2013.8  Present Pulse Position Coded PDU (PPCP):

A brandnew link layer architecture proposed for energyefficient wireless sensor networking (MAWSN). The key idea is to
encode a PDU in terms of silence duration between two sets of delimiter pulses, whose positions are modulated based on the value of the PDU. This new link architecture offers a suitable
networking technique for severely energystarved networks, and achieves significant energysavings by using lesser amount of bits/pulse transmissions, and by eliminating long multibit
preambles, which are normally used in traditional packets.

The core research contributions are: 1) develops architectural solutions to a subset of
the challenges from transmitting, receiving, idle listening, hidden collision and medium sharing. 2) proposes multiPPCP PDUbased solutions for a multiaccess wireless sensor network, in
which PPCP provides various PDU formats for lowenergy sensors to operate in either transmitter or receiver mode. 3) a concept of Pulse Slot is used for accommodating pulse shifts and for achieving clock synchronization between transmitter and receiver without overhead of preamble
during a PPCP transmission. 4) Flexible Base Digit Separation (FBDS) and the corresponding concrete mathematical principle are developed to mitigate the transmission delay,
which uses a variable coding base to shrink the value. 5) a systematical
error detection theory is established based on the proposed PPCP architecture. 6) a hardware platform—Jurassic—is designed for the purpose of PPCP implementation, and this platform has been
elegantly operating in Green House of MSU Agricultural Department for more than six months.
2007.1  2009.7 Energysaving Technology in Electrical Transmission Systems, A Chinese National 863 Key Program
 To reduce the energy consumption of the electric transmission system, the program developed an electric transmission and control system for highpower permanent
magnet synchronous motors (PMSM) by carrying out the offline simulation, the realtime hardwareintheloop simulation and the physical system experiments
 Adopted the energysaving PMSM as the actuator
 Improved the circuit topological structure of the electric transmission system by applying the power factor correction and the soft switching technology
to the system design
 Designed cost functions, optimal control laws, calculated control rate, and developed control strategies by applying vector control, fuzzy control, and Fourier
integraladaptive control techniques to minimize the energy consumption
Responsibilities
 Analyzed the technical difficulty of the project by carrying out the engineering analysis (from a technical feasibility point of view), the material collection on
fuzzy control and adaptive control, the evaluation of the technical feasibility, and managed the project schedule
 Studied the limitation of the existing control solutions on energysaving, and presented the PMSMoriented vector control algorithm
 Developed the fuzzy control and Fourier integral adaptive control methods to correct the power factors and to achieve the system steadystate precision and the
transient performance
 Created the target functions and the optimal control methods with the aim to minimize the energy consumption
2009.4  2010.10 The Fuzzy Control Approach of Nonlinear Random System under Network
Environment, a project funded by National Natural
Science Foundation of China (No. 60774048)
Responsibilities
 Analyzed the characteristics of the specific nonlinear system under network environment. Carried out fuzzy identification for the nonlinear system, ie. approached
the target nonlinear system within a compact set by the fuzzy identification method and built the TS fuzzy model for the nonlinear system
 Carried out the system modeling by treating as an independent Bernoulli process the data packet loss which is introduced from network transmission, and set an
upper bound for the maximal packet loss ratio
 Solved the random disturbance problem by introducing robust control design, and designed a new robust adaptive controller which could achieve asymptotic stability
of the closedloop system and a better transient state performance
2011.1  2012.3 System Monitoring and Fault Diagnosis of Complex Control Process based on Datadriven, a project funded by National Natural Science Foundation of China (No. 61034005)
Responsibilities

Set up a data set X_{m}_{×n}
(m is the number of sampling points and n is the number of sensors) under normal production conditions, then built a statistical model for the complex
control process; Carried out standardized processing on the data matrix, namely standardized the every column vector in X_{m}_{×n} and got a standardized data matrix X
 According to the principle of CPV (Cumulative Percent of Variance), carried out space decomposition and dimension reduction on data matrix X, and got the first kdimension linear independent vector X _{1} =[
x _{1} , x _{2} ,…, x
_{k} ] to constitute the principal space or loading vectors, and the last (nk)dimension vector X _{2} =[ x _{k+1} , x _{k+2} ,…, x _{n}
] to form the residual space
 Built PCA (Principal Component Analysis) statistical models respectively in the two subspace in order to implement the variable detection in lowdimensional
subspace
 When the statistical data of the established model went beyond the control limit, it indicated that there may be some faults or changes in the complex control
process. Under these circumstances, system detecting was carried out to further determine whether the system has real faults or not
 If faults really do exist in system process, implement characteristics extraction aiming at the subsystem where the faults happened, and
diagnose fault causes. Designed adaptive controllers to get rid of or, for the most part, minimize the impacts on stability of complex control process and
transient performance brought by specific faults