Fuzzy-Type Nonlinear Systems and Construction of Lyapunov Functions for te Control of Autonomous Robot

1.该报告提出了一个带有仲裁非线性反馈的系统的模式分类。分类是使用robust非线性渗透技术进行的，因为非线性渗透被列为线性稳定系统的非线性渗透。结果显示，如果自动机器人系统在稳定范围内保持非线性谎言的稳定性。我们提出了一个由Sup·Minor Inf·max组合来解决模糊关系等于的算法。这个解决方案是有用的，可以稳定的模糊信息。遗传算法（GA）需要建立一个适合性的功能和评估它以解决问题。然后，由于游戏策略的自动获取问题，这并不容易应用GA，因为GA不能在游戏的可改变情况下固定健身功能。报告给提出的共同进化方法对这个问题是有用的。模糊信息系统的“antecedent”和“consequent”条件很好地与常规非线性反馈的输入和输出相关联。《野蛮渗透技术》显示，如果非线性物质存在于野蛮渗透限制中，模糊控制系统将被验证为稳定性理论，以适应利apunov的稳定性。该报告对模糊控制系统使用这些技术的稳定性进行了调查。

1.The report presents a pattern classification for systems with arbitrary nonlinear feedbacks. Classification is carried using the robust nonlineear-perturbation technipue, 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・min or Inf・max 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. The report has investigated the stability of fuzzy contrl systems using thetechnique.