... of the fuzzy controller is the sum of two nonlinear PI/PD controllers with variable gains. The gain variation and properties of the proposed controllers are studied. Two examples of nonlinear dynamic processes are considered to demonstrate the applicability of the proposed controllers. Contributed...

... fuzzy control fuzzy set theory robust control time-varying systems 29 12 2009 10 03 2011 22 11 2011 22 11 2011 2011 American Society of Mechanical Engineers ...

... conservative results, which will be illustrated in Sec. 4 . 12 11 2009 14 03 2011 21 11 2011 21 11 2011 actuators delays fuzzy control fuzzy systems linear matrix inequalities Lyapunov methods reliability statistical distributions reliable control probabilistic...

... mode attitude control algorithm with an exponential time-varying sliding surface is designed in Ref. [ 14 ], which guarantees the occurrence of the sliding mode at the beginning and eliminates the reaching phase of time-invariant SMC. Fuzzy control is used in Ref. [ 15 ] to approximate the equivalent...

... differential equations fuzzy control Markov processes robust control stochastic systems robust tracking control fuzzy approximation nonlinear stochastic systems Markovian jumps In the past few decades, the stochastic systems governed by the Itô differential equation have been extensively...

... Control Systems ,” IEEE Trans. Fuzzy Syst. 1063-6706 , 14 ( 5 ), pp. 676 – 697 . 10.1109/TFUZZ.2006.883415 Tanaka , K. , and Wang , H. O. , 2001 , Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach , Wiley , New York . Chen , B. -S. , Tseng...

... . Passion , K. , and Yurkovich , S. , 1998 , Fuzzy Control , Addison-Wesley , Reading, MA . The beam’s steady state tip velocity for different controllers during the natural frequency and excitation change. Control type Steady state tip velocity, u ̇ (mm/s) Measured...

... = [ − 217.8616 − 139.1802 ] 56c K 3 , 1 = [ − 229.1276 − 146.4630 ] , K 3 , 2 = [ − 182.6718 − 117.3268 ] Now, we apply the fuzzy controller 13 with the gain matrices 56a , 56b , 56c to system 53 . Let the reference input and the disturbance...

... be maximized for the shortest stopping distance or can be optimally distributed for vehicle stability. vehicle stability wheel slip control tire force estimation target slip assignment brake by wire automotive engineering braking control engineering computing force control fuzzy control...

... technique is applied to a Lur’e-like dynamic system and the Lorenz system as two illustrative examples of chaotic systems. The simulation results verify the effectiveness of this approach in controlling an unknown chaotic system. chaos estimation theory fuzzy control nonlinear dynamical systems...

...Huai-Ning Wu This paper is concerned with the design of reliable robust H ∞ fuzzy control for uncertain nonlinear continuous-time systems with Markovian jumping actuator faults. The Takagi and Sugeno fuzzy model is employed to represent an uncertain nonlinear system with Markovian jumping actuator...

...Chengying Xu; Yung C. Shin In this paper, a multi-level fuzzy control (MLFC) technique is developed and implemented for a creep-feed grinding process. The grinding force is maintained at the maximum allowable level under varying depth of cut, so that the highest metal removal rate is achieved...

...Chein-Chung Sun; Sheng-Ming Wu; Hung-Yuan Chung; Wen-Jer Chang This paper presents a new structure of Takagi-Sugeno (T-S) fuzzy controllers, which is called T-S fuzzy region controller or TSFRC for short. The fuzzy region concept is used to partition the plant rules into several fuzzy regions so...

... neural-fuzzy controller (ANFC) are presented: The former is used to generate desired self-motions in a real-time manner, and the latter is used to prevent the robot from tipping over and to control the end-effector to follow a desired spacial trajectory at the same time. The proposed algorithm does...

... control scheme, a set of Takagi-Sugeno (T-S) fuzzy controllers is synthesized to stabilize the NN linearly interconnected system. Finally, a numerical example with simulations is given to demonstrate the concepts discussed throughout this paper. 19 10 2004 09 08 2005 decentralised...

... = 0.838 486 . Denote the error E y = x 2 ( k ) − x d 2 ( k ) , the fuzzy control rules are given by, R ULE 1 I F E y IS PL T HEN u I S NL R ULE 2 I F E y I S PM T HEN u I S NM R ULE 3 I F...

... architecture for this procedure is illustrated in Fig. 13 . This tool provides us with an integrated environment for fuzzy controller design, analysis, and simulation as well as real-time evaluation of the tension control system. 12 ECU hardware configuration As shown in Fig. 12 , the ECU...

...Wen-Jer Chang; Chong-Cheng Shing In this paper, a method is developed to find the output feedback fuzzy controllers for assigning a common state covariance matrix of discrete Takagi–Sugeno (T–S) fuzzy systems. The fuzzy control approach developed in this paper is based on the concept of Parallel...

... servomechanisms position control three-term control fuzzy control control system synthesis pneumatic actuators pneumatic drives fuzzy logic robust control friction Pneumatic drives are traditionally used in manipulation tasks to quickly move loads between two positions using simple on-off valves...

... multi-robot systems fuzzy control fuzzy logic force sensors end effectors Multiple cooperating manipulators make manufacturing systems more flexible and dexterous by allowing the system to handle complex tasks that are beyond the capacity of a single manipulator. For example, two or more...