate for online or real-time tuning of PID controllers in applications such as driverless cars or robot manipulators, where fast decision making is critical.

Keywords: Autonomous Ssystems, Control applications, Robotics
Abstract: The paper proposes a control algorithm for a differentially drive Wheeled Mobile Robot (WMR) whose model incorporates kinematic and dynamic equations of motion for driving the vehicle from an initial state to a desired target in a given work space. In the suggested control algorithm we apply particular structural properties of the system. The proposed control algorithms are based on the use of polynomial functions. However, the current approach can be extended and other set of linearly independent functions can be applied. By using tools from the dynamic programming framework one may contribute to the reduction in the energy consumption required to the accomplishment of the control objective. The approach is implemented successfully in point-to-point control for WMRs subject to a forward velocity restriction.

Keywords: Linear and nonlinear systems, Control algorithms implementation, Embedded Systems
Abstract: This paper deals with the state feedback control of singular continuous-time linear systems with discrete-time state measurement. The sampling time period is time varying. Intuitively, descriptor or singular description of linear systems is more general than conventional state space description. In particular, a descriptor form includes information about algebraic as well as dynamic constraints. The use of a dynamic event-triggering mechanism (DETM) allows to design a stabilizing controller based on a Lyapunov function which leads to a strict inequality condition. The DETM is shown to insure that the inter-event time interval is lower bounded and as a consequence it avoids the Zeno phenomena. It is demonstrated that a continuous time singular system in a sampled data closed loop framework could become badly posed unless the open loop is regular. In the case the open loop system is regular, it is shown that the fast component of the state system exhibits a discontinuous behavior. Simulations are presented to illustrate the obtained results.

Keywords: Control applications, Motion control
Abstract: In this paper we propose a Lyapunov redesign control method to improve the positioning of a Piezo-electrical actuator. This scheme is usually used with nonlinear systems that have matched disturbances. This actuator has a hysteric nonlinearity and it is canceled by modeling and inserting its inversion in the forward path. However, some of the nonlinearity remains and can be modeled as a matched disturbance. This is further reduced by feedback control. The suggested method fits well with this class of nonlinearity. Furthermore, the stability of the closed-loop system is established because a Lyapunov function is part of the controller design. Simulation results are presented with different trajectories to verify the effectiveness of this method. We also compared the results of the proposed method with other different methods.

Keywords: Control applications, Linear and nonlinear systems, Modeling and simulation
Abstract: Continuous Stirred Tank Reactor (CSTR) is an important installation in many chemical industrial processes. To achieve optimal productivity, this installation is maintained at very high conversion rates in safety exploitation conditions. Our paper addresses the stability of the stationary operating regime for the non-isothermal processes based on a nonlinear model of the CSTR. In addition, it proposes a closed loop control design for stability and performance for this type of processes. The mathematical model is computed and the geometrical conditions of stability for a non-isothermal reactor in a stationary plain are introduced. The detected conditions offer some stable operating requirements for the non-linear reactor model obtained for minor variations around a stationary point. For the linearized mathematical model, the necessary and sufficient conditions for stability of CSTR are demonstrated using the Lyapunov stability analysis. Finally, an adequate closed loop state control is proposed to avoid thermal avalanche phenomenon. The control solution ensures stability and provides high performances for the exothermic nonlinear reactor. A numerical study case and simulations confirm the effectiveness of this theoretical approach.

Keywords: Control applications, Guidance and control theory, Linear and nonlinear systems
Abstract: The aim of this research work is to investigate theoretical methods of Model Free-Control (MFC) for MIMO system. In the context of model-free control, three theoretical approaches are proposed to establish the model-free control law for three study cases; the first one concerns the SISO linear system, the second one the MIMO system using a decomposed MFC controller and the third one the MFC controller with the observer. This work shows the design of model free control (MFC) of an aircraft system with two inputs: the elevator and the throttle control and two outputs: altitude and velocity. The results of the simulation of the model are quite encouraging, knowing that we used a decomposed control approach using MFC for each output.

Keywords: Control applications, Power systems, Modeling and simulation
Abstract: The predictive torque control (PTC) has a similar structure to the direct torque control (DTC). However, instead of using a look-up switching table and hysteresis comparators, this technique evaluates the torque and stator flux in cost function and includes the inverter model in the control design and without the need for any modulation bloc. This paper investigates the sensorless predictive torque control. The association of a sensorless algorithm can reduce the cost of the drive and improves its reliability. In this work, dual observer structures will be incorporated into the main PTC scheme. The model reference adaptive system (MRAS) is proposed as a speed estimator. Then, this paper proposes an enhancement in the external speed control loop using a load disturbance observer (DOB). Over than the estimation of the applied load torque, this observer can ensure accurate speed tracking and can improve the disturbance rejection ability of the speed loop. The effectiveness of the presented algorithms is verified by a numerical simulation using MATLAB/Simulink software.

Keywords: Motion control, Control applications, Linear and nonlinear systems
Abstract: The successive generalized dynamic inversion (SGDI) control design methodology is used to control the linearized underactuated three degrees of freedom lateral motion of the F-16 fighter aircraft. The lateral kinematical state variables are analyzed first for the property of mutual direct controllability (MDC) to decide on the best SGDI control design configuration. The MDC analysis reveals that the yaw and sideslip angles do not form together an MDC subset of state variables. The MDC analysis also reveals that the sideslip and roll angles form together an MDC subset of state variables. However, it is shown that the SGDI control system design that is based on the roll and sideslip angles suffers from an excessively stable zero dynamics, which implies a large control effort and an undesirably fast closed loop transient response. Finally, the MDC analysis reveals that the roll and yaw angles form together an MDC subset of state variables and that the associated SGDI control design configuration is the most favorable in terms of the zero dynamics characteristics. Hence, the SGDI control design configuration that is based on the roll and yaw angles is exploited to synthesize a multivariable lateral stability augmentation system (SAS).

Keywords: Control applications, Intelligent and AI based control, Power systems
Abstract: In this article, we propose an adaptive neural network Backstepping control technique for the stand-alone doubly-fed induction generator (DFIG) based WECS. In order to control the voltage magnitude and frequency via the rotor converter, a new state-space model representation is developed by adding capacitive loads in parallel with the three-phase machine. The proposed technique is independent of the system model and guarantees the robustness against speed and load variations. The neural network is used to estimate online the nonlinear uncertainties of the system. The chosen architecture is a feed forward with one hidden layer, it is simple to implement and doesn’t require much computational force. The Lyapunov approach is used to ensure the stability of the proposed control and neural adaptation laws. The experimental tests are conducted on a 1.5kW DIFG using a 4.5 kW wind emulator and the dSPACE 1104 card. The obtained results show the effectiveness of our strategy compared with the previous works done on the same testbed using PI and the Backstepping controller.

Keywords: Linear and nonlinear systems, Mathematical systems theory
Abstract: In this paper, we study directly the asymptotic stability of a particular class of linear 2D discrete Fornasini-Marchesini model. The study is challenging mathematically because it is based on the explicit form of the solutions, therefore we limit the study to the case where model matrices are commutative. We propose a new conjecture to directly test asymptotic stability based on the eigenvalues of the model matrices and we support our conjecture with numerical evidence.

Keywords: Linear and nonlinear systems, Optimal control, Robotics
Abstract: In order to improve the healthcare services quality, various initiatives have been carried out to develop new assistive technologies such as wearable robots. This paper deals with the control of an actuated knee joint orthosis dedicated to assistive and rehabilitation purposes. The proposed control scheme is based on a nonlinear state feedback complied with a linear quadratic regulator (LQR) in a cascaded control architecture. The proposed control scheme has been validated in simulation for the control of an active orthosis in various operating conditions and compared with a PID controller. The obtained simulation results show clearly the efficiency of the proposed control scheme and its superiority with respect to the PID in terms of the tracking performance and the comfort of the user.

Keywords: Optimization, Control applications, Control algorithms implementation
Abstract: The dynamic operation of high-temperature fuel cells under temporally varying electric loads requires models for the electric stack power that depend on the supplied fuel mass flow, the electric current, the temperature of the supplied reaction media, and the stack temperature. This information is required to optimize the fuel consumption when tracking time-varying power profiles under the constraint of preventing fuel starvation. For that reason, the stack current needs to stay below the one that defines the maximum power point. However, due to the numerous influence factors, this point is only imperfectly known so that an online estimation with a corresponding quantification of the accuracy is necessary. In this paper, stochastic and interval-based modeling procedures are compared for an online control optimization on the basis of an experimentally validated dynamic SOFC model. The interval-based modeling combines nonlinear autoregressive models with a set-valued uncertainty quantification in a novel way.

Keywords: Fault detection and Diagnostics, Estimations and identification, Linear and nonlinear systems
Abstract: This paper deals with fault detection for discrete-time linear switched systems affected by actuator fault, additive disturbances and measurement noises. In order to improve the accuracy and to attenuate the effects of the unknown but bounded uncertainties, L_{infty} performance residual framer gains are computed by solving Linear Matrix Inequalities (LMI) which are formulated based on multiple quadratic Lyapunov functions under an average dwell time condition.