Huaguang Zhang

Multi-Objective Optimal Design of Wind/PV/Pumped-Storage System Based on GA

This paper describes a hybrid wind/PV system which uses pumped-storage station to offset the effects of the inclusion of wind or wind power and to transfer energy form low-use periods to peak-use periods instead of battery. The model of wind/PV/pumped- storage system is given in the paper, under the economic and security criteria conditions, the question of how much wind, PV and pumped storage capacity is addressed by formulating a nonlinear programming optimization problem which is optimized by using GA (genetic algorithm) because of its good global convergence and robustness. Results showed that the optimal system has the characteristic that the LPSP (loss of power supply probability) is merely zero and the CUE (cost of unit energy) is lowest.

Robust and non-fragile H ∞ control for affine fuzzy large-scale systems

This paper investigates robust and non-fragile Hinfin controller design for the affine fuzzy large-scale systems, which are composed of a number of T-S affine fuzzy subsystems with interconnections. According to the Lyapunov direct method and the decentralized control theory of large-scale systems, a sufficient condition in the form of LMIs which guarantees the existence of state feedback Hinfin control for affine fuzzy large-scale systems is proposed. A numerical example is given to demonstrate the fuzzy Hinfin controller design procedure and its effectiveness.

The multi-objective coordinated control of excitation and ASVG of SMIB system based on hamiltonian principle

A multi-objective co-ordinated control scheme for ASVG and synchronous machine excitation to achieve transient stability and voltage regulation enhancement of power systems is presented. First, the new third order nonlinear state-space system model for rotor power angle stability is derived for a single-machine infinite-bus power system with ASVG, the new third order nonlinear state-space system model of ASVG for voltage regulation is given. Then, the non-linear property of the dynamic system is well preserved and utilized, which can meet the requirement of power rotor angle stability and that of ASVG voltage support. with the help of Hamiltonian energy control theory, the variation of system structure, the parameter and the interconnection between the synchronous machine and ASVG are taken into consideration in the multi-objective cocoordinate controller design. In the end, the performance of the proposed multi-objective control scheme is evaluated through a real time test by means of the real time digital simulation. It is shown that the proposed multi-objective coordinated control of excitation and ASVG can provide better system stability and local voltage control.

Power Distribution Fault Diagnosis Based on Rough-Cloud Sets

The volume of data with a few uncertainties overwhelms classic information systems in the distribution control center and exacerbates the existing knowledge acquisition process of expert systems. To deal with the uncertainty and deferent structures of the system, rough sets and cloud theorem are introduced and the rough-cloud sets are proposed. The reduction algorithm based on them is improved. By which, the current and voltage information is employed to fault diagnosis. The paper describes a systematic approach for detecting superfluous data. It is considered as a white box rather than a black box like in the case of neural network. The approach therefore could offer user both the opportunity to learn about the data and to validate the extracted knowledge. The simulation result of a power distribution system shows the effectiveness and usefulness of the approach.

Energy Shaping Repetitive Control (ESRC) for Three-Phase Three-Wire Shunt Active Power Filter

Active Power Filter (APF) is usually used to compensate the harmonic and reactive currents which are generated by the nonlinear load, and its compensation performance mainly depends on the design of controller. When the parameters of the line and load are uncertain or unknown, the system may be unstable. In order to solve this problem, this paper adopts the energy shaping repetitive control (ESRC) to improve the output current waveform of three-phase three-wire shunt active power filter. In this control strategy, the Energy Shaping control is used to guarantee system dynamic performance and the repetitive control is to correct current waveform quality. The new controller design procedure is analyzed in detail. Theoretical analysis and experimental results demonstrate the validity of the proposed method and the filtering performance is improved obviously.

Adaptive tracking control of a class of nonlinear time-delay systems with NN actuator saturation compensation

In this paper, adaptive tracking control is investigated for a class of nonlinear time-delay systems with actuator saturation nonlinearity. The uncertain time-delay function is bounded by a nonlinear function with unknown coefficients. The actuator saturation nonlinearity is assumed to be nonsymmetric and unknown. Neural network approximation techniques are utilized to compensate the saturation nonlinearity and the NN saturation compensator is placed in a feed-forward path, which is easy to be implemented. Based on Lyapunov approach, the resulting closed-loop control system performance and the boundedness of the NN weights are derived and guaranteed, and the tracking error exponentially converges to a small adjustable neighborhood of zero. Simulation studies are included to demonstrate the effectiveness of the proposed approach.

T-S fuzzy modeling and control for a class of chaotic (hyperchaotic) systems with uncertain parameters

A novel T-S fuzzy model-based method is proposed for controlling a class of chaotic (hyperchaotic) systems with uncertain parameters. The interval matrix theory is applied to describe the parametric uncertainty. The T-S fuzzy model is employed for accurately modeling the chaotic (hyperchaotic) systems. Based on the T-S fuzzy model, the parallel distributed compensation (PDC) technique is applied to design a state feedback controller for the chaotic (hyperchaotic) systems. By using Lyapunov stability theory, the robust stability of the closed-loop system is proved. The new scheme considers the interactions of the fuzzy sub-systems sufficiently. The gain matrices of the controller can be obtained by solving a set of linear matrix inequalities (LMIs). Simulation results are presented to demonstrate the effectiveness of the proposed method.

Fuzzy H/spl infin/ filter design for a class of nonlinear discrete-time system with time delays

This paper studies fuzzy H/sub /spl infin// filter for signal estimation of nonlinear discrete-time systems with time delays and unknown bounded disturbances. First, the Takagi and Sugeno (T-S) fuzzy model is proposed to represent the state-space model for a nonlinear discrete-time system with time delays. Next, we design a stable fuzzy H/sub /spl infin// filter based on T-S fuzzy model, which assures asymptotic stability and a prescribed H/sub /spl infin// index for the filtering error system. Sufficient condition for the existence of such a filter is established in terms of linear matrix inequality problem (LMIP). The LMIP can be efficiently solved using convex optimization techniques with global convergence guaranteed, such as the interior point algorithm. Simulation example is made to illustrate the efficiency of the proposed method.

Genetic algorithm to fixed-order H/sub 2//H/sub /spl infin// adaptive filter for leak detecting signal of pipeline

Some difficulties exist in the signal processing of the leak detection of pipeline that is caused by the low signal-to-noise ratio. It can enhance signal-to-noise ratio for pressure and flow signals by the mixed H/sub 2//H/sub /spl infin// adaptive noise cancellation (MHANC). The MHANC is proposed to achieve the H/sub 2/ optimal reconstruction and a desired robust against the effect of uncertainties in signal processing from the H/sub /spl infin// norm perspective. In order to simplify implementation and conserve operation time, the fixed-order MHANC is design from the practical design perspective. The genetic algorithm (GA) was used to obtain the optimum coefficients of the fixed-order MHANC. Practice results show that the fixed-order MHANC can obtain a excellent reconstruction of pressure and flow signals to improve the ability of the leak detecting of pipeline. Furthermore, reconstruction performance of the fixed-order MHANC is acceptable even if the coefficients of the noise cancellation are fixed or the noise character changes.

Asymptotic stability of a class of generalized Hopfield neural networks with time delay and nonsymmetric interconnecting structure

Since time delay and parameters uncertainty are inevitable, the asymptotic stability of the generalized Hopfield neural networks with time delay and nonsymmetric interconnecting structure is analyzed. The sufficient conditions for the asymptotic stability of equilibrium point are established by way of constructing a suitable Lyapunov functional and sector conditions. The simulation results are presented to prove the effectiveness of the conclusion.