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This research paper introduces an adaptive terminal synergetic nonlinear control. This control aims at synchronizing two hyperchaotic Zhou systems. Thus, the adaptive terminal synergetic control’s synthesis is applied to synchronize a hyperchaotic i.e., slave system with unknown parameters with another hyperchaotic i.e., master system. Accordingly, simulation results of each system in different initial conditions reveal significant convergence. Moreover, the findings proved stability and robustness of the suggested scheme using Lyapunov stability theory.

Blood glucose automatic regulation achievement depends on the robustness of the used control algorithm. However, some constraints were encountered due to the human glucose-insulin regulatory system’s complexity. It is proposed to tackle such a goal through the development of a robust synergetic control algorithm. An adaptive approach is integrated into this synergetic control scheme to handle disturbances and parameters variations. Multiple meal disturbances often occur daily as well as some other stochastic noises making efficient glucose regulation a tough challenge addressed in this paper via a new synergetic scheme. Simulation results show a robust function during multiple meal disturbances with good noise rejection.

In this paper, an adaptive fuzzy synergetic controller(AFSC) is designed around a dSpace based experimental setup to provide robust DC–DC buck converter voltage control. Upholding high performance is a challenging task when operating a system under varying operating conditions and parameters uncertainties as is the case when dealing with DC–DC converter control. Fuzzy systems are used to approximate converter dynamics assumed, in this paper, to be unknown (accurate mathematical model is thus considered unavailable). Synergetic control is used to construct a robust continuous control law easy to implement despite varying operating conditions. The combination of these two techniques results in an intelligent robust DC–DC converter control. Unlike many works published, the present paper provides experimental results which corroborate the given analytical stability proof of the closed-loop system and confirm the system signals boundedness. Simulation results followed by experimental validation show that the proposed controller is able to achieve satisfactory voltage regulation performances over system parameters uncertainties, reference output voltage changes, load changes and source voltage variations.

Finite time convergence based on robust synergetic control (SC) theory and terminal attractor techniques is investigated. To this end a fast terminal synergetic control law (FTSC) is applied to drive a DC–DC Buck converter via simulation and through a dSpace based experimental setup to validate the approach. As robust as sliding mode control, the synergetic approach used is chattering free and provides rapid convergence. Efficacy of the proposed fast terminal synergetic controller is tested for step load change and output voltage variation and results compared to classical synergetic and PI control. Experimental validation using dSpace DS1104 confirms the results obtained in simulation showing the soundness of this approach compared to synergetic and PI controllers.

In this paper, a new robust terminal synergetic control scheme is proposed to regulate blood glucose level in diabetic patients (type I diabetes), based on recently developed synergetic control and a terminal attractor technique. The technique presented has the advantage of using a continuous control law. Moreover, the proposed control scheme, besides being chattering free, has the characteristics of finite time convergence. Lyapunov synthesis is adopted to ensure controlled system stability. Simulation results of terminal synergetic control are compared to classic synergetic and second-order sliding mode control (SMC) performance, demonstrating that the proposed control method allows for rapidly achieving normoglycemia in type I diabetes patients.

This paper proposes an Adaptive Terminal Synergetic Control (ATSYC) as a control strategy for Buck DC-DC converter. A simple Adaptive synergetic control (ATSYC) technique for the buck converter that has a fixed switching frequency and zero steady state error. The responses of this controller is robust and its can be defined directly in the time domain. In addition, GA & PSO algorithms will be used to optimize controller parameters using an ITAE criterion. The proposed control scheme is evaluated in a simulation study of a buck converter indicating satisfactory overall performance with stability ensured through Lyapunov synthesis.

Robust control often requires some adaptive approach in evaluating systems dynamics to handle parameters variations and external disturbances. Therefore, an error due to dynamics approximation is inevitably added to uncertainties already present in the model. This issue is addressed in this paper, through the combination of two robust techniques, Hinf and synergetic control. These latter are used to ensure reducing tracking error in the overall closed-loop system while guaranteeing stability via Lyapunov synthesis. With the aim of handling parameters variations, an indirect adaptive fuzzy scheme is used to elaborate system model. Simulation studies are conducted to assess the proposed approach on two practical systems, and the results are compared to a sliding mode proportional integral (PI)-based technique. It is to be noted that a large class of systems depicted as control affine systems will be considered in this paper. An induction motor and an inverted pendulum representing, respectively, a linear and a nonlinear system are utilized in this study showing improvement due to the suggested approach, in overall performance over its sliding mode control counterpart.

This work presents an indirect adaptive fuzzy sliding mode power system stabilizer that is used to damp out the low frequency oscillations in power systems. The proposed controller design is based on an adaptive fuzzy control combining a proportional integral control and sliding mode control. The fuzzy logic system is used to approximate the unknown system function and using the particle swarm optimization technique to optimize parameters proportional integral control to eliminate the chattering action in the sliding mode control. Using Lyapunov synthesis, adaptation laws are developed to make the controller adaptive to changes in operating conditions of the power system. The nonlinear simulation studies show the successful performance of the proposed stabilizer.

DC-DC converters have been receiving great attention for their extensive use in a myriad of applications starting with basic calculators to photovoltaic systems to sophisticated weaponry. Several control methods were developed for DCDC converters control mostly with asymptotic convergence. Synergetic control are a proven robust controllers approach and will be used here in a so called terminal scheme to achieve finite time convergence thus enhancing the already established technique robustness. An adaptive non-singular terminal synergetic control approach to handle uncertainties is provided resulting in enhancing robustness as well as a better transient performance compared to terminal synergetic control. Lyapounov synthesis is adopted to assure controlled system stability. Furthermore, a PSO algorithm will be used to optimize controller's parameters using an ITAE criterion. Simulation of terminal synergetic control of a DC-DC converter is carried out for different operating conditions and results are compared to terminal synergetic control performance, that which demonstrate the effectiveness and feasibility of the proposed approach.

A new indirect adaptive type-2 fuzzy sliding mode controller as a power system stabilizer (PSS) is proposed for damping low frequency power oscillation of interconnected power system and capable of performing well for a wide range of variations in system parameters and/or operating conditions. The proposed controller design is based on the integration of sliding mode control (SMC) and Adaptive type-2 fuzzy control. The type-2 fuzzy logic system is used to approximate the unknown system function and PI control term is used to eliminate chattering action in the design of sliding mode control. Using Lyapunov stability theory, the adaptation laws are developed to make the controller adaptive to take care of the changes due to the different operating conditions occurring in the power system and guarantees stability converge. The robustness of the proposed stabilizer has been tested on a two-area four machine power system. Nonlinear simulation studies show the best performance of the proposed stabilizer and confirm its superiority over adaptive type-2 fuzzy synergetic (AFSPSS), adaptive type-2 fuzzy (AFPSS) and the conventional (CPSS) stabilizers.

Diabetes mellitus is a chronic disorder of carbohydrate metabolism due to relative or absolute insulin deficiency. This latter can be best handled in an automatic procedure. It's essential that control used in such a scheme be robust to any kind of disturbances and parameters uncertainties. In this paper, Bergman's minimal model is used as a starting point in an effort to regulate efficiently glucose level using synergetic control which is then compared to the application of second order sliding mode. These two proven robust control techniques can handle adequately uncertainties to a great extent through their invariance properties. Our contribution shows that synergetic methodology provides better performance. It is obvious that obtaining system parameters exact values is unrealistic in most biological systems, therefore all model parameters will be considered uncertain. Parametric uncertainty will be exploited in developing a control scheme based on a closed-loop feedback strategy. The behavior of the obtained controller is analyzed on its ability to track a normoglycemic in presence of disturbance and perturbed parameters. A comparative study of the application of the two techniques is carried out showing through simulation results that the synergetic control approach offers stronger robustness in performance compared to sliding mode control, despite disturbances.

In this paper, an adaptive fuzzy power system stabilizer is developed based on robust synergetic control theory and terminal attractor techniques. The main contribution consists in making the dynamic system insensitive to parameters variation. This aim is achieved using a new synergetic controller design such that power system states start, evolve and remain on a designer chosen attractor toward the equilibrium point therefore avoiding transient mode. Rendering the design more robust, fuzzy logic systems are used to approximate the unknown power system dynamic functions without calling upon usual model linearization and simplifications. Based on an indirect adaptive scheme and Lyapunov theory, adaptation laws are developed to make the controller handle parameters variations due to the different operating conditions occurring on the power system and to guarantee stability. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results show the effectiveness and robustness of the proposed stabilizer in damping power system oscillations under various disturbances and better overall performance than classical PSS and some other types of power stabilizers.

A new particle swarm optimized robust indirect adaptive power system stabilizer is developed based on recently developed synergetic control methodology. Fuzzy systems are used in an adaptive scheme to approximate the system using a nonlinear model while synergetic control guarantees robustness and the use of a chatter free continuous control law which makes the controller easy to implement. In addition the controller parameters are optimized using PSO approach. Simulation of severe operating conditions of a power system is conducted to validate the effectiveness of the proposed approach while stability is guaranteed via Lyapunov synthesis.

In this paper, a type-2 fuzzy-based adaptive sliding mode power system controller is proposed for damping low-frequency oscillations with the aim to enhance power system stability despite model uncertainties introduced by variations of system parameters and external disturbances. Addressing these latter, type-2 fuzzy systems approximating properties are used to approximate unknown power system non-linear dynamics. Furthermore, to achieve more robustness, the proposed controller design is combined with sliding mode approach. The latter and Lyapunov synthesis approach are incorporated in an adaptive fuzzy control scheme such that the derived controller is robust, closely tracking any changes in power system operating conditions and guaranteeing stability while a PI control term is added to mitigate chattering. Proposed stabiliser robustness has been tested on a single machine infinite bus system and a multi-machine power system. Non-linear simulation studies show good performance of the proposed stabiliser and confirm its superiority over conventional PSS and some other types of power stabilisers.

Control of dc/dc buck converter is a complex task due to the nonlinearity inherent in the converter and introduced by the external changes. A robust synergetic controller for the control of dc/dc buck converter is described in this study. An adaptive terminal synergetic control is developed based on robust synergetic control theory and terminal attractor techniques. The method estimates the boundary of parameter uncertainty and external disturbance by adaptive law. The idea behind this strategy is to use the terminal synergetic control (TSYC) approach to assure finite time convergence of the output voltage error to the equilibrium point, and integrate an adaptive law to handle uncertainties is provided resulting in enhancing robustness as well as a better transient performance compared to the conventional control. In addition, modified PSO algorithms will be used to optimise controller's parameters using an ITAE criterion. The results show and demonstrate the effectiveness and feasibility of the proposed approach.

In this paper, an optimal synergetic controller based on a bat algorithm for a DC-DC boost converter is presented. DC-DC boost converters are some of the most widely used power electronics devices for their high conversion efficiency and versatility. Bat optimisation based on the echolocation behaviour of bats, a bio-inspired algorithm, is successfully used for synergetic parameters optimization. The proposed control scheme is evaluated in a simulation and implementation study of a boost converter indicating satisfactory overall performance with stability insured through Lyapunov synthesis. Experimental results show that the proposed control provides good regulation.

DC-DC converters are widely used as reliable power source for many industrial and military applications, computers and electronic devices. Several control methods were developed for DCDC converters control mostly with asymptotic convergence. Sliding mode, synergetic control are a proven robust controllers approach and will be used here in a so called terminal scheme to achieve finite time convergence thus enhancing the already established technique robustness. Lyapounov synthesis is adopted to assure controlled system stability. Furthermore, a PSO algorithm will be used to optimize controller's parameters using an ITAE criterion. Simulation of terminal synergetic control of a DC-DC converter is carried out for different operating conditions and results are compared to terminal sliding mode control performance, that which demonstrate the effectiveness and feasibility of the proposed control method.

This paper presents a novel terminal synergetic control for DC-DC buck converters. Since buck converters have high nonlinearity and uncertainty, an indirect adaptive control is developed based on recently developed synergetic control methodology. Fuzzy systems are used in an adaptive scheme to approximate the system using a nonlinear model while synergetic control guarantees robustness and the use of a chatter free continuous control law which makes the controller easy to implement. In addition the controller parameters are optimized using GA approach. Simulation of severe operating conditions of a power system is conducted to validate the effectiveness of the proposed approach while stability is guaranteed via Lyapunov synthesis.

DC-DC converters are widely used as reliable power source for many industrial and military applications, computers and electronic devices. Several control methods were developed for DC-DC converters control mostly with asymptotic convergence. Synergetic control (SC) is a proven robust control approach and will be used here in a so called terminal scheme to achieve finite time convergence. Lyapounov synthesis is adopted to assure controlled system stability. Furthermore particle swarm optimization (PSO) algorithm, based on an integral time absolute of error (ITAE) criterion will be used to optimize controller parameters. Simulation of terminal synergetic control of a DC-DC converter is carried out for different operating conditions and results are compared to classic synergetic control performance, that which demonstrate the effectiveness and feasibility of the proposed control method., {"references":["L. Fan, and Y. Yu , \"Adaptive non-singular terminal sliding mode control for DC-DC converter\", Advances in Electrical and Computer Engineering, Vol. 11, Number 2, 2011.","V.I. Utkin. , Sliding modes in control and optimization, New York, Springer, 1992.","J.E. Slotine., and W.P. Li, Applied nonlinear control, Prentice-Hall, Englewood Cliffs, NJ, 1991.","H.F. Ho, Wong, Y.K., and A.B. Rad, \"Adaptive fuzzy sliding mode control with chattering elimination for nonlinear SISO systems\", Simulation Modelling Practice and Theory'', 2009,(17), pp. 1199–1210","Zhenhua.J, Roger.A. Dougal. Synergetic Control of Power Converters for Pulse Current Charging of Advanced Batteries from a Fuel Cell Power Source. IEEE Transactions on powr electronics,Vol. 19. No. 4. July 2004.","E. Santi. E, Monti. A, Donghong. L, Karthik. P, Roger. A. Dougal. Synergetic Control for DC-DC Boost Converter: Implementation Options. IEEE Transactions on industry applications. Vol. 39. No. 6. November 2003.","Mezghani N., Damak T., Adaptive terminal sliding mode control for rigid robotic manipulators, International Journal of Automation and Computing 8(2), May 2011, 215-220 DOI: 10.1007/s11633-011-0576-2.","H. Komurcugil, \"Adaptive terminal sliding-mode control strategy for DC-DC buck converters\", ISA Transactions 51 (2012) 673-681.","J. Kennedy and R.C. Eberhart, \"Particle swarm optimization\", Proc. Of IEEE International Conference on Neural Networks, Piscataway, NJ. Pp 1942-1948,1995.\n[10]\tB. Liu, K.Wang,and Q. Zou, \"Study on the application of particle swarm optimization algorithm to power regulation of CPS in interconnects power grids\". IEEE Electrical Power & Energy Conference. 2008. \n[11]\tR. Suresh Kumar,and J. Suganthi , Improving the boost Converter PID Controller performance using Particle swarm optimization, European Journal of Scientific Research, ISSN 1450-216X Vol. 85 No 3 September, 2012, pp.327 – 335. \n[12]\tS. Vishnu Teja, T. N. Shanavas, and S. K. Patnaik, Modified PSO Based Sliding Mode Controller Parameters for Buck Converter, 2012 IEEE, Students Conference on Electrical, Electronics and Computer Science."]}

Power system stability is enhanced through a novel stabilizer developed around an adaptive fuzzy sliding mode approach which applies the Nussbaum gain to a nonlinear model of a single-machine infinite-bus (SMIB) and multi-machine power system stabilizer subjected to a three phase fault. The Nussbaum gain is used to avoid the positive sign constraint and the problem of controllability of the system. A comparative simulation study is presented to evaluate the achieved performance.

This paper presents a novel power system stabilizer based on adaptive fuzzy sliding mode approach without reaching phase. We consider consequences of a major post disturbance on a power system for three different loading and operating conditions. Speed deviation and accelerating power are selected as controller inputs. A new sliding surface enabling for sliding to occur at any state initial conditions is used to develop a robust controller. Moreover, two adaptive fuzzy systems are used to approximate power system dynamics. Stability issue is addressed via Lyapunov synthesis. The robustness of the proposed method is verified on a single-machine infinite-bus and on a multi-machine power system stabilizer under different operating conditions. A comparative simulation study is presented to evaluate achieved performance enhancements showing better oscillations damping and faster transient dynamic behaviour over three considered controllers: a conventional, a dual-input and a classical sliding mode power system stabilizer.

This paper introduces a new type-2 fuzzy based adaptive synergetic power system stabilizer used in damping power flow limiting oscillations that often occur following disturbances in power systems. Small magnitude and low frequency oscillations, linked to the electromechanical modes in power systems, often persist for long periods of time leading in some cases to loss of synchronism and eventually to blackouts. These oscillations may occur locally or between different areas of a power system. Among many robust control techniques to assure service continuity sliding mode has been proposed despite its inherent chattering drawback. This paper present a novel power system stabilizer based on synergetic control which possesses the same strong robustness and invariance to external disturbances as sliding mode but without its negative chattering. Type-1 fuzzy systems have also been heavily relied on to describe unknown system model but they lack fuzziness in dealing with uncertainties. Better suited to deal with uncertainties type-2 fuzzy systems are used in this paper in approximating the unknown power system nonlinear dynamics while stability is insured through Lyapunov synthesis. Severe operating conditions are used in a simulation study to test the validity and effectiveness of the proposed method. Results indicate good performance and satisfactory transient dynamic behaviour. A multi-machine power system is used to demonstrate the performance of the proposed controller and to show its superiority over other conventional stabilizers used in the literature.

A new robust controller for a class of nonlinear system is presented in which the control law is continuous unlike that used in sliding mode control. Motivated by the recently developed synergetic control we develop an indirect adaptive fuzzy synergetic controller for a non linear system. The latter is forced to evolve according to designer chosen dynamics but without the chattering problem inherent to sliding mode control. Fuzzy inference systems are used to approximate the system model nonlinear functions in an indirect adaptive scheme to account for varying operating conditions as well as for system parameters uncertainties. Further enhancement consisting in finite time convergence is also achieved using a terminal manifold technique. Simulation of stabilization and reference tracking for nonlinear systems illustrates the approach effectiveness while stability is assured in the Lyapounov sense.