where $q_1$ and $q_2$ are the angular positions, and $u$ is a torque input. The physical parameters $g, I, J, k, L,$ and $M$ are all positive. Taking $y=q_1$ as the output, it can be verified that $y$ satisfies the fourth-order differential equation
We consider a single-input-single-output nonlinear system which can be represented globally by an input-output model. The system is input-output linearizable by feedback and is required to satisfy a minimum phase condition. The nonlinearities are not required to satisfy any global growth condition. The model depends linearly on unknown parameters which belong to a known compact convex set. We design a semiglobal adaptive output feedback controller which ensures that the output of the system tracks any given reference signal which is bounded and has bounded derivatives up to the nth order, where n is the order of the system. The reference signal and its derivatives are assumed to belong to a known compact set. It is also assumed to be sufficiently rich to satisfy a persistence of excitation condition. The design process is simple. First we assume that the output and its derivatives are available for feedback and design the adaptive controller as a state feedback controller in appropriate coordinates. Then we saturate the controller outside a domain of interest and use a high-gain observer to estimate the derivatives of the output. We prove, via asymptotic analysis, that when the speed of the high-gain observer is sufficiently high, the adaptive output feedback controller recovers the performance achieved under the state feedback one
The model of the MAGLEV system is unstable and nonlinear
$$
m\ddot{x}=mg-\dfrac{K_{c}V^{2}}{x^{2}},
$$
where $x$ is the metal ball position being the system output, $V$ is the system input as the voltage. Other parameters are $m$ as the mass of the metal ball, $K_c$ as constant for magnet circuit, and $g$ is the gravitational acceleration of 9.8 m/s$^2$. A free-body diagram is shown also in the attached image.
Identification of a practical process, especially if unstable, is challenging as its model is generally stochastic and nonlinear. In this work we consider a class of unstable processes where the model is identified in a closed-loop operating regime. Important issues in identification are addressed, namely: identification scheme, the closed loop identification of unstable plants, choice of sampling period, and constraints on the estimated model parameters. Further the structure of the identified model may not be identical to that of the physical system due to noise artifacts, and inability to capture faster dynamics. Generally least-squares identification is employed to estimate the parameters of the system wherein all the coefficients of numerator and the denominator coefficients of system transfer function are estimated. In many practical system there are constraints on the model parameters. The identified coefficients using the conventional scheme may not obey the constraint. In this work a novel constrained least-squares identification scheme is proposed where in a priori known structural constraint is factored in parameter estimation. This scheme is evaluated on a physical magnetic lévitation system.
where $x_1(t)$ : angle difference between truck and trailer. $x_2(t)$ : angle of trailer. $x_3(t)$ : vertical position of rear of trailer, $u(t)$ : steering angle, $T$ : sampling time. In this example, the parameters are $T=2.0s$, $l=2.8m$, $L=5.5m$, $v=-1.0m/s$.
This paper deals with the stabilization problem for discrete-time nonlinear systems that are represented by the Takagi - Sugeno fuzzy model. By the multiple fuzzy Lyapunov function and the three-index algebraic combination technique, a new stabilization condition is developed. The condition is expressed in the form of linear matrix inequalities (LMIs) and proved to be less conservative than existing results in the literature. Finally, a truck-trailer system is given to illustrate the novelty of the proposed approach.
This paper deals with the measurement of the frequency response of the mechanical part of a drive for the parameter identification of a plant. The system is stimulated by pseudorandom binary signals. The measurement of the frequency response is part of a system identification procedure being carried out during an automatic commissioning of the drive. For the calculation of the frequency response of the mechanics, the Welch-method is applied for spectral analysis. The Welch-method is known from the fields of communications and measurement engineering. This paper addresses the application of this powerful method for the identification of electrical drives. Investigations have pointed out that the pure utilization of conventional identification strategies does not yield satisfying experimental results. Experimental results presented in this paper point out clearly the efficiency and flexibility of the proposed Welch-method. This paper contains many practical aspects and realization details that are important for their implementation on industrial systems. Although in principle, commercial software tools can be utilized for identifying the parameters of the plant, this paper addresses the implementation of the necessary identification algorithms on the embedded control electronics of the drives. The utilization of the Levenberg-Marquardt-algorithm yields excellent results for the identified parameters on the basis of the measured frequency response data.
$T_M$ and $T_L$ are the run-up times of the motor and the load. The nonrigid shaft of the two-mass-configuration is modeled as a damper-spring-system. $T_C$ is the normalized spring-constant and $d$ is the related damping of the spring.
This paper deals with the measurement of the frequency response of the mechanical part of a drive for the parameter identification of a plant. The system is stimulated by pseudorandom binary signals. The measurement of the frequency response is part of a system identification procedure being carried out during an automatic commissioning of the drive. For the calculation of the frequency response of the mechanics, the Welch-method is applied for spectral analysis. The Welch-method is known from the fields of communications and measurement engineering. This paper addresses the application of this powerful method for the identification of electrical drives. Investigations have pointed out that the pure utilization of conventional identification strategies does not yield satisfying experimental results. Experimental results presented in this paper point out clearly the efficiency and flexibility of the proposed Welch-method. This paper contains many practical aspects and realization details that are important for their implementation on industrial systems. Although in principle, commercial software tools can be utilized for identifying the parameters of the plant, this paper addresses the implementation of the necessary identification algorithms on the embedded control electronics of the drives. The utilization of the Levenberg-Marquardt-algorithm yields excellent results for the identified parameters on the basis of the measured frequency response data.