Dianwei Qian

Load frequency control by neural-network-based integral sliding mode for nonlinear power systems with wind turbines

Load frequency control (LFC) plays an important role in maintaining constant frequency in order to ensure the reliability of power systems. With the large-scale development of sustainable but intermittent sources such as wind and solar, such intermittency challenges the LFC problem. Moreover, the generation rate constraint (GRC) of power systems also complexes the LFC problem. Concerning the constraint, this paper addresses an integral sliding mode control (I-SMC) method for power systems with wind turbines. Since the intermittency of wind farms and the linearization of GRC deteriorate the uncertainties of power systems, sliding-mode-based neural networks are designed to approximate the uncertainties. Weight update formulas of the neural networks are derived from the Lyapunov direct method. The neural-network-based integral sliding mode controller is employed to achieve the LFC problem. By this scheme, not only are the update formulas obtained, but also the control system possesses the asymptotic stability. The simulation results by an interconnected power system illustrate the feasibility and validity of the presented method.

Robust sliding mode control for a class of underactuated systems with mismatched uncertainties

Abstract Based on the sliding mode control methodology, this paper presents a robust control strategy for underactuated systems with mismatched uncertainties. The system consists of a nominal system and the mismatched uncertainties. Since the nominal system can be considered to be made up of several subsystems, a hierarchical structure for the sliding surfaces is designed. This is achieved by taking the sliding surface of one of the subsystems as the first-layer sliding surface and using this sliding surface and the sliding surface of another subsystem to construct the second-layer sliding surface. This process continues till the sliding surfaces of all the subsystems are included. A lumped sliding mode compensator is designed at the last-layer sliding surface. The asymptotic stability of all of the layer sliding surfaces and the sliding surface of each subsystem is proven. Simulation results show the validity of this robust control method through stabilization control of a system consisting of two inverted pendulums and mismatched uncertainties.

Robust control using incremental sliding mode for underactuated systems with mismatched uncertainties

A new robust controller using sliding mode control method for a class of underactuated mechanical systems with mismatched uncertainties is proposed in this paper. Two state variables of the underactuated system are chosen to construct the first-layer sliding surface. The first-layer sliding surface and one of the left state variables are used to construct the second-layer sliding surface. This process continues till the last sliding surface is constructed. And a distributed compensator is added to the sliding mode surfaces. We design a new sliding mode control law to guarantee that every sliding surface can converge rapidly to zero. For an underactuated system, which consists of 2n state variables, the controller has the (2n-1)-layer structure. Using Lyapunov law, we prove the stability of all the sliding surfaces theoretically. The simulation results show the validity of this method.

Load frequency control considering generation rate constraints

Constrained generalized predictive algorithm is employed to load frequency control in this paper. Generation rate constraint (GRC) has been considered. Using the linearization modeling technique, this paper deals with load frequency control by multivariable generalized predictive control method to build Controlled Auto-Regressive Integrated Moving Average model (CARIMA) and obtain generalized predictive control algorithm for load frequency control of the two-area reheat power system. Results demonstrate the effectiveness of the proposed generalized predictive control algorithm.

Robust Control Using Sliding Mode for a Class of Under-Actuated Systems With Mismatched Uncertainties

Based on the methodology of sliding mode, this paper presents a robust controller for a class of under-actuated systems with mismatched uncertainties. Such a system consists of a nominal system and the mismatched uncertainties. The structural characteristic of the nominal system is that it is made up of several subsystems. Based on this characteristic, the hierarchical structure of the sliding mode surfaces is designed for the nominal system as follows. Firstly, the nominal system is divided into several subsystems and the sliding mode surface of every subsystem is defined. Secondly, the sliding mode surface of one subsystem is selected as the first layer sliding mode surface. The first layer sliding mode surface is then to construct the second layer sliding mode surface with the sliding mode surface of another subsystem. This process continues till the sliding mode surfaces of all the subsystems are included. For dealing with the mismatched uncertainties, a lumped sliding mode compensator is designed at the last layer sliding mode surface. The asymptotic stability of every layer sliding mode surface and the sliding mode surface of each subsystem is proven theoretically by Barbalats lemma. Simulation results show the validity of this robust control method through stabilization control of a double inverted pendulums system with mismatched uncertainties.

Hierarchical Sliding Mode Control to Swing up a Pendubot

To swing up a Pendubot, a pendulum robot, this paper presents a hierarchical sliding mode controller with limited control torque. The structure characteristic of the Pendubot system is that it can be treated as two subsystems. Thus, the hierarchical structure of the sliding mode surfaces is designed as follows. The sliding mode surfaces of the two subsystems are defined at first. The sliding mode surface of one subsystem is selected as the first layer sliding mode surface. The second layer sliding mode surface is constructed by the first layer sliding mode surface and the sliding mode surface of the other subsystem. The hierarchical sliding mode control law is deduced in terms of Lyapunov stability theorem. Asymptotic stability of the entire sliding mode surfaces is proven theoretically and control parameter boundaries of the two subsystems are also given theoretically. Finally, simulation results show the validity of this control method and its robustness for external disturbances.

Neural sliding-mode load frequency controller design of power systems

Load frequency control (LFC) is one of the most profitable ancillary services of power systems. Governor dead band (GDB) nonlinearity is able to deteriorate the LFC performance. In this paper, controller design via a neural sliding-mode method is investigated for the LFC problem of power systems with GDB. Power systems are made up of areas. In each area, a sliding-mode LFC controller is designed by introducing an additional sate, and a RBF neural network is utilized to compensate the GDB nonlinearity of the area. Weight update formula of the RBF network is derived from Lyapunov direct method. By this scheme, not only the update formula is obtained, but also the control system possesses the asymptotic stability. Simulation results illustrate the feasibility and robustness of the presented approach for the LFC problems of single-area and multi-area power systems.

Control of Overhead Crane Systems by Combining Sliding Mode with Fuzzy Regulator

Abstract In industries, overhead cranes are commonly employed to lift and lower materials or to move them horizontally. A combining sliding mode control method with fuzzy regulator is proposed for overhead crane systems in this paper. The ideas behind the combining sliding mode are as follows. First, an intermediate variable is introduced by dividing the system states into two groups. Then, a sliding surface is defined on basis of the intermediate variable. The control law is deduced from Lyapunonv direct method to asymptotically stabilize the sliding surface. In light of the relationship between the reachability of sliding mode and the controller gain, a fuzzy interface system is designed to regulate the controller gain. The stability of the system states is also proven. Simulation results demonstrate the feasibility of the presented method through transport control of an overhead crane system.

Design of reduced order sliding mode governor for hydro-turbines

This paper investigates modeling and control problems of the speed governing system of a hydro-generator unit with one upstream surge tank, driven by a Francis turbine. This governing system is organized into four main functional blocks, namely the hydrodynamic, mechanical, electrical, and servo subsystems. Mathematic models of the individual components are developed and are subsequently interconnected to obtain a model for the governor design. From the viewpoint of modern control theory, only a part of states of this speed governing system are measurable. By introducing an additional state variable, a reduced order sliding mode controller is presented. Simulation results illustrate the feasibility and robustness of the presented method.

Control of a class of under-actuated systems with saturation using hierarchical sliding mode

This paper presents a control scheme of a class of under-actuated systems with saturation using hierarchical sliding mode. This class with a single input and multiple outputs is made up of several subsystems. Based on this physical structure, the hierarchical structure of the sliding mode surfaces is developed as follows. The sliding surface of every subsystem is defined. Then the sliding surface of one subsystem is selected as the first layer sliding surface. The first layer sliding surface is used to construct the second layer sliding surface with the sliding surface of another subsystem. This process continues till all the subsystem sliding surfaces are included. The hierarchical sliding mode control law is deduced by using Lyapunov theorem. On account of saturation nonlinearity of the single input, asymptotic stability of the control system is proven by nonlinear small gain theorem. Parameter ranges of the subsystem sliding surfaces are also given. In practice, simulation and experimental results show the validity of this control method.