Stabilization fuzzy control of inverted pendulum systems

Underactuated robotics: A review

Underactuated robotics is an emerging research direction in the field of robotics. The control input of the underactuated robot is less than the degree of freedom of the system. It has the advantages of lightweight, low energy consumption, excellent performance, and broad development prospects. This article reviews the state of the art on underactuated robotics. On the basis of previous studies, this article takes the non-holonomic constraint equation as the entry point to classify and summarize underactuated robot and their common mechanisms. The controllability of underactuated robot is further discussed. The control flow of underactuated robot is described based on the open–closed control method. In the closed-loop control, the control method based on the fuzzy system is mainly used. Finally, the difficulties in the current research of underactuated robot are summarized, and the future research directions are prospected.

Differentiation-Free Multiswitching Neuroadaptive Control of Strict-Feedback Systems

Issues of differentiation-free multiswitching neuroadaptive tracking control of strict-feedback systems are presented. It mainly consists of a set of nominal adaptive neural network compensators plus an auxiliary switched linear controller that ensures the semiglobally/globally ultimately uniformly bounded stability when the unknown nonlinearities are locally/globally linearly bounded, respectively. In particular, the so-called explosion of complexity is annihilated in two steps. First, a set of first-order low-pass filters are constructed for solving such a problem in the nominal neural compensators. In contrast to most existing dynamic surface control-based schemes, bounded stability of the filter dynamics is ensured by virtue of the localness and hence boundedness of the neural compensators. Separation of controller-filter pairs is thus achieved in this paper. Next, an auxiliary switched linear state feedback control is synthesized to further solve such a problem in the nonneural regions. Besides being differentiation-free, such an approach provides more flexibility for meeting various control objectives at a time. An earlier proposed smooth switching algorithm is also incorporated to tackle the control singularity problem. Finally, simulation works are presented to demonstrate the validity of the proposed scheme.

Design of Adaptive Fuzzy Control for a Class of Networked Nonlinear Systems

This paper presents an adaptive fuzzy controller for a class of unknown nonlinear systems over network. The network-induced delays can degrade the performance of the networked control systems (NCSs) and also can destabilize the system. Moreover, the seriousness of the delay problem is aggravated when packet losses occur during a transmission of data. The proposed controller uses a filtered tracking error to cope the time-varying network-induced delays. It is also robust enough to cope some packet losses in the system. Fuzzy logic systems (FLSs) are used to approximate the unknown nonlinear functions that appear in the tracking controller. Based on Lyapunov stability theory, the constructed controller is proved to be asymptotically stable. Stability of the adaptive fuzzy controller is guaranteed in the presence of bounded external disturbance, time-varying delays, and data packet dropouts. Simulated application of the inverted pendulum tracking illustrates the effectiveness of the proposed technique with comparative results.

Intermittent appearances of saddle-type hyperbolic dynamics during human stick balancing on a manually controlled cart

Stabilization of an inverted pendulum on a manually controlled cart (cart-inverted pendulum; CIP), analogous to human fingertip stick balancing, is considered to get insights of how the human central nervous system stabilizes unstable dynamics. We explore a possibility that a type of intermittent control strategy proposed for human postural control might also be applicable to the CIP task, i.e., whether a transient contracting dynamics along a stable manifold of a saddle-type equilibrium of the non-controlled inverted pendulum is exploited intermittently. To this end, we measured task performances during CIP balancing from several experimental subjects. Intermittent appearances of hyperbolicity as typical characteristics reflecting the intermittent control strategy were examined in the recorded motion data using phase space analysis and wavelet analysis. We show that skilled subjects tend to exhibit those characteristics, suggesting that they stabilize upright posture of the stick by utilizing the intermittent control strategy.

A COMPOSITIONAL METHOD USING AN EVOLUTIONARY ALGORITHM FOR FINDING FUZZY RULES IN 3-LAYERED HIERARCHICAL FUZZY STRUCTURE

This paper presents a novel compositional method for finding fuzzy rules in a three-layered hierarchical fuzzy structure. The proposed method incorporates a multi-objective evolutionary algorithm and a large set of initial conditions, including dynamical conditions of the system under investigation. The proposed method is focused on handling the large set of initial conditions by a multi-objective evolutionary algorithm and it can be applied to a wide range of dynamical control systems in robotics. The method has been evaluated on a dynamical system such as the inverted pendulum. The experimental results and analysis showed that the proposed method is much better than the existing methods such as amalgamation and single objective evolutionary algorithm based methods.