ZG stabilization and tracking control for bilinear system of u-integration type

The Line-of-Sight stabilization and tracking control based on gyro stabilized platform is required to isolate Line of sight from the movement and vibration of carrier and ensure pointing and tracking for target in electro-optical tracking system.This work describes the design of a high performance controller for an electromechanical target tracking system with an optical sensor for sighting.The control law has been obtained using a linear model of the electro mechanical system.The modelling of the system has been carried out using the experimental frequency response data.The PID adesigning of control system methodology has been used to design the controller and study the comparative analysis using both controller and optimized tuned performance is also seeing by using the designing the PID controller in different loop analysis and study responses of system by using step response and frequency response analysis by using the bode diagram so as to stabilize the line of sight stabilization and tracking control system.The mixed sensitivity optimisation problem has been posed and weighting functions are selected by using the gradient and dissent method having more numbers of iterations so that they not only encapsulate all the design goals but also accommodate the modelling uncertainties.A stabilising controller with excellent robustness properties has been obtained.Investigator has used MATLAB for the designing of controller and simulated the system for a required criterion of the system.

This paper presents development of an autonomous flying robot (unmanned aerial vehicle) and its verification via flight control experiment. The autonomous flying robot has a global positioning system (GPS) sensor to control its altitude and also a wireless camera to gather visual information from the air. First, we construct a longitudinal model of the autonomous flying robot to design a stable controller using a common Lyapunov approach. The longitudinal model has three degree of freedom, i.e., the altitude, the horizontal position and the pitch angle. A stable controller is designed so as to guarantee the stability of the trajectory tracking control system for the three-degree-of-freedom model. The experimental result demonstrates the viability of the stable trajectory tracking control.

Challenging simulation practice (failure and success) on implicit tracking control of double-integrator system via Zhang-gradient method

This paper investigates network-based output tracking control for a T-S fuzzy system that can not be stabilized by a nondelayed fuzzy static output feedback controller, but can be stabilized by a delayed fuzzy static output feedback controller. By intentionally introducing a communication network that produces proper network-induced delays in the feedback control loop, a stable and satisfactory tracking control can be ensured for the T-S fuzzy system. Due to the presence of network-induced delays, the fuzzy system and the fuzzy tracking controller operate in an asynchronous way. Taking the asynchronous operation and network-induced delays into consideration, the network-based tracking control system is modeled as an asynchronous T-S fuzzy system with an interval time-varying delay. A new delay-dependent criterion for L2 -gain tracking performance is derived by using the deviation bounds of asynchronous normalized membership functions and a complete Lyapunov-Krasovskii functional. Applying a particle swarm optimization technique with the feasibility of the derived criterion, a novel design algorithm is presented to determine the minimum L2 -gain tracking performance and control gains simultaneously. The effectiveness of the proposed method is illustrated by performing network-based output tracking control of a Duffing-Van der Pol's oscillator.

This paper presents a nonlinear control technique, feedback linearization, for an electromagnetic suspension (EMS) system which is a nonlinear system. It is shown that the EMS system is feedback linearizable as it satisfies the required conditions. For the EMS system, feedback linearization technique is used to design stabilization control and tracking control. For the tracking control a random sinusoidal trajectory is taken as the reference signal. Also, these results are compared with that obtained using the standard linear state-feedback controller whose design is based on a linearized model of the plant obtained by small perturbations of the plant around an operating point.

In this paper, we propose an improved adaptive trajectory tracking control scheme for wheeled mobile robots without using velocity measurement. At first, a modified tracking error equation is developed. Based on the modified tracking error equation, a modified adaptive tracking controller is developed. The developed controller does not require measurements of longitudinal velocity. In the control system using the controller, robust tracking control can be achieved for uncertainties of the weight, the moment of inertial and the position of gravity center. In addition, even if the characteristics of left and right motors to drive wheels are unknown and different, stable tracking control can be also achieved.

A new method to design asymptotically stabilizing and adaptive control laws for nonlinear systems is presented. The method relies upon the notions of system immersion and manifold invariance and, in principle, does not require the knowledge of a (control) Lyapunov function. The construction of the stabilizing control laws resembles the procedure used in nonlinear regulator theory to derive the (invariant) output zeroing manifold and its friend. The method is well suited in situations where we know a stabilizing controller of a nominal reduced order model, which we would like to robustify with respect to higher order dynamics. This is achieved by designing a control law that asymptotically immerses the full system dynamics into the reduced order one. We also show that in adaptive control problems the method yields stabilizing schemes that counter the effect of the uncertain parameters adopting a robustness perspective. Our construction does not invoke certainty equivalence, nor requires a linear parameterization, furthermore, viewed from a Lyapunov perspective, it provides a procedure to add cross terms between the parameter estimates and the plant states. Finally, it is shown that the proposed approach is directly applicable to systems in feedback and feedforward form, yielding new stabilizing control laws. We illustrate the method with several academic and practical examples, including a mechanical system with flexibility modes, an electromechanical system with parasitic actuator dynamics and an adaptive nonlinearly parameterized visual servoing application.

Zhang dynamics (ZD) and gradient dynamics (GD) are two types of powerful methods for online problems solving. In this paper, a classic nonlinear system of Van der Pol oscillator in the affine-control form is investigated. By combining the ZD and GD methods, a method called Zhang-gradient (ZG) method is proposed to design a ZG controller for the trajectory generation of the aforementioned nonlinear oscillator. Simulation results of ZG trajectory generation further demonstrate the feasibility and effectiveness of the ZG controller with the division-by-zero problem successfully handled. In addition, we investigate the effects of the ZD and GD design parameters on the ZG controller.

During recent years there has been considerable interest in using bilinear systems [1, 2] as mathematical models to represent the dynamic behavior of a wide class of engineering, biological and economic systems. Moreover, there are some methods [3] which may approximate nonlinear control systems by bilinear systems. For the first time Zubov has proposed a method of stabilization control synthesis for a set of programmed motions in linear systems [4]. In papers [5, 6] this method has been developed and used to solve the same problem for bilinear systems.In the present paper the following problems are considered. First, synthesis of nonlinear control as feedback under which the bilinear control system has a given set of programmed and asymptotic stable motions. Because this control is not unique, the second problem concerns optimal stabilization. In this paper a method for the design of nonlinear optimal control is suggested. This control is constructed in the form of a convergent series. The theorem on the sufficient conditions to solve this problem is represented.

This paper investigates the original Zhang-gradient (ZG) control failure for the output tracking, which is caused by the system states tending to infinity in the time-varying nonlinear scalar (TVNS) systems. Aiming at solving this problem, the extra Zhang dynamics aid (EZDA) approach is considered, and EZDA controllers are designed. Meanwhile, mathematical derivations are presented, and numerical experiments are conducted, substantiating that this control strategy proposed by the EZDA approach is good. This means that the original ZG control failure is effectively solved. Specifically, the effectiveness and feasibility of the EZDA approach are verified.

When a homogeneous bilinear system is dyadic, it permits the use of the so-called division controller for global stabilization. However, due to singularities in the control law, a dead-zone must be cascaded with the division controller in practical implementation. The contribution of this note is to show that the division controller, when cascaded with a dead-zone, can asymptotically drive the bilinear system state into a bounded set around the origin with the size of the bounded set proportional to the size of dead-zone. This note further proposes a C/sup 0/ modification and a C/sup /spl infin// modification of the conventional discontinuous dead-zone so that the control signals from the modified division controllers are continuous and smooth, respectively.

This paper presents the problems of accurate identification and learning control of ocean surface ship in uncertain dynamical environments. Thanks to the universal approximation capabilities, radial basis function neural networks (NNs) are employed to approximate the unknown ocean surface ship dynamics. A stable adaptive NN tracking controller is first designed using backstepping and Lyapunov synthesis. Partial persistent excitation (PE) condition of some internal signals in the closed-loop system is satisfied during tracking control to a recurrent reference trajectory. Under the PE condition, the proposed adaptive NN controller is shown to be capable of accurate identification/learning of the uncertain ship dynamics in the stable control process. Subsequently, a novel NN learning control method which effectively utilizes the learned knowledge without re-adapting to the unknown ship dynamics is proposed to achieve closed-loop stability and improved control performance. Simulation studies are performed to demonstrate the effectiveness of the proposed method.

New stabilization and tracking control laws for electrohydraulic servomechanisms

This paper presents trajectory tracking control of a kind of flying robots (a powered paraglider (PPG)) and its verification by experiments. The PPG has a GPS sensor to control its 3D position and a wireless camera to gather information from the air. We update the autonomous flight system (constructed in our previous paper) by adding the function of real-time monitoring on 3D positions and control inputs. In addition, we design a stable controller to guarantee the stability of the trajectory tracking control system for the simplified three-degree-of-freedom dynamics of the PPG. Experimental results show that altitude control is perfectly realized via the stable controller and circular flight control is also demonstrated.

In this brief, we consider the problem of tracking a desired trajectory for fully actuated ocean vessels, in the presence of uncertainties and unknown disturbances. The combination of approximation-based and domination design techniques allows us to handle time-varying disturbances, without the need for explicit knowledge of the bounds. Using backstepping and Lyapunov synthesis, the stable tracking controller is first designed for the full-state feedback case. Subsequently, the output feedback problem is tackled by employing a high-gain observer to estimate the unmeasurable states required by the stable tracking controller. Under the proposed control, semiglobal uniform boundedness of the closed-loop signals is guaranteed for both full-state and output feedback cases.