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Classification is carried using the robust nonlineear-perturbation technique, in which nonlinearities are regarded as the non-linear perturbation of linear stable systems. The results show that the autonomous robot system can keep stable if nonlinearities lie in the robust-stable range. 2. We have proposed an algorithm that solves fuzyy relation equations given by Sup\u30fbmin or Inf\u30fbmax composite. The solution is useful to establish fuzzy inference. 3. The genetic algorithm(GA) requires setting a fitness function and evaluat-ing it to solve the probrem. then, for the autonomous acquisition problem of game strategy, it is not easy to apply GA because the fitness function can not be fixed in changeable situation of game. The report gives that the proposed co-evolution approach is useful to the problem. 4. The \"antecedent\" and \"consequent\" conditions of fuzzy inference systems are well correlated with input and output of conventional nonlinear feedbacks, respectively. The robust perturbation technique shows that if the nonlinearities are within the robust perturbation limit, the fuzzy control system is verified to be stable according to the stability theorm of Lyapunov. 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