Advanced genetic algorithms applied in MRFACS for fuzzy rules set optimization

This paper presents a theoretical study on a model-reference adaptive fuzzy logic controller for vector-controlled permanent magnet AC servomotor drives. In the proposed system, fuzzy logic is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The results are compared with that provided by a nonadaptive fuzzy controller. The implementation of proposed adaptive fuzzy controller is also discussed.

This paper develops a fuzzy model reference adaptive control of continuous-time nonlinear systems described by Takagi-Seguno (TS) fuzzy model. The tracking performance is assured using a direct TS fuzzy controller. Both full state information and observer-based control schemes are investigated. It is proved, using Lyapunov stability tools, that this adaptive scheme is asymptotically stable and the tracking and observation errors converge to zero. Simulation results illustrate the performance of the proposed approach.

This paper presents a method for fuzzy model reference adaptive control system design for a partially known multi-input multi-output (MIMO) linear dynamic plant. Differential or convolutional equations can describe the plant to be controlled, and the fuzzy controller is assumed to be from the MIMO sector-bounded nonstationary nonlinearities class. The task is to obtain robust adaptive stabilization. Some absolute stability theorems and integral evaluations of the state and control vectors are applied in the MIMO fuzzy adaptive controller design procedure for the first time. A method for automatically obtaining a near-optimal nonlinear dynamic reference model is described. A practical step-by-step procedure of the MIMO adaptive fuzzy controller design is proposed, resulting in highly interpretable MIMO fuzzy control rules based on triangular fuzzy sets and strong triangular fuzzy partition. An example of the fuzzy controller design according to the proposed procedure is given.

In this paper, we study the application of fuzzy set theory, genetic algorithms and rough set theory techniques to the control of the rectifier. A fuzzy adaptive control scheme with the aid of rough set theory via genetic algorithms (GAs) finding the center parameters in place of the classical control is proposed. On the one hand, genetic algorithm gets optimal parameters of an accurate domain model, which tunes the scaling factors of fuzzy adaptive control but is hardly established in a non-liner system. On the other hand, fuzzy adaptive control deals with the dynamics and complexity of responses from rectifier of a HVDC system in the operation points, by adjusting its control parameters with the aid of rough tuner adaptively. Our study includes a brief introduction to fuzzy control and rough set algorithms, both theory and application. We also evaluate the performance of rough fuzzy control by simulation in the paper. The focus of our experiments is on the constant current control in rectifier side of HVDC system. The result shows there are many improvements offered by the fuzzy control scheme based on rough set theory in comparison with the only fuzzy control scheme in the rectifier side of HVDC system.

This paper concerned with different control strategies used to balance (control) inverted pendulum system. The often used control strategy is PID tuning, but in PID the main issue is parameter tuning according to the process parameter variation. So proposed strategy is MRAC, combination of model reference adaptive Control (MRAC) with fuzzy. The main aim is to find further improvement of traditional MRAC method and to provide more accurate control to the inverted pendulum and to minimize drawbacks of the traditional MRAC method. This is examined when combining the MRAC method with Fuzzy control. The performance of the application system is examined from the simulation results in MATLAB/SIMULINK. For showing its effectiveness, simulated results are compared with the traditional control strategies like fuzzy and MRAC. Incorporating application for inverted pendulum system, subjected to it finds the analogy with various control system applications like satellite launching system, robotic arm etc.

We present efficient parallel matrix multiplication algorithms for linear arrays with reconfigurable pipelined bus systems (LARPBS). Such systems are able to support a large volume of parallel communication of various patterns in constant time. An LARPBS can also be reconfigured into many independent subsystems and, thus, is able to support parallel implementations of divide-and-conquer computations like Strassen's algorithm. The main contributions of the paper are as follows. We develop five matrix multiplication algorithms with varying degrees of parallelism on the LARPBS computing model; namely, MM/sub 1/, MM/sub 2/, MM/sub 3/, and compound algorithms C/sub 1/(/spl epsiv/)and C/sub 2/(/spl delta/). Algorithm C/sub 1/(/spl epsiv/) has adjustable time complexity in sublinear level. Algorithm C/sub 2/(/spl delta/) implies that it is feasible to achieve sublogarithmic time using /spl sigma/(N/sup 3/) processors for matrix multiplication on a realistic system. Algorithms MM/sub 3/, C/sub 1/(/spl epsiv/), and C/sub 2/(/spl delta/) all have o(/spl Nscr//sup 3/) cost and, hence, are very processor efficient. Algorithms MM/sub 1/, MM/sub 3/, and C/sub 1/(/spl epsiv/) are general-purpose matrix multiplication algorithms, where the array elements are in any ring. Algorithms MM/sub 2/ and C/sub 2/(/spl delta/) are applicable to array elements that are integers of bounded magnitude, or floating-point values of bounded precision and magnitude, or Boolean values. Extension of algorithms MM/sub 2/ and C/sub 2/(/spl delta/) to unbounded integers and reals are also discussed.

We study the space complexity of refuting unsatisfiable random k-CNFs in the resolution proof system. We prove that for any large enough /spl Delta/, with high probability a random k-CNF over n variables and /spl Delta/n clauses requires resolution clause space of /spl Omega/(n/spl middot//spl Delta//sup -1+/spl epsiv//k-2-/spl epsiv//), for any 0 >/spl radic/n. This bound is nearly tight. Specifically, we show that with high probability, a random 3-CNF with /spl Delta/n clauses requires tree-like refutation size of exp(/spl Omega/(n//spl Delta//sup 1+/spl epsiv//1-/spl epsiv//)), for any 0</spl epsiv/<1/2. Our space lower bound is the consequence of three main contributions. 1. We introduce a 2-player matching game on bipartite graphs G to prove that there are no perfect matchings in G. 2. We reduce lower bounds for the clause space of a formula F in resolution to lower bounds for the complexity of the game played on the bipartite graph G(F) associated with F. 3. We prove that the complexity of the game is large whenever G is an expander graph. Finally, a simple probabilistic analysis shows that for a random formula F, with high probability G(F) is an expander. We also extend our result to the case of G-PHP, a generalization of the pigeonhole principle based on bipartite graphs G. We prove that the clause space for G-PHP can be reduced to the game complexity on G.

Summary form only given. The single-particle theory of electron multipactor is now well understood. The multipactor parameter space is spanned by the normalized magnetic and electric field parameters. In particular, for given normalized magnetic field /spl Omega/ multipactor can errupt within a certain range of electric field amplitudes /spl epsi//sub 1/</spl epsi/</spl epsi//sub 2/; to each value /spl epsi/ corresponds a different locked-phase /spl phi/. Once a multipactor has been launched, it is very important to know the saturation level; the latter determines the cavity power losses when the multipactor is a parasitic side effect, or the saturated current when a multipactor is deliberately triggered for the production of short period high current pulsed beams. The collective space charge effects must be included to address multipactor saturation. One proposed approach employs a single charge sheet and yields saturation when the secondary emission coefficient /spl delta/ equals one. Setting /spl delta/=1 fixes the impact parameters and therefore the value of the driving electric field /spl epsi/; the external RF field adjusts to that value through the nonlinear effect of the induced multipactor current on the cavity LC circuit. A limitation of the method is that one must start near the appropriate /spl epsi/ since the range of the voltage self-adjustment is usually small. A most general approach introduced here is based on multilayered space charge cloud involving electrons emitted at slightly different times. There is a continuous distribution of impact energies and interaction phases between the leading and the trailing edge of the bunch.

This paper demonstrates tracking control of a class of feedback linearizable unknown nonlinear dynamical systems, such as a robotic systems, using a discrete-time fuzzy logic controller (FLC). Designing a discrete-time FLC is significant because almost all FLC's are implemented on digital computers. A repeatable design algorithm and a stability proof are examined for an adaptive fuzzy logic controller that uses fuzzy basis functions based on the fuzzy system, unlike most standard adaptive control approaches which use basis vectors depending on the unknown plant. An /spl epsiv/-modification sort of approach to adapt the fuzzy system parameters is examined. Using this adaptive fuzzy logic controller, uniform ultimate boundedness of the closed-loop signals is presented and that the controller achieves tracking. In fact, the fuzzy system designed is a model-free universal fuzzy controller that works for any system in the given class of systems.

Fuzzy controller design of micro-unmanned helicopter relying on improved genetic optimization algorithm

Abstract- This paper introduces a linear structure of wind turbine, operator and the pitch angle controller. Then, a new method of adaptive fuzzy on the variable speed wind turbines was provided and it was compared with PID and Fuzzy Logic Control ler and the simulation results were analyzed. So when the results of each simulation using PID and Fuzzy controllers and adaptive fuzzy PID controllers provided, the observed advantages and disadvantages of the rotor speed and wind turbine power can be introduced. It can be seen that in PID method the high overshoot is discussed as a disadvantage while it is overcome by using fuzzy controller and overshoot will decrease. The time of reaching to a sustained speed increases slightly and in adaptive fuzzy PID controller, the less overshoot has provided a good and effective performance for system response. The use of adaptive fuzzy PID controller causes the system does not have any steady-state error and at all moments of time, the response rate is better than PID and fuzzy controller. The importance of the amount of overshoot and rate fluctuations is that by reducing these parameters in addition to reducing the cost of preventive care, maintenance and depreciation, the fluctuations in electricity generated by induction generator also greatly reduced.

To achieve a better robustness and get a static response of a certain target missiles in longitudinal control, a mathematical model of target missiles is established. The uncontrolled trajectory, the predetermined trajectory and the requirements of the predetermined trajectory are analyzed next. Then the trajectory instruction angle is designed to ensure the stable flight of the target missiles system. To solve the problem that the PID controller cannot adjust parameters online and the output is easy to be disturbed by external noise, the fuzzy adaptive PID control is designed. It enhanced the robustness of the target missiles by fuzzy control, and also has a good response by using PID control. The simulation experiments show the fuzzy adaptive control system can track the predetermined trajectory rapidly and smoothly, and the static error and overshoot were significantly reduced. When the system are affected by noise, the fuzzy adaptive PID control can achieve a good robustness than traditional PID controller.

Research on A Fuzzy Adaptive PID Control Method for Four Rotor UAV Control System With the continuous improvement of national living standards, people have higher and higher requirements for the reliability of power supply. The emergence of unmanned aerial vehicle inspection technology provides a new idea to solve the contradiction between the increasing equipment scale and the increasing inspection requirements. However, at present, the stability of the traditional proportion integration differentiation (PID) control system of the four rotor unmanned aerial vehicle (UAV) is not high enough. During the inspection, there are accidents of drones hitting power equipment from time to time. In view of the above problems, this paper studies the fuzzy adaptive PID control method to support the stable flight of four rotor UAV. The principle of fuzzy control is analyzed. The fuzzy control method and PID control method are deeply integrated. A fuzzy adaptive PID control system is designed. The universe and membership function of the relevant control parameters of the system are formulated. The tuning rules of fuzzy adaptive PID control system are formulated. Finally, the improved control system is simulated. The simulation results show that the fuzzy adaptive PID control algorithm can effectively improve the stability, reliability and emergency ability of UAV. This method can effectively improve the adaptability of UAV to perform complex missions in complex environments. The research results have guiding significance for expanding the application field of UAV.

This paper describes various control strategies used for controlling the desired heading angle of the Autonomous under water vehicle(AUV). The control of AUV is a great challenge for the researchers due to the time varying and highly nonlinear effect of hydrodynamic forces. The presence of communication constraints and the external disturbances inside the fluid makes the design of control action of AUV more difficult. In these situation the adaptive controller techniques such as Model reference adaptive controller (MRAC) is more suitable. The proposed new adaptive controller Fuzzy Model Reference Adaptive Controller (FMRAC) technique is the combination of MRAC and Fuzzy logic which produces better transient performance. The heading controller is designed and their performance is examined through the MATLAB/SIMULINK. The time response characteristics of the proposed controller are compared with traditional MRAC and FUZZY. The FMRAC has the ability to produce the stable operation and more effectiveness for controlling the heading angle.

Considering wind power generation system with variable-speed squirrel-cage induction generators (SGIG), a Model Reference Fuzzy Adaptive (MRFA) controller was proposed for harvesting the maximum power from wind, The designed MRFA controller was established by embedding fuzzy controller into model reference adaptive control framework, substituting complicated traditional adaptive rules with the fuzzy inverse model. The simplified control model was applied to the Wind Energy Conversion System (WECS) and the simulation was well done. The simulation results show that the proposed controller has the advantages of shortening the time for system adjustment and quickening the response speed, higher anti -interference ability and adaptability to parameter varation than conventional PID controllers.