In the paper, problem of proper tuning of second-order Reduced Active Disturbance Rejection Controller (RADRC2) is considered in application for industrial processes with significant (but not dominant) delay time. For First-Order plus Delay Time (FOPDT) and Second-Order plus Delay Time (SOPDT) processes, tuning rules are derived to provide minimal Integral Absolute Error (IAE) assuming robustness defined by gain and phase margins. Derivation was made using optimization procedure based on D-partition method. The paper also shows results of comprehensive simulation validation based on examplary benchmark processes of more complex dynamics as well as final practical validation. Comparison with PID controller shows that RADRC2 tuned by the proposed rules can be practical alternative for industrial control applications.

The purpose of this paper is to show possibility and advantages of initial control plane reproduction for an adaptive fuzzy controller. Usually the fuzzy control is used when the object is not very well known. Yet the truth is, however, that some, at least general information about the object, is available. Usually, in such a case, optimization algorithms are used to tune the control structure. The purpose of this article is to show how to find a starting point that is closer to optimum than a statistically random point, and this way to obtain better results in a shorter time.

In this paper, the PLC-based (Programmable Logic Controller) industrial implementation in the form of the general-purpose function block for ADRC (Active Disturbance Rejection Controller) is presented. The details of practical aspects are discussed because their reliable implementation is not trivial for higher order ADRC. Additional important novelties discussed in the paper are the impact of the derivative backoff and the method that significantly simplifies tuning of higher order ADRC by avoiding the usual trial and error procedure. The results of the practical validation of the suggested concepts complete the paper and show the potential industrial applicability of ADRC.

In this paper, the adaptive control based on symbolic solution of Diophantine equation is used to suppress circular plate vibrations. It is assumed that the system to be regulated is unknown. The plate is excited by a uniform force over the bottom surface generated by a loudspeaker. The axially-symmetrical vibrations of the plate are measured by the application of the strain sensors located along the plate radius, and two centrally placed piezoceramic discs are used to cancel the plate vibrations. The adaptive control scheme presented in this work has the ability to calculate the error sensor signals, to compute the control effort and to apply it to the actuator within one sampling period. For precise identification of system model the regularized RLS algorithm has been applied. Self-tuning controller of RST type, derived for the assumed system model of the 4th order is used to suppress the plate vibration. Some numerical examples illustrating the improvement gained by incorporating adaptive control are demonstrated.

This paper presents a state feedback controller (SFC) for position control of PMSM servo-drive. Firstly, a short review of the commonly used swarm-based optimization algorithms for tuning of SFC is presented. Then designing process of current control loop as well as of SFC with feedforward path is depicted. Next, coefficients of controller are tuned by using an artificial bee colony (ABC) optimization algorithm. Three of the most commonly applied tuning methods (i.e. linear-quadratic optimization, pole placement technique and direct selection of coefficients) are used and investigated in terms of positioning performance, disturbance compensation and robustness against plant parameter changes. Simulation analysis is supported by experimental tests conducted on laboratory stand with modern PMSM servo-drive.

In renewable systems, there may be conditions that can be either network error or power transmission line and environmental conditions such as when the wind speed is unbalanced and the wind turbine is connected to the grid. In this case, the control system is not damaged and will remain stable in the power transmission system. Voltage stability studies on an independent wind turbine at fault time and after fixing the error is one of the topics that can strengthen the future of independent collections. At the time of the fault, the network current increases dramatically, resulting in a higher voltage drop. Hence the talk of fast voltage recovery during error and after fixing the error and protection of rotor and grid side converters against the fault current and also protection against rising DC voltage (which sharply increases during error) is highly regarded. So, several improvements have been made to the construction of a doubly-fed induction generator (DFIG) turbine such as:

a) error detection system,

b) DC link protection,

c) crow bar circuit,

d) block of the rotor and stator side converters,

e) injecting reactive power during error,

f) nonlinear control design for turbine blades,

g) tuning and harmonization of controllers used to keep up the power quality and to stabilize the system output voltage in the power grid.

First, the dynamic models of a wind turbine, gearbox, and DFIG are presented. Then the controllers are modeled. The results of the simulation have been validated in MATLAB/Simulink.

This paper proposes a practical tuning of closed loops with model based predictive control. The data assumed to be known from the process is the result of the bump test commonly applied in industry and known in engineering as step response data. A simplified context is assumed such that no prior know-how is required from the plant operator. The relevance of this assumption is very realistic in the context of first time users, both for industrial operators and as educational competence of first hand student training. A first order plus dead time is approximated and the controller parameters immediately follow by heuristic rules. Analysis has been performed in simulation on representative dynamics with guidelines for the various types of processes. Three single-input-single-output experimental setups have been used with no expert users available in different locations – both educational and industrial – these setups are representative for practical cases: a variable time delay dominant system, a non-minimum phase system and an open loop unstable system. Furthermore, in a multivariable control context, a train of separation columns has been tested for control in simulation, followed by experimental tests on a laboratory system with similar dynamics, i.e. a sextuple coupled water tank system. The results indicate the proposed methodology is suitable for hands-on tuning of predictive control loops with some limitations on performance and multivariable process control.