Performance-guaranteed Robust PID Controller Design for Systems with Unstable Zero

The proposed new method is applicable for control of linear stable single-input-single-output non-minimum phase systems even with unknown mathematical model and unstructured uncertainties. The control objective is to provide required nominal maximum overshoot and settling time of the controlled variable y(t). The proposed new controller design approach guarantees fulfillment of these performance measures specified by the designer for processes with unstable zero. The developed algorithm has been extended to guarantee robustness of the PID controller design for uncertain processes modelled by unstructured uncertainties, and verified on a vast batch of benchmark examples.

In this paper design and real-time implementation of robust PID controller is performed for a Twin Rotor MIMO System (TRMS) which is a laboratory scale set-up of a helicopter. The robust PID controller is designed employing Kharitonov stability theorem. The controller design is based on the linearised model of highly nonlinear TRMS. The performance of the compensated system is investigated through experimental results with the laboratory prototype model. The time domain responses for the main and tail rotors are found to be satisfactory. The controller provides comparable performances as presented in the literature for similar system.

The paper presents a robust PID control design method for spacecraft attitude tracking. Spacecraft control for large-angle control is subject to nonlinear couplings and uncertainties. Although nonlinear robust control design methods, such as nonlinear H/sub /spl infin// control can be applied to address these issues. The solving of the associated Hamilton-Jacobi equation is often extremely complicated and the resulting controller is not easy to implement. In the paper, the PID controller architecture is assumed for the spacecraft attitude control and concepts in nonlinear H/sub /spl infin// control theory are applied to obtain robustness properties. Results of both PD control and PID control are derived and applied to the ROCSAT-3 satellite of a science model system for verification.

Robust velocity and height control problem is dealt with for hypersonic vehicles subject to highly nonlinearity and uncertainties. The linear robust controller design for nonlinear systems suffers from the conservation problem, because the nonlinear dynamics are considered as uncertainties. In this paper, a feedback linearization controller is firstly applied to achieve the dynamic decoupling of the velocity and height channels. Then, robust controllers are designed for each channel to restrain the effects of the parametric uncertainties, external disturbances, and nonlinear dynamics, which cannot be counteracted accurately by the feedback linearization technique. This method can guarantee the robust stability and robust tracking properties of the closed-loop control system, while the conservation of the robust controller design can be reduced because the nonlinear information of dynamic system is used. Simulation comparisons are given to show the advantages of the proposed robust nonlinear control method.

This paper reviews robust feedback control applications in power system. Robust control concept in power system control area evolves by the way of uncertainty modeling. Uncertainties can be caused by variation of loading, load parameters, network topology and machine parameters. One direct way to take into consideration of uncertainties is to enumerate various system operating conditions and use a set of linear time invariant systems to model the power systems. Enumeration method is used in robust control signal selection and robust controller design. Another way is to model uncertainties as structured or unstructured uncertainties. Controllers are designed based on nominal system condition to tolerate uncertainty as much as possible. The controller synthesis problem is solved by either Algebraic Ricatti Equation (ARE) or Linear Matrix Inequality (LMI). LMI is shown to be more flexible in controller design since it provides a way to specify system dynamic performance. Most recently, linear parameter varying (LPV) concept expands the use of enumeration method to express a set of linear time invariant (LTI) systems with state space dependent on linear parameters. LPV based control methods extend gain scheduling to design linear control for each operating conditions and overall a nonlinear controller for the varying parameter system.

Hybrid Passive/Active Control Performance in Buildings Using Robust Control Design Approaches

We propose a robust control system which has robustness for disturbance and can deal with a nonlinear system with partially unknown structure by fusing reinforcement learning and robust control theory. First, we solved an optimal control problem without using unknown part of functions of the system, using neural network and the repetition learning of reinforcement learning algorithm. Second, we built the robust reinforcement learning control system which permits uncertainty and has robustness for disturbance by fusing the idea of H infinity control theory with above system.

Robust STATCOM voltage controller design using loop-shaping technique

A novel methodology is proposed for robust gain-scheduled PID controller design for uncertain LPV systems. The proposed design procedure is based on the parameter-dependent quadratic stability approach. A new uncertain LPV system model has been introduced in this paper. To access the performance quality the notion of a parameter varying guaranteed cost is used. Numerical examples show the benefit of the proposed method.

This paper presents the methodology of design of a nonlinear robust controller for attitude regulation and its implementation in an experimental platform of an unmanned aerial vehicle (UAV) quadrotor. Details on the kinematic and dynamic modeling based on the Euler-Lagrange formalism are provided, as well as the particulars of the design of a nonlinear robust H-infinity PID controller to regulate the rotational moments. The performance and effectiveness of the proposed controller are tested in a simulation and an experimental platform. The performance of the proposed controller is compared with a conventional PID controller by using the integral square error (ISE) as performance parameter. Experimental results help to demonstrate the correct operation of the system for real-time applications in the presence of unmodeled dynamics and the uncertainties of the parameters.

Decision letter for "New design of robust PID controller based on meta‐heuristic algorithms for wind energy conversion system"

A robust adaptive backstepping controller design method is proposed for a nonlinear system with uncertainty and unknown parameters based on the CMAC neural network. The CMAC neural network was used not only to approach the arbitrary model uncertainties but also to eliminate the bad effects of the uncertainties with robust terms in the controller and virtual controllers. Novel update and control laws are proposed to guarantee that all the signals in the closed-loop control system are uniformly ultimately bounded in a Lyapunov sense. Simulation experimental showed the tracking control of the nonlinear system is achieved and this method is effectual.

A nonlinear robust controller design method is proposed for the lateral control of heavy vehicles for automated highway systems. In the controller design, the actuator dynamics is explicitly taken into account. A first order pre-filter is introduced to reduce chattering which is inherent in the nonlinear robust controller and to prevent the saturation in the front wheel steering angle and steering system slew rate. A constructive backstepping design technique is utilized in the design of a robust controller for the augmented system. Simulation results are shown.

The problem of robust velocity and height control is dealt with for hypersonic vehicles subject to high nonlinearity and uncertainties. Robust linear controller design for nonlinear systems suffers from the problem of conservation because the nonlinear dynamics are considered as uncertainties. In this paper, a feedback linearization controller is firstly applied to achieve dynamic decoupling of the velocity and height channels. Robust controllers are then designed for each channel to achieve the desired tracking and restrain the effects of parametric uncertainties, external disturbances, and nonlinear dynamics, which cannot be accurately counteracted by the feedback linearization technique. This method can guarantee the robust stability and robust tracking properties of the closed-loop control system. Moreover, the conservation of the robust controller design can be reduced because the nonlinear information of the dynamic system is used. Simulation results are given to show the advantages of the proposed robust nonlinear control method compared with its linear counterpart.

A systematic and complete method to design robust predictive controllers for unconstrained linear systems is proposed. The synthesis procedure is based on rigorous theoretical foundations, without resorting to approximations or ad hoc design guidelines, yet it remains a viable tool for practical application. A significant feature is that the robust predictive controller retains the servo performance of a nominal predictive controller designed using conventional methods. In addition, the robust predictive controller can be designed to guarantee perfect steady‐state rejection of asymptotically constant disturbances. The robust design method is developed for systems affected by unmodeled dynamics and is based on solving a discrete‐time model‐matching problem. It is shown that the robust controller can be classified legitimately as a predictive controller because it minimizes the same performance functional as the nominal predictive controller. An illustrative design example is given.