Synchronous generator nonlinear excitation system: Synergetic sliding mode control

This paper aims to present the design of power system stabilizer (PSS) as a second-order sliding mode controller (SOSMC). Power systems have always been growing into more dynamic and complex systems. This is because of continuously occurring disturbances and parametric uncertainties in power systems due to changing loads. One of the major problems with this area is small frequency oscillations which lead to the system instability if these oscillations are not damped properly and also reduce power transfer capability. Therefore, it is essential to use power system stabilizers (PSS) to damp out small frequency oscillations. In this paper, single machine infinite bus (SMIB) system is used as study system. Sliding mode control (SMC) is a nonlinear and very robust control technique. Advantages of this controller can be used to control the power systems in order to increase the stability. But SMC has a major disadvantage of chattering. SOSMC overcomes the disadvantages produced by SMC. Therefore, in this paper, PSS is designed as SOSMC using twisting algorithm and applied to SMIB. The robustness of PSS as SOSMC is demonstrated by carrying out comparative simulation under different operating conditions of the SMIB power system.

—Stability, robust and reliability are the main objectives to design a controller for highly nonlinear spherical motor. Most of linear and nonlinear controllers are stable, model-base controllers are reliable but in this group sliding mode controller is a robust controller. Therefore in this research sliding mode controller is used to design stable, robust and reliable controller. For intelligence part, the minimum rule base Proportional Integral Derivative (PID) Fuzzy hybrid guidance Controller for three dimensions spherical motor is presented in this research. Guidance control in a three dimensions spherical motor is performed by the robust sliding mode controllers producing the control signals which are applied to systems torque. Sliding mode controller has an important problem, namely chattering. In this research, chattering-free sliding mode controller is design as a robust guidance controller to their robust performance in a wide range of operating conditions. In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PD-like fuzzy controller and a PI-like controller to have the minimum rule base. Nonlinear type robust sliding mode controller is used to modify PID fuzzy logic theory to design robust and reliable hybrid guidance methodology. This research is used to reduce or eliminate the fuzzy and conventional sliding mode controller problem based on minimum rule base fuzzy logic theory and modified it by sliding mode method to control of spherical motor system.

Purpose The flexible mode transitions, multiple power sources and system uncertainty lead to challenges for mode transition control of four-wheel-drive hybrid powertrain. Therefore, the purpose of this paper is to improve dynamic performance and fuel economy in mode transition process for four-wheel-drive hybrid electric vehicles (HEVs), overcoming the influence of system uncertainty. Design/methodology/approach First, operation modes and transitions are analyzed and then dynamic models during mode transition process are established. Second, a robust mode transition controller based on radial basis function neural network (RBFNN) is proposed. RBFNN is designed as an uncertainty estimator to approximate lumped model uncertainty due to modeling error. Based on this estimator, a sliding mode controller (SMC) is proposed in clutch slipping phase to achieve clutch speed synchronization, despite disturbance of engine torque error, engine resistant torque and clutch torque. Finally, simulations are carried out on MATLAB/Cruise co-platform. Findings Compared with routine control and SMC, the proposed robust controller can achieve better performance in clutch slipping time, engine torque error, vehicle jerk and slipping work either in nominal system or perturbed system. Originality/value The mode transition control of four-wheel-drive HEVs is investigated, and a robust controller based on RBFNN estimation is proposed. Compared results show that the proposed controller can improve dynamic performance and fuel economy effectively in spite of the existence of uncertainty.

In this paper, a Multi-Index Nonlinear Robust Adaptive Control (MINRAC) method was proposed for ultra-complex multi-input multi-output power systems with uncertain parameter factors and external disturbances. The controller designed by this method has excellent static and dynamic characteristics. Under the condition of the uncertainty of system parameters and external disturbance at the same time, the MINRAC method can ensure that the multiple indexes concerned by ultra-complex power systems can be controlled at their expected values. The simulation results showed that the control mechanism of MINRAC method was consistent in both single-machine infinite bus system and multi-machine interconnected coupling system. The output function chooses power angle, angular frequency and terminal voltage as constraints. When the system has parameter uncertainty and external interference, the uncertain parameter values are adjusted by adaptive control to force these indicators to tend to the given expected value. For three-phase short circuit, which is the most serious fault in power system, the use of multi index nonlinear robust controller can ensure that the system is stable in a wide range and has better dynamic performance.

In this chapter, a novel control method using a reinforcement learning (RL) (Sutton and Barto (1998)) with concept of sliding mode control (SMC) (Slotine and Li (1991)) for unknown dynamical system is considered. In designing the control system for unknown dynamical system, there are three approaches. The first one is the conventional model-based controller design, such as optimal control and robust control, each of which is mathematically elegant, however both controller design procedures present a major disadvantage posed by the requirement of the knowledge of the system dynamics to identify and model it. In such cases, it is usually difficult to model the unknown system, especially, the nonlinear dynamical complex system, to make matters worse, almost all real systems are such cases. The second one is the way to use only the soft-computing, such as neural networks, fuzzy systems, evolutionary systems with learning and so on. However, in these cases it is well known that modeling and identification procedures for the dynamics of the given uncertain nonlinear system and controller design procedures often become time consuming iterative approaches during parameter identification and model validation at each step of the iteration, and in addition, the control system designed through such troubles does not guarantee the stability of the system. The last one is the way to use the method combining the above the soft-computing method with the model-based control theory, such as optimal control, sliding mode control (SMC), H∞ control and so on. The control systems designed through such above control theories have some advantages, that is, the good nature which its adopted theory has originally, robustness, less required iterative learning number which is useful for fragile system controller design not allowed a lot of iterative procedure. This chapter concerns with the last one, that is, RL system, a kind of soft-computing method, supported with robust control theory, especially SMC for uncertain nonlinear systems. RL has been extensively developed in the computational intelligence and machine learning societies, generally to find optimal control policies for Markovian systems with discrete state and action space. RL-based solutions to the continuous-time optimal control problem have been given in Doya (Doya (2000). The main advantage of using RL for solving optimal

This chapter deals with the control and synchronization of chaos where both of them are regarded as a case of a control problem. The proposed approach consists in using the sliding mode control theory. We first compare the pioneering OGY control method to the sliding mode control method. We next present a sliding surface design based on the Lyapunov theory. We show that for the class of chaotic systems that can be stabilized using a smooth feedback controller, a sliding manifold can be easily constructed using the Lyapunov function. Besides, we prove that the designed sliding surface is a stable manifold for the originally chaotic system. Thus, should the state behavior be confined to it, then the trajectory will slide towards the equilibrium. We also prove that the proposed controller is robust to mismatched parametric uncertainties. To diminish the effect of the unwanted chattering phenomenon resulting from high sliding gains, an adaptive sliding controller is finally designed to present a robust model independent controller that achieves stabilization of the equilibrium points as well as synchronization of two systems. All these results will be confirmed through numerical simulations on Rossler’s system.

This paper presents a design method of robust nonlinear controller with inner-outer loop structure (robust chattering free backstepping/backstepping sliding mode controller). Because backstepping control and sliding mode control are in nature two different robust controllers, the combination of them brings up a controller which has stronger robustness for synthesizing their advantages. In this paper, the chattering of backstepping sliding mode controller can be effectively prevented by substituting sign function of the sliding mode exponential approaching rate with a simple saturation function. The controller adopts inner-outer loop control structure. The inner loop is used to stabilize attitude by adopting backstepping sliding mode controller. The outer loop is used to track position by adopting backstepping controller. Simulation results show that the control strategy proposed in this paper is effective and has strong robustness in the presence of aerodynamic torque disturbance and parameter uncertainty.

Abstract— This paper presents the complete model of a minihelicopter quadrotor and describes its behavior control for the altitude by using sliding mode control. The control technique is robust against disturbances and attenuates the parametricunc ertainties. The plant is a nonlinear one with state variables strongly coupled. The simulations show that the technique successfully drives the system and the altitude is well controlled as well as the rotational movements.Keywords- Sliding Mode Control, Control theory, UAV’s , Non linear control.

Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions

In this paper, a novel adaptive robust control (ARC) scheme is proposed for electro-hydraulic servo systems (EHSSs) with uncertainties and disturbances. All dynamic functions in system dynamics are effectively approximated by multi-layer radial basis function neural network (RBF NN)-based approximators with online adaptive mechanisms. Moreover, neural network-based disturbance observers (NN-DOBs) are established to actively estimate and efficiently compensate for the effects of not only the matched/mismatched but also the imperfections of RBF NN-based approximators on the control system. Based on that, the nonlinear robust control law which integrates RBF NNs and NN-DOBs is synthesized via the sliding mode control (SMC) approach to guarantee the high-accuracy position tracking performance of the overall control system. Furthermore, the problem of the combination between DOBs and RBF NNs is first introduced in this paper to treat both disturbances and uncertainties in the EHSS. The stability of the recommended control mechanism is proven by using Lyapunov theory. Finally, numerical simulations with several distinct frequency levels of reference trajectory are conducted to convincingly demonstrate the effectiveness of the proposed approach.

One of the unavoidable issues with various real-time control systems is existence of the external disturbances and uncertainties which is usually unavailable. To deal with these disturbances and uncertainties, various robust control methods have been introduced in the literature such as Sliding Mode Control (SMC), adaptive control method and so on. This paper proposes a novel Adaptive Terminal SMC (ATSMC) method to control the hyper-chaotic 4-order system within a finite-time by utilizing only one control input. The dynamical model of the hyper-chaotic 4-order system is subjected to the mismatched external disturbances and uncertainties which are bounded, but these bounds are unavailable. The adaptive concept is employed to approximate the upper bounds of these unknown mismatched external disturbances and uncertainties within a finite-time and their estimations are used in the control input. The robust controller is designed by utilizing Lyapunov stability theory. The key features of the designed controller are robustness against all mismatched uncertainties and external disturbances, and providing stability within a finite-time. Finally, a numerical simulation is performed in Simulink/MATLAB to verify the effectiveness of the designed controller to suppress the chaotic oscillations. The numerical simulation results reveal that the finite-time stability is achieved accurately as soon as the controller is introduced.

To eliminate the effect of the uncertain disturbances and improve the control accuracy of spacecraft Attitude Control System, a nonlinear control algorithm named nonsingular terminal sliding-mode feedback controller is proposed in this work, which is mainly made up of nonsingular terminal sliding-mode controller and sliding-mode feedback controller. In the first place, nonsingular terminal sliding-mode controller is designed, which guarantees global asymptotic convergence of the attitude in the presence of the uncertain perturbations from the space. Despite that, it is the influence of the uncertain disturbances that hinder the control accuracy. Then, in order to promote the control accuracy, the sliding-mode feedback controller based on the principle of minimum sliding-mode error is proposed, which is used to compensate the control errors of the nonsingular terminal sliding-mode controller caused by the uncertainties. Hence, the determination principle of the weighting matrix in sliding-mode feedback controller is discussed, and the algorithm structure of the sliding-mode feedback controller is also analyzed, which provides the theoretical basis for the sliding-mode feedback controller. By contrast, an adaptive fuzzy algorithm is designed and introduced into the nonsingular terminal sliding-mode controller to improve the control accuracy, which named the nonsingular terminal fuzzy sliding-mode controller. Last but not the least, several numerical examples are presented to demonstrate the efficacy of the proposed nonsingular terminal sliding-mode feedback controller. Simulation results confirm that the control accuracy of the nonsingular terminal sliding-mode feedback controller is higher than the nonsingular terminal sliding-mode controller and the same as nonsingular terminal fuzzy sliding-mode controller. Not only is the calculation of the nonsingular terminal fuzzy sliding-mode feedback controller smaller than nonsingular terminal fuzzy sliding-mode controller, the adjusted parameters are also fewer than nonsingular terminal fuzzy sliding-mode controller obviously. The numerical results clearly indicate that the proposed nonsingular terminal sliding-mode feedback controller based on the principle of minimum sliding-mode error can compensate control errors accurately and quickly; therefore, it can reduce the effect of the uncertainties from the space indirectly.

In this paper, the parameter robust design method and sliding mode control theory are combined to design the helicopter control system in the whole flight envelop with the uncertainties and nonlinearities considered. First based on the flying qualities and the constraint conditions of the measurable states, the partial pole assignment is realized by the parameter robust design method, accordingly the mapping relationship of the parameter space and the corresponding usable set is determined, which provides an effective method to design the equivalent scheduling control law in the whole flight envelop. Second based on the helicopter T -S model within the whole flight envelop, according to the parameter mapping law, the equivalent control law is designed using the parallel distributed compensation algorithm, which ensures the well dynamic performance the control system in the whole flight envelop. Finally the closed-loop system characteristic equation corresponding to the equivalent control law is used to construct the integral sliding surface. The switching is designed so that the system has the robustness against the uncertainties and disturbances. The simulations indicate that the proposed sliding mode control system is robust against the external disturbances, it has the strong disturbance-suppression capability and satisfies the dynamic performance requirements of the helicopter.

The integration of renewable energy sources (RESs) at the edge of the grid plays a contributory role in advancing the transition to a sustainable energy future. However, this transition introduces significant variability, which challenges the maintenance of frequency stability in power systems. To address the impacts of RES variability, various robust control strategies have been developed. This paper compares the performance of different advanced sliding mode control (SMC) approaches, i.e., super twisting (ST) algorithm‐based second order sliding mode control (STSOSMC), second order sliding mode control (SOSMC), double integral sliding mode control (DISMC) and integral sliding mode control (ISMC) with conventional sliding mode control (SMC) for load frequency control with stochastic RESs such as biogas generators (BG) and wind‐based doubly fed induction generators (DFIG). The impact of the advanced sliding mode controllers on the voltage and rotor angle stability of the system is also explored. The efficacy of the controllers is tested under different load disturbances, considering nonlinearities such as communication delay (CD), sensor inaccuracy (SI), governor dead band (GDB), and generation rate constraint (GRC). The results demonstrate that STSOSMC achieves superior frequency regulation with minimal chattering and outperforms other controllers in terms of settling time, overshooting, and undershooting in frequency deviation. The result also demonstrates the effectiveness of STSOSMC in managing the variability and disturbances of RESs. Therefore, it could be considered the most robust control mechanism from the edge of the grid system with high penetration of RESs.

Adaptive fractional-order sliding-mode disturbance observer-based robust theoretical frequency controller applied to hybrid wind–diesel power system