Hybrid control of biped robots in the double-support phase via H∞ approach and fuzzy neural networks

Adaptive robust controls of biped robots

“…Efforts were also made to build complete models to represent the whole periodic walking motion and three phases of the walking cycle (single‐support, double‐support, and transition phase) as an integrated model, such that the performance and stability analysis of the whole closed‐loop motion system could be improved, such as in [11, 15, 19]. In the recent, using the approximation property of the fuzzy systems and the neural networks, adaptive control have obtained many results [20–23].…”

Traffic Signal Predictive Control Based on Cellular Automata Prediction Model and Non-Analytical Optimization

“…Aboudolas et al [4] utilized the store-and-forward model to capture traffic dynamics and demonstrated the control efficiency and real-time feasibility of model predictive control. Fu et al [5] and Liu et al [6] proposed model predictive control strategy based on the prediction model of neural network.…”

Adaptive control of single‐input single‐output hybrid systems possessing interacting discrete‐ and continuous‐time dynamics

“…Hybrid systems sometimes incorporates also logic switching rules, [15,34] or the use of numerical tools, [28]. They offer a wide range of models for applications in the fields of robotics, compartmental dynamic models, control of DC or induction servomotors, Fuzzy systems, neural networks or computational techniques (see, for instance, [2,18,19,22,25,26,27,30,36,37]). In particular, the use of so-called hybrid functions (block-pulse functions plus Legendre polynomials) is of usefulness in the analysis and optimal control of linear delay systems, [27].…”