Control Toolbox In Matlab Research Articles

Control of a Reactive Distillation Process Using Model Predictive Control Toolbox of MATLAB

This research work has been carried out to investigate the application of the Model Predictive Control Toolbox contained in MATLAB in controlling a reactive distillation process used for the production of a biodiesel, the model of which was obtained from the work of Giwa et al.1. The optimum values of the model predictive control parameters were obtained by running the mfile program written for the implementation of the control simulation varying the model predictive control parameters (control horizon and prediction horizon) and recording the corresponding integral squared error (ISE). Thereafter, using the obtain optimum value of 5 and 15 for control horizon and prediction horizon respectively as well as a manipulated variable rate weight of 0.025 and an output variable rate weight of 1.10, various steps were applied to the setpoint of the controlled variable and the responses plotted. The results given by the simulations carried out by varying the model predictive control parameters (control horizon and prediction horizon) for the control of the system revealed that optimizing the control parameters is better than arbitrary choosing. Also, the simulation of the developed model predictive control system of the process showed that its performance was better than those used to control the same process using a proportional-integral-derivative (PID) controller tuned with Cohen-Coon and Ziegler-Nichols techniques. It has, thus, been discovered that the Model Predictive Control Toolbox of MATLAB can be applied successfully to control a reactive distillation process in order to obtain better performance than that obtained from a PID controller tuned with Cohen-Coon and Ziegler-Nichols methods.

A Novel Iterative Method To Approximate Structured Singular Values

A novel method for approximating structured singular values (also known as $\mu$-values) is proposed and investigated. These quantities constitute an important tool in the stability analysis of uncertain linear control systems as well as in structured eigenvalue perturbation theory. Our approach consists of an inner-outer iteration. In the outer iteration, a Newton method is used to adjust the perturbation level. The inner iteration solves a gradient system associated with an optimization problem on the manifold induced by the structure. Numerical results and comparison with the well-known MATLAB function mussv, implemented in the MATLAB Control Toolbox, illustrate the behavior of the method.

Positioning Control of Electrical Discharge Machining Device for Improved Transient Response Performance

Electrical discharge machining (EDM) has experienced steady growth in engineering applications since its emergence. This paper has presented positioning control of electrical discharge machining (EDM) device for improved transient response performance. A model dynamic of a DC servomotor responsible for positioning tool electrode on a workpiece was obtained. The controlled variable is the angular shaft position which was made the output of the process in the model transfer function. A proportional integral and derivative (PID) compensator was designed using robust response time tuning method with interactive, adjustable performance and robustness of the Matlab control tool box. The designed compensator was integrated with the servomotor to form a closed loop control system. Simulations were performed for uncompensated and compensated conditions of the machining process. The results obtained indicated that with the compensator in the loop, the transient response performance of the servo positioning was largely improved.

New stability criterion of neural networks with leakage delays and impulses: a piecewise delay method

This paper analyzes the global asymptotic stability of a class of neural networks with time delay in the leakage term and time-varying delays under impulsive perturbations. Here the time-varying delays are assumed to be piecewise. In this method, the interval of the variation is divided into two subintervals by its central point. By developing a new Lyapunov-Krasovskii functional and checking its variation in between the two subintervals, respectively, and then we present some sufficient conditions to guarantee the global asymptotic stability of the equilibrium point for the considered neural network. The proposed results which do not require the boundedness, differentiability and monotonicity of the activation functions, can be easily verified via the linear matrix inequality (LMI) control toolbox in MATLAB. Finally, a numerical example and its simulation are given to show the conditions obtained are new and less conservative than some existing ones in the literature.

Impulsive controller design for exponential synchronization of delayed stochastic memristor-based recurrent neural networks

In this paper, impulsive synchronization of stochastic memristor-based recurrent neural networks with time delay is studied. One can find that the memristive connection weights have a certain relationship with the stability of the system. Based on the drive-response concept, the stochastic differential inclusions theory and the Lyapunov functional method with the impulsive delay differential inequality technique was established to guarantee the impulsive synchronization of memristor-based recurrent neural networks with stochastic effects. The obtained sufficient conditions can be checked easily by Linear Matrix Inequalities (LMI) Control Toolbox in MATLAB. Finally, a numerical example is given to illustrate the effectiveness of the theoretical results.

Synchronization of fuzzy bidirectional associative memory neural networks with various time delays

The problem of synchronization for fuzzy bidirectional associative memory (BAM) neural networks (NNs) with various time delays is formulated and investigated. The various delays consist of discrete delays, unbounded distributed delays and constant delay in the leakage term (i.e. ‘leakage delay’) are considered. Then, some sufficient conditions are presented to guarantee the global asymptotic stability of the error dynamical system by using Lyapunov–Krasovskii functional and linear matrix inequality (LMI) method. As a result, we achieved synchronization of master-slave (drive-response) fuzzy BAM NNs systems. Even, if there is no leakage delay, the obtained results are less restrictive to some known sufficient conditions. Moreover, the proposed results do not require the boundedness, differentiability and monotonicity of the activation functions, which can also be easily checked via the LMI solver in robust control toolbox in Matlab. Furthermore, using a parameter-dependent Lyapunov function approach the synchronization problem for polytopic uncertain fuzzy BAM NNs with various time delays is considered. The parameter uncertainties under consideration are assumed to belong to a fixed convex polytope. Finally, two numerical examples and simulations are given to illustrate the effectiveness of the derived theoretical results.

Improved stability and [formula omitted] performance for neutral systems with uncertain Markovian jump

This paper addresses the problem of the delay-dependent stability and H∞ performance for neutral systems with uncertain Markovian jump; the uncertainty of Markovian jump refers to the partial information on transition probability. In order to highlight the methods for the analysis of the systems, the neutral delay is assumed same as discrete delay. By the novel constructed Lyapunov functional, combining with the delay decomposition technique and free matrices, and using the new inequality rather than the Jensen inequality, the delay-dependent stability conditions are firstly obtained for the two kinds of neutral dynamical systems. Based on the stability condition, the H∞ performance result for the systems with Markovian jump is secondly provided. All of the delay-dependent stabilization results are formulated in terms of LMIs, which can be easily checked by the LMI control toolbox in Matlab. Finally, two numerical examples are given to show the validity and potential of the developed criteria.

Study on Control of First Order Plus Delay Using Smith Predictor

This paper presents the implementation of Smith predictor structure for the control of a first order plus delay time process. Water heater for vacuum distillation apparatus is studied, the open loop transfer function shows a first order plus delay time. The control system is analyzed using open loop Bode plot and root locus method through “sisotool” in MATLAB control tool box. The Smith predictor control design carried out using MATLAB (7.11.0) command windows. The controller gain is found to be 96.3 and the integral time 256.4

Computation of the Structured Singular Value via Moment LMI Relaxations

The Structured Singular Value (SSV) provides a powerful tool to test robust stability and performance of feedback systems subject to structured uncertainties. Unfortunately, computing the SSV is an NP-hard problem, and the polynomial-time algorithms available in the literature are only able to provide, except for some special cases, upper and lower bounds on the exact value of the SSV. In this work, we present a new algorithm to compute an upper bound on the SSV in case of mixed real/complex uncertainties. The underlying idea of the developed approach is to formulate the SSV computation as a (nonconvex) polynomial optimization problem, which is relaxed into a sequence of convex optimization problems through moment-based relaxation techniques. Two heuristics to compute a lower bound on the SSV are also discussed. The analyzed numerical examples show that the developed approach provides tighter bounds than the ones computed by the algorithms implemented in the Robust Control Toolbox in Matlab, and it provides, in most of the cases, coincident lower and upper bounds on the structured singular value.

Optimal Strategy for Multi-product Inventory System with Supplier Selection by Using Model Predictive Control

In this paper, we compute the optimal strategy to control the stock level of a multiproduct inventory system and to select the supplier from several alternatives such that the total cost is minimum by using the model predictive control. The dynamic of this system will be modeled into linear time invariant state space. Furthermore, to control the stock level and to select the supplier in simultaneous way, the model predictive control will be applied which minimizes an objective function subject to a dynamic equation. This dynamic equation presents the dynamic stock level whereas the objective function of this problem presents the total cost of the supplier selection problem as well as the gain between the stock level and the desired level given by the decision maker. We give the numerical simulation for this system by using the model predictive control toolbox in MATLAB then we observe how this model predictive control method generates the optimal strategy to the corresponding response of the stock level. From the simulation results, the model predictive control generates the optimal strategies to control the stock level with minimum total cost and the stock level follows the decision maker desired level.

Stability criteria for stochastic Takagi‐Sugeno fuzzy Cohen‐Grossberg BAM neural networks with mixed time‐varying delays

This article is concerned with the asymptotic stability analysis of Takagi–Sugeno stochastic fuzzy Cohen–Grossberg neural networks with discrete and distributed time‐varying delays. Based on the Lyapunov functional and linear matrix inequality (LMI) technique, sufficient conditions are derived to ensure the global convergence of the equilibrium point. The proposed conditions can be checked easily by LMI Control Toolbox in Matlab. It has been shown that the results are less restrictive than previously known criteria. They are obtained under mild conditions, assuming neither differentiability nor strict monotonicity for activation function. Numerical examples are given to demonstrate the effectiveness of our results. © 2014 Wiley Periodicals, Inc. Complexity 21: 143–154, 2016

New results of stability analysis for a class of neutral-type neural network with mixed time delays

In this paper, by using Lyapunov–Krasovskii functionals involving triple terms, we investigate the global exponential robust stability for uncertain neutral-type neutral networks with discrete and distributed delays. Several stability criteria are derived for the delayed neural networks in terms of LMIs. Some numerical examples are given to illustrate the applicability of the obtained results by using LMI control toolbox in MATLAB.

Global Exponential Attractive Sets for Recurrent Neural Networks with Infinite Distributed Delays

This paper is concerned with the problem on global exponential attractive sets of recurrent neural networks (RNNs) with general activation functions and infinite distributed delays. By employing a new differential inequality and abandoning the limitation on activation functions, several sufficient conditions for detailed estimations of the global exponential attractive sets are derived in terms of linear matrix inequalities (LMIs) which can be easily checked by LMI Control Toolbox in Matlab. Compared with previous methods, the results obtained are independent of the time-varying delays and do not require the differentiability of delay functions. They extend and improve the earlier publications. Finally, a numerical example is provided to demonstrate the potential effectiveness of the proposed results. KeywordsRecurrent Neural Network; Global Exponential Attractive Sets; Infinite Distributed Delays; Linear Matrix Inequalities

Pre-Load Torque Responses for Flexibility in Single Link Manipulator

The Research article includes Model Torque Responses for flexibility of single link manipulators using Linearization Technique named as a LCQ. Manipulators are nothing but one type robotic arms commonly used in the industry .Here the controller design technique used for controlling manipulator was Linear Quadratic Controller Design. Generally the robotic arms are non-linear in nature. In order to control the non-linearity of manipulator and angular displacement, state space technique is used. The topology explains dynamic characteristics occurring in abnormal working condition torque responses are modified by using Linear Quadratic Controller Design Technique. The design method approach in state space control strategy. The dynamic torque responses of single link manipulator in abnormal condition and also using LCQ Technique are shown by M-File Controlling block of Simulink Library in Mat Lab Control tool box.

Research on synchronization of chaotic delayed neural networks with stochastic perturbation using impulsive control method

In this paper, an impulsive controller is designed to achieve the exponential synchronization of chaotic delayed neural networks with stochastic perturbation. By using the impulsive delay differential inequality technique that was established in recent publications, several sufficient conditions ensuring the exponential synchronization of chaotic delayed networks are derived, which can be easily checked by LMI Control Toolbox in Matlab. A numerical example and its simulation is given to demonstrate the effectiveness and advantage of the theory results.

ZIEGLER-NICHOLS PID CONTROLLER FOR EFFECTIVE PAY-LOAD TORQUE RESPONSES AND TIP-VIBRATIONS OF DOUBLE LINK MANIPULATOR

Robotic Technology is an imitation for human being’ s. It is an electro mechanical modelling objects ar e important aspect of manipulator. A Manipulator is a machine able to dri ve the robot. This paper describes and investigates on effective pay-load torque responses, tip-vibrations. This paper presents mode lling and simulation of the double link manipulator using the proposed PID Controller. Here the proposed Ziegler-Nichols propo rtional‐integral‐derivative controller (PID control ler) initiates more advantageous in the view of better performance and flexible operation of manipulator. First, the elect ro mechanical object was modeled and simulated using State space technique. Here the torque responses and end tip vibrations ar e assigned by state space variables. The entire two link manipulator topology was investigated and modeled, simulated. The propo sed control strategy carries a back ‐back feed forward controller can be used for flexible operation of manipulator. Here, the simula tion was done by using M-File Technique in Control tool box of MATLAB.

Global Robust Exponential Dissipativity for Interval Recurrent Neural Networks with Infinity Distributed Delays

This paper is concerned with the robust dissipativity problem for interval recurrent neural networks (IRNNs) with general activation functions, and continuous time-varying delay, and infinity distributed time delay. By employing a new differential inequality, constructing two different kinds of Lyapunov functions, and abandoning the limitation on activation functions being bounded, monotonous and differentiable, several sufficient conditions are established to guarantee the global robust exponential dissipativity for the addressed IRNNs in terms of linear matrix inequalities (LMIs) which can be easily checked by LMI Control Toolbox in MATLAB. Furthermore, the specific estimation of positive invariant and global exponential attractive sets of the addressed system is also derived. Compared with the previous literatures, the results obtained in this paper are shown to improve and extend the earlier global dissipativity conclusions. Finally, two numerical examples are provided to demonstrate the potential effectiveness of the proposed results.

Steam Pressure of Foaming Machine of Fuzzy PID Control and Simulation

This paper focus on designing a fuzzy PID controller design about the vapor pressure of the EPE foaming machine parameters, and raise a self-tuning method of PID parameters, and use the fuzzy control toolbox of MATLAB to simulate its control system, which are compared with the simulation of conventional PID controller, the results show the design of fuzzy PID controller have high control precision, small overshoot, good dynamic performance characteristics.

The LMI method for stationary oscillation of interval neural networks with three neuron activations under impulsive effects

In this paper, we investigate the stationary oscillation of interval neural networks with three neuron activation functions and time-varying delays under impulsive perturbations. Several theorems are given which present some sufficient conditions to guarantee the existence, uniqueness, and global exponential stability of periodic solutions (i.e., stationary oscillation) based on Lyapunov functionals approach and inequality analysis techniques. The obtained results can be easily checked by the Linear Matrix Inequality control toolbox in MATLAB. Finally, an example is given to illustrate the advantage of the obtained results.

Robust exponential stability and H ∞ control for switched neutral‐type neural networks

SUMMARYIn this paper, we consider the problem of robust exponential stability for a class of uncertain switched delayed neutral‐type neural networks with an H ∞ performance level γ > 0. Further, the result is extended to design an H ∞ control law to ensure the robust exponential stabilization of the closed‐loop neural networks about its equilibrium point with the guaranteed H ∞ performance level γ, for all norm bounded parameter uncertainties. On the basis of a new set of Lyapunov–Krasovskii functional, linear matrix inequality technique, and average dwell time approach, a set of novel sufficient conditions is derived for the existence of H ∞ performance and as well as existence of H ∞ control problem. The obtained results are derived in the form of convex optimization problems, which can be solved easily by the standard Matlab control toolbox. Numerical examples with simulation results are provided to illustrate the effectiveness of the proposed method. Copyright © 2012 John Wiley & Sons, Ltd.