The paper proposes two Nonlinear Model Predictive Control schemes that uncover a synergistic relationship between on-line receding horizon style computation and Particle Swarm Optimization, thus benefiting from both the performance advantages of on-line computation and the desirable properties of Particle Swarm Optimization. After developing these techniques for the unconstrained nonlinear opti...

This paper describes a new multiple-observer approach to Wireless Network Control Systems (WNCS). Two sets of observers are proposed, Lost Sample Observers (LSO) to deal with packet dropout and State Prediction Observers (SPO) to compensate for time-varying delays. These are designed using Linear Matrix Inequalities (LMI), thereby ensuring closed-loop stability. A numerical example, of a cart-m...

We extend the method of controlled Lagrangians to include potential shaping for complete state-space stabilization of mechanical systems. The method of controlled Lagrangians deals with mechanical systems with symmetry and provides symmetry-preserving kinetic shaping and feedback-controlled dissipation for state-space stabilization in all but the symmetry variables. Potential shaping complement...

Recently, MOESP-type closed-loop subspace model identification (CL-MOESP) has been proposed by the authors and its effectiveness has been demonstrated via both numerical simulations and real-life systems, e.g., a cart-inverted pendulum system. However, asymptotic properties of CLMOESP has not yet been studied. The purpose of this paper is to clarify the asymptotic properties of CL-MOESP from th...

The problem of tracking control of nonlinear systems whose the zero dynamics are unstable is addressed in this paper. It is shown that, using a novel cascade structure where the backstepping approach is given to stabilise the internal dynamics and the standard input output linearization to stabilise the external dynamics. Assuming high-gain feedback for the external dynamics, a stability analys...

Based on a power-series approximation method, recurrent neural networks (RNN) are proposed for real-time synthesis and auto-tuning of feedback controllers for nonlinear output regulation systems. The proposed neurocontrol approach represents a novel application of recurrent neural networks to the nonlinear output regulation problem. The proposed approach completely inherits the stability and as...

In this paper, an adaptive fuzzy controller (AFC) for a certain class of unknown nonlinear systems is proposed. The proposed approach employs a fuzzy system to approximate the unknown functions in designing the adaptive controller and an observer is designed to generate an error signal for the adaptive law. The free parameters of the AFC can be tuned on line based on the Lyapunov synthesis appr...

Generally the inverted pendulum is unstable, because the pendulum will fall downward due to the gravitational force acting on mass of the pendulum. Keeping the pendulum at vertically inverted position, the position of DC motor shaft needs to be controlled using closed loop analysis. For closed loop analysis, feedback or input device such as encoder is used. To control and set the pendulum at de...

This paper investigates secure control of Networked Inverted Pendulum Visual Servo Systems (NIPVSSs) based on Active Disturbance Rejection Control (ADRC). Firstly, considering the network- and image-induced delays in conjuction with computational errors caused by image processing attacks, model NIPVSSs is established. Secondly, limitations traditional Single-Input-Single-Output (SISO) ADRC used...