© Springer International Publishing Switzerland 2014
Z. Zeng et al. (Eds.): ISNN 2014, LNCS 8866, pp. 150–158, 2014.
DOI: 10.1007/978-3-319-12436-0_17
Memristive Radial Basis Function Neural Network
for Parameters Adjustment of PID Controller
Xiaojuan Li
1
, Shukai Duan
1(
)
, Lidan Wang
1
, Tingwen Huang
2
, and Yiran Chen
3
1
College of Electronic and Information Engineering,
Southwest University, Chongqing, China
duansk@swu.edu.cn
2
Department of Electrical and Computer Engineering,
Texas A&M University, Doha, Qatar
3
Department of Electrical and Computer Engineering,
University of Pittsburgh, Pittsburgh, USA
Abstract. Radial basis function (RBF) based-identification proportional–
integral–derivative (PID) can automatically adjust the parameters of PID con-
troller with strong self-organization, self-learning and self-adaptive ability.
However, the compound controller has complex weight updating algorithm and
large calculation. Memristor, applied well to the investigation of storage circuit
and artificial intelligence, is a nonlinear element with memory function. Thus, it
can be introduced to RBF neural network as electronic synapse to save and up-
date the synaptic weights. This paper builds a model of memristive RBF-PID
(MRBF-PID), and proposes the updating algorithm of weight upon
memristance. The proposed MRBF-PID is used for the control of a nonlinear
system. Its controlling effect is showed by numerical simulation experiment.
Keywords: Memristor · Radial basis function neural network · PID controller ·
Simulink model
1 Introduction
Based on the completeness of circuit, Chua proposed theoretically the notion of
memristor in 1971 [1]. In 2008, a team at HP Labs announced that the physical model
of memristor had been realized, which verified the existence of memristor [2-3], and
attracted major research fields’ attention. By reason of memristor’s non-volatile
memristive behavior and dynamic change resistance characteristic, we can primely
introduce it into, for example, storage circuit, neural network and pattern recognition
etc. Memristor has nanoscale size, which can greatly simplify the circuit by being
applied in the large scale integrated circuit.
PID controller is the primary means of control in industrial control systems. In
traditional PID controller, once the parameters are identified in the process, they can
not be adjusted any more; therefore, systems can not achieve perfect controlling
effect. Radial basis function neural network (RBF) is a local approximation network.
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