An adaptive fuzzy neural networks (FNN) output feedback control approach is proposed for a class of multi-input and multi-output (MIMO) pure-feedback nonlinear systems with unknown backlash-like hysteresis and immeasurable states. The state observers are designed to estimate the unmeasured states, the filtered signals are introduced to circumvent algebraic loop problem encountered in the implem...

In this paper, the backstepping design scheme is developed for the tip-position trajectory tracking control of single-link flexible robotic manipulator systems. An infinite dimensional dynamic model of a single-link flexible manipulator is derived through the assumed modes method associated with Lagrange approach. For simplicity, a linearized system model would be analyzed and investigated for ...

We consider a problem of stabilization of the linearized Schrödinger equation using boundary actuation and measurements. We propose two different control designs. First, a simple proportional collocated boundary controller is shown to exponentially stabilize the system. However, the decay rate of the closed-loop system cannot be prescribed. The second, full-state feedback boundary control desig...

Robust nonlinear controller design with constraint on the poles' location of the linear part of closed-loop system is proposed. The design method is based on the integrator backstepping procedure and linear constrained ∞ H for nonlinear strictfeedback systems with disturbance also in strict-feedback form. The resulted closedloop system will be globally stable, while both local robustness and de...

For a class of MIMO nonaffine block nonlinear systems, a neural networkNNbased dynamic feedback backstepping control design method is proposed to solve the tracking problem. This problem is difficult to be dealt with in the control literature, mainly because the inverse controls of block nonaffine systems are not easy to resolve. To overcome this difficulty, dynamic feedback, backstepping desig...

M. Krstic Dept. Mechanical Engr. University of Maryland College Park, MD 20742 J. M. Protz and J. D. Paduano Massachusetts Institute of Technology Cambridge, MA 02139 P. V. Kokotovic Dept. Electr. & Comp. Engr. University of California Santa Barbara, CA 93106 Abstract. A new systematic method for nonlinear control design|backstepping|is applied to low-order compression system models. Backsteppi...

The position tracking control problem of permanent magnet synchronous motors with parameter uncertainties and load torque disturbance is addressed. Fuzzy logic systems are used to approximate nonlinearities and adaptive backstepping technique is employed to construct controllers. The proposed adaptive fuzzy controllers guarantee that the tracking error converges to a small neighborhood of the o...

For the actuators fault of reconfigurable modular robots, a backstepping decentralized fault tolerant control (DFTC) algorithm is proposed. The reconfigurable robot system is divied into a set of interconnected subsystems. The fault tolerant controller is designed based on backstepping method. It is hard to obtain the model parameters uncertainty term and interconnected term, so the adaptive fu...

This paper presents a new fuzzy Lyapunov controller for nonholonomic mobile vehicles. A symbiosis between classical backstepping techniques and fuzzy logic was realized. The control system ensures a good robustness with respect to outside perturbations. These perturbations can interact with the vehicle. They are sources of uncertainty for the system model and can perturb the validity of the non...

In this paper a novel neural network (NN) backstepping controller is modified for application to an industrial motor drive system. A control system structure and NN tuning algorithms are presented that are shown to guarantee stability and performance of the closed-loop system. The NN backstepping controller is implemented on an actual motor drive system using a two-PC control system developed a...