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In this paper, a data mining based methodology for process identification from historical data was proposed. Thereon, it considers the phases of process understanding, data collection, data prepara...

This article tackles the problem of high-accurate tracking of the stator currents of a six-phase induction motor in the presence of unknown dynamics such as unmeasurable rotor currents, parameter variation, and disturbances. Since the good features offered by sliding mode theory motivate the community of researchers on control, a time delay estimation based discrete-time super-twisting controller is proposed. First of all, an outer loop is carried out to regulate the speed and to generate the desired stator currents. Second, the inner loop, based on an indirect rotor field-oriented control, is executed based on the developed approach. The structure of the proposed method allows a precise approximation of the unknown dynamics and an accurate tracking and a fast convergence of the tracking error to a neighbor of zero. The design procedure and the stability analysis are detailed for the stator currents closed-loop system. Experimental tests have been performed on a six-phase induction motor to demonstrate the effectiveness of the developed discrete approach. In addition, the performances obtained are compared to the ones obtained using the discrete-time sliding mode with time delay estimation. The results obtained highlighted the satisfactory stator currents tracking performance in transient conditions and steady state and under different sampling times, parameters mismatch, and load and no-load conditions.

The bulk port operations are given a growing attention for their important role in the global supply chain in different industries (mining, energy ...). To guarantee their competitiveness, the efficient management of port logistics, including yard side management is crucial. In this paper, we consider a real-word storage space allocation problem at an export bulk terminal. We formulate the problem as a mixed integer linear program and we propose a heuristic method to solve large scale data sets. Both the model and the heuristic can help the yard planner to test different scenarios and provide better stock yard plan, which is a first step toward improving the management of port operation in the bulk terminal under study.

In industrial smelters, sulfuric acid is manufactured using the elemental sulfur in a series of three-unit operations: elemental sulfur oxidation, sulfur dioxide catalytic conversion, and sulfur trioxide absorption. The sulfur oxidation, which is the basic step in this process, is generally performed under a sulfur combustion furnace that ensures the production of the process gas stream, which will be the main supply stream to the other unit operations. In this paper, a dynamic model is developed based on the fundamental mass and energy balance, including the sulfur oxidation and the dynamic flow behavior aspects within the furnace. The obtained model is simulated in the Matlab/Simulink environment and data from an industrial plant were used to validate the model. The simulation results and the plant measurement comparison showed an accuracy of 96%, with a mean absolute error of 16.12 °C and a root mean square error of 23.27 °C. Afterwards, the effect of different operating conditions and disturbance parameters on the sulfur combustion furnace performance were studied. Finally, the relationship and a correlation between the temperature and sulfur dioxide molar fraction at the outlet of the furnace were investigated for industrial use.

This study deals with the problem of controlling rotor speed and stator currents of an asymmetrical six-phase induction machine with uncertain dynamics, disturbances, and unmeasurable rotor currents and proposes a robust non-linear variable structure controller. First of all, an outer control loop based on a proportional–integral regulator is performed to control the rotor speed and to construct the desired stator current references. Then, the inner loop is performed based on the proposed method that combines the time delay estimation method and discrete sliding mode control based on exponential reaching law. This structure allows an accurate and simple estimation of uncertainties and rotor currents, a high-tracking precision, a convergence of the stator currents to their known desired references in finite-time and chattering reduction. The design procedure is detailed step by step and the stability analysis and the convergence time are established for the current closed-loop system. Experimental work was carried out on an asymmetrical six-phase induction motor drive to show the effectiveness and performance of the proposed robust non-linear discrete method. The results obtained highlighted the good tracking performance of the stator currents.

In the mining industry, thickeners are used to increase density of slurries by removing water. When a thickener is in operation, the underflow slurry density should follow a given setpoint and stay inside a boundary layer. In general, thickeners are manually controlled. However, industrial experience has shown that manual control is not sufficient. For this reason, an advanced process control strategy is proposed in this paper. On the one hand, using historical data, a linear dynamic model of the studied thickener is developed. In this regard, data is collected, prepared, and data informativity is studied to ensure model identifiability and interpretability. On the other hand, a model predictive control is designed to control the process by manipulating the feed and the underflow slurry flowrates. The simulation results show that the method can be successfully used to control the underflow slurry density in the presence of feed variations and unmeasured disturbances.

Sulfuric acid is a basic chemical used intensively in many industrial processes. To produce the sulfuric acid, there are two major processes: the lead chamber process and the current contact process. The first step in the latter process consists of burning sulfur in the air to form sulfur dioxide. In this paper, modeling and simulation of an industrial sulfur burning unit are performed. For the modeling task, an adiabatic conversion reactor was used for the sulfur burner, a centrifugal pump for the liquid sulfur pump, and an air compressor for the air supply. To simulate the model, the Unisim Design R451 simulator was used. Then, the simulation results were validated using industrial data. In addition, a parametric study was performed to analyze the effects of the inputs' variations on the sulfur burner outlet. The proposed model can be used to develop a digital twin of the studied sulfur burner to perform real-time simulations and test new control and optimization strategies.

This work investigates the problem of controlling robot manipulators with matched and mismatched uncertainties. To this end, a robust backstepping combined with super-twisting controller is developed to guarantee the convergence of the joint position states to their desired references. The proposed control technique allows the rejection of the uncertainties while eliminating the sliding mode's famous drawback that is the chattering. Based on recursive Lyapunov function, sufficient condition is set to ensure the closed-loop system stability. Finally, simulation and experimental works were carried out respectively on a two degrees-of-freedom robot model and on the seven degrees-of-freedom ANAT modular robot to verify the performance and the robustness of the developed control strategy.

Flow behavior of solid-liquid flow systems depends on the solids’ properties, the carrier fluid and the interactions between the two phases. The solids’ properties of slurry pumping systems such as granulometry and density change as a function of time and location. The above-mentioned changes impact directly the slurry pumping flow rate. In this paper, a dynamic model of an industrial mixing tank with a slurry centrifugal pump is proposed. The dynamic model takes into account the different parts of the pump; the hydraulic part, the induction motor and the system head. A graphical method is then used to estimate the hydraulic part and the induction motor parameters. Regarding the system head, the model is generalized for both homogeneous and heterogeneous flows. The overall model is simulated using MATLAB/Simulink software and validated through a comparison between the results obtained and the real industrial data of a slurry mixing and pumping unit. Finally, the effects of density and level variations on the flow dynamic behavior are studied.

Tubular exchangers are among the most widely used exchangers in the industrial sector. It is essentially divided into two most common categories: shell and tube heat exchangers (STHE) and coaxial exchangers. It is also possible to consider a STHE as a sum of simple coaxial tubes, which greatly facilitates the understanding and modeling of STHE. Currently, the optimization of heat transfer in exchanger is a recurring problem for thermal engineers. Therefore, several numerical and experimental studies have been carried out. In this paper, the experimental and numerical study of heat transfer and dynamic behavior analysis of tubular heat exchanger (HE) is carried out in order to optimize the energetic performance of the exchanger. Experimentally, two configurations of co-current and counter-current exchangers have been investigated. Theoretically, the dynamic modeling and simulation of the HE was performed using Matlab/Simulink, Unisim-Design simulator, ANSYS-Fluent and Comsol multiphysics commercial software. The models' results were validated experimentally with very good agreement of 99%. Finally, the developed models are confronted to an industrial case of sulfuric acid cooling unit. The results obtained have a very good accuracy of 98.99% with the real plant data.

Multiphase induction generators are gaining popularity in wind energy systems for their robustness, reliability and fault-tolerant behavior when compared to the famous three-phase ones. This work proposes an advanced robust nonlinear control strategy for a multiphase induction generator in a variable speed wind energy conversion system. The considered structure in this paper consists of a six-phase induction generator and two conventional three-phase two-level voltage source converters. The stator currents of the structure are regulated using the proposed method that consists of a time delay estimation-based modified super-twisting. On one hand, and a proportional-integral regulates the speed in an outer control loop. On the other hand, the proposed method regulates the stator currents in an inner control loop. The stability analysis of the closed-loop error dynamics is proved using a quadratic Lyapunov function. Finally, numerical simulations have been carried out on a model of a real six-phase induction generator to show the good features of the designed method.

This paper proposes a super-twisting algorithm (STA) with time delay estimation (TDE) for the problem of high-accuracy tracking trajectory of robotic manipulators in the presence of uncertainties and unexpected disturbances. The TDE method is known for it capability to estimate uncertainties simply without an exact knowledge of the system dynamics. Using the estimated uncertainties, the control law is then designed based on STA to ensure robustness, finite-time convergence and chattering reduction. The stability analysis of the closed-loop system and the finite-time convergence are proved using Lyapunov theory. In order to show the effectiveness of the proposed method, simulations and experimental results were carried out on a 2-DOF rigid robot manipulator and on the 7-DOF ANAT robot arm, respectively.

One of the most efficient approaches to control a multiple degree-of-freedom robot manipulator is the virtual decomposition control (VDC). However, the use of the re- gressor technique in the conventionnal VDC to estimate the unknown and uncertaities parameters present some limitations. In this paper, a new control strategy of n-DoF robot manipulator, refering to reorganizing the equation of the VDC using the time delay estimation (TDE) have been investigated. In the proposed controller, the VDC equations are rearranged using the TDE for unknown dynamic estimations. Hence, the decoupling dynamic model for the manipulator is established. The stability of the overall system is proved based on Lyapunov theory. The effectiveness of the proposed controller is proved via case study performed on 7-DoF robot manipulator and com- pared to the conventionnal Regressor-based VDC according to some evalution criteria. The results carry out the validity and efficiency of the proposed time delay estimation- based virtual decomposition controller (TD-VDC) approach.

Control of uncertain nonlinear systems is one of the main topics in automation, control problem. However, uncertainties caused by uncertain parameters, load variations, unmodeled dynamics and external disturbances affect the control performance. This paper investigates the problem of high accuracy joint space trajectory tracking. A discrete-time second order sliding mode combined with time delay estimation is designed to make the joint positions track a desired trajectory with high accuracy. In addition, sufficient condition assuring convergence of the error to zero in finite time based on Lyapunov theory is presented. Experiments on a 7-DOF ANAT robot arm are presented to verify the performance of the proposed controller.

In this work, a time delay estimation based optimal conventional and second order sliding mode stator currents controller are proposed and compared for a six-phase induction machine fed by voltage source power converters. In a first step, the speed is regulated in an outer loop using a proportional-integral controller. Then, in a second step, the stator currents are controlled in an inner loop using the proposed methods. On one hand, the first method is a combination of time delay estimation with optimal first order sliding mode with exponential reaching law. On the other hand, the second method is a combination of time delay estimation with optimal super-twisting control. Based on Lyapunov theory, the stability of the stator currents closed-loop error dynamics is demonstrated and sufficient conditions of stability are determinate. As a case example, numerical simulations have been conducted on an asymmetrical six-phase induction machine to demonstrate the good features of the developed nonlinear controllers.

The inverse kinematic analysis is required in many technical applications. Due to the non linearity of the system, resolving the Inverse Kinematics (IK) for robotic system becomes more challenging problem. In this chapter, the problem of IK for medical application is faced, based on human lower limb as being the three arm robotic system depending on the physiological constaints. A system analysis is carried out specially in three dimensionnel space. The developed forward kinematic model leads to define the feasible workspace of the human leg in the considered configuration. A constructive algorithm to compute the optimal IK of robot system is outlined, based on human performance measure that incorporates a new objective function of musculoskeletal discomfort. The effectiveness of the proposed approach is tested, and the algorithmic complexity is finally discussed.

In this chapter, a robust backstepping sliding mode controller with time delay estimation method is presented for high accuracy joint space tracking trajectory of robot manipulators with unknown dynamics and external disturbances. The proposed method is based on backstepping scheme, on a switching function and on a time delay estimation in the final step. This structure is used to estimate unknown dynamics and disturbances, to adapt the switching gains in term of the error and its first time derivative and to reduce the control effort and the chattering phenomenon. Lyapunov theory is used to establish sufficient condition that ensures the stability of the closed-loop system. The proposed controller is simulated on a two-link robot and implemented in real time on the 7-DOF ANAT robot to show the effectiveness regarding unknown dynamics and external disturbances and chattering reduction.

This work investigates the problem of finite-time position and attitude trajectory of quadrotor unmanned aerial vehicle systems based on a modified second order sliding mode algorithm. The selected algorithm is a modified super-twisting with both nonlinear and linear correction terms. It ensures robustness against unknown dynamics and perturbations and allows fast finite-time convergence even when the trajectories of the considered system are far from the user-chosen switching surface. In addition, this algorithm is very attractive since it solves the major problems of the first and second order sliding mode, namely, the chattering phenomenon and the required unavailable information for practical implementation. To show the effectiveness of the used modified structure of the super-twisting algorithm, simulation results are presented for the considered quadrotor system.

The aim of this chapter is to presents a Kinematic analysis of a Cable-Driven Robot for rehabilitation use of human lower limb, by taking into account the constraints required by the entrainment system and the mobile platform (human leg). The proposed approach is focused on optimizing the manipulability and the human performance of the human leg, as being a physiologically constrained three-link arm. The obtained forward kinematic model leads to define the feasible workspace of the human leg in the considered configuration. Using an effective optimization-based human performance measure that incorporates a new objective function of musculoskeletal discomfort, and the mapping relation between articular joints actuator, length cables and articular joint mobile platform, the optimal inverse kinematic (IK) model is obtained.

A robust nonlinear backstepping technique with Lagrange’s extrapolation and PI compensator is proposed in this chapter for high accuracy trajectory tracking of robot manipulators with uncertain dynamics and unexpeted disturbances. The proposed controller is synthesized by using Lagrangian extrapolation method with PI compensator to estimate the uncertainties and disturbances and to deal with the effect of hard nonlinearities caused by the estimation error while nonlinear backstepping technique is used to ensure good tracking. The stability analysis is accomplished recursively using appropriate Lyapunov functions candidate. As a result, the proposed control technique shows better performances via experimental results on a 7-DOF robot arm in comparison with the classical backstepping and sliding mode control.

The object of this paper is to study the problem of robust stabilizability for a class of continuous-time Linear Systems with Markovian Jumps (LSMJ) and saturated input. Sufficient conditions for stochastic stabilizability with constrained control input are given in terms of Linear Matrix Inequalities (LMIs). The approach gives a direct expression of the linear state feedback controller that respects the condition of saturation. Also, the robustness of these systems for four types of structural uncertainties: (1) matching conditions, (2) norm bounded, (3) value bounded and (4) linear combinations is treated. Finally, numerical examples are given to illustrate the usefulness of the proposed results.

This paper investigates the problem of stator current control in presence of uncertainties and unmeasurable rotor current for a six-phase induction motor drive. An inner control loop based on a robust discrete-time sliding mode with time delay estimation method is proposed to ensure the finite-time convergence of the stator currents to their desired references while the proportional-integral controller is used for the outer speed control. Sufficient conditions are established to ensure the stability of the closed-loop system. Simulation results were carried out to verify the performance of the proposed robust control strategy for a six-phase induction motor drive.

The paper presents a robust sliding mode with time delay estimation method for controlling the attitude of a tri-rotor unmanned aerial vehicle (UAV) in presence of uncertainties and disturbances. The proposed control algorithm allows high accuracy tracking since a good disturbance estimation is provided using time delay estimation method and allows chattering reduction. The stability analysis of the closed-loop system is presented using the theory of Lyapunov. Finally, two numerical simulations are presented in the presence of disturbances to show the effectiveness of the proposed nonlinear control scheme.