Hybrid Adaptive Law Research Articles

Hybrid Adaptive Robust Controller on Inertial Gyro LOS Platform

This paper was presented one new modified controller scheme for inertial gyro control system. Based on Narendras hybrid adaptive law, the modified algorithm was variable metric that took use of parameter matrix Γk to obtain two updating laws in turn online. The key modified contents were: 1) the output y (t) was passed by one low-pass filter, 2) the parameter was updating in term of one proper initial Γ0 and the measurable values. The objective of the proposed new adaptive robust control schemes was to achieve fast convergence of parameter updating, and promise good robust stability of control system during tracking, reduce the tracking error at start-time with filtered output.

Hybrid adaptive control of a dragonfly model

Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.

Hybrid adaptive fuzzy identification and control of nonlinear systems

We present a combined direct and indirect adaptive control scheme for adjusting an adaptive fuzzy controller, and adaptive fuzzy identification model parameters. First, using adaptive fuzzy building blocks, with a common set of parameters, we design and study an adaptive controller and an adaptive identification model that have been proposed for a general class of uncertain structure nonlinear dynamic systems. We then propose a hybrid adaptive (HA) law for adjusting the parameters. The HA law utilizes two types of errors in the adaptive system, the tracking error and the modeling error. Performance analysis using a Lyapunov synthesis approach proves the superiority of the HA law over the direct adaptive (DA) method in terms of faster and improved tracking and parameter convergence. Furthermore, this is achieved at negligible increased implementation cost or computational complexity. We prove a theorem that shows the properties of this hybrid adaptive fuzzy control system, i.e., bounds for the integral of the squared errors, and the conditions under which these errors converge asymptotically to zero are obtained. Finally, we apply the hybrid adaptive fuzzy controller to control a chaotic system, and the inverted pendulum system.

Robust model reference adaptive control with hybrid adaptive law

Robust model reference adaptive control (RMRAC) with hybrid adaptive law is considered. The advantages of the hybrid RMRAC scheme over other continuous counterparts include smaller computational effort during implementation and better robustness properties in the presence of modelling errors and disturbances. For the hybrid adaptive control scheme, stability and the tracking performance are analysed rigorously.

Robust adaptive LQ control schemes

The certainty equivalence principle is used to combine a robust adaptive law with a control structure derived from the linear quadratic (LQ) control problem. The resulting adaptive control scheme is applicable to minimum and nonminimum phase continuous-time plants and is robust with respect to unmodeled dynamics and bounded disturbances. The computational complexity of the continuous-time adaptive LQ control scheme is improved by using a hybrid adaptive law which requires the solution of an algebraic Riccati equation at each interval of time rather than at each time t. >

Robust Adaptive LQ Control Scheme

The certainty equivalence principle is used to combine a robust adaptive law with a control structure from the linear quadratic (LQ) control design. The resulting adaptive control scheme is applicable to minimum and non-minimum phase continuous-time plants and is robust with respect to unmodeled dynamics and bounded disturbances. The computational complexity of the continuous-time adaptive LQ control scheme is improved by using a hybrid adaptive law.