Based on the Multi Variable System Design and Parameter Tuning Method of PID Controller

In this paper, an innovative design method of PID controller based on genetic algorithm tuning parameters, VHDL description and FPGA implementation is proposed. The parameters of the PID controller are optimized by using genetic algorithm. The intelligent PID controller based on genetic algorithm is realized by using FPGA. During the realization process, the functional modules of the system are divided based on top-down design method. Each module of the system is described with VHDL language. Finally, the closed loop tests of the intelligent PID controller based on FPGA and genetic algorithm are implemented by means of DSP Builder and Matlab/Simulink. Simulation results have shown that the design method of the intelligent PID controller based on FPGA and genetic algorithm is verified, and it has some advantages such as design flexible, self-tuning on line, high reliability, short cycle of technical development, high running speed and so on. This intelligent PID controller based on FPGA and genetic algorithm can be applied in high control precision digital control system with high speed responsibility and high stability.

A simple tuning method for multiloop PID controllers will be presented in this article. The method is suited for PID algorithms with no proportional and derivative kick. This tuning method is derived from a controller synthesis method with a control performance specification of 5% overshoot on servo response. Depending on the interaction natures of the multiloop systems, tuning based on the diagonal elements of the model or further detuning may be necessary. For systems with a relative gain array [RGA(λii)] < 1, a detuning factor based on this information is proposed. The information needed for controller tuning purposes is the dynamic model parameters of the diagonal elements and the process gain information of the off-diagonal elements. The tuning method procedure is very simple and straightforward, utilizing only nth identification tests with n as the number of the interacting control loops. The tuning method can easily be applied to various industrial situations with almost no need for a priori process knowledge.

Variable-order fuzzy fractional PID controller

When a controlled object has a nonlinear characteristic, a good control result is not always obtained with fixed PID gains. This paper proposes a design method of a nonlinear PID controller using a neural network to overcome the problem. In the proposed controller, PID gains are tuned online by a neural network and a controlled object is controlled by the PID controller with the tuned PID gains. The neural network learns by a learning algorithm based on the Extended-Fictitious Reference Iterative Tuning (E-FRIT) and the backpropagation. The FRIT is a method that tunes control parameters directly by using a set of operating data. The main advantage of the FRIT is that the parameters can be determined without any mathematical model. The FRIT evaluates only a control response, whereas the E-FRIT does it as well as the difference of manipulated variable. In this paper, the E-FRIT is utilized for a learning algorithm of a neural network. Simulation examples are provided to show an effectiveness of the proposed method by simulation examples.

This paper concerns a tuning method for PID controller using optimization subject to constraints on derivatives of control input. To evaluate the control performance, the responses to load disturbance and reference input changes are presented compared to those by the partial model matching method. Moreover, it is found that the PID controller tuned by this optimization technique is somewhat robust and effective enough for practical applications.

In this paper, we introduce a procedure to assess the performance of three particular systems, when the orders of the integrator and differentiator of a fractional PID controller are changed in a range of values. At first, a conventional tuning method for PID controllers is used, and then, the orders are changed individually. The dynamical response is analyzed in transient state as well as when a load disturbance is introduced.

The paper studies the discrete event model-based PID controller. The structure of the networked controller is constructed. The structure is reduced for stability investigation. Than the automatic tuning method of PID controller and the synthesis of the model is presented. The stability theorem for a known process is formulated and proved using piecewise quadratic Lyapunov function. Finally, the numeric example of the whole process is shown.

In this paper, a frequency response based design method of PID controller is proposed for higher order (HO)/-plus delay time (HOPDT) systems. The HO/-PDT models are converted into real and imaginary part at a frequency where a criteria similar to amplitude and phase margin is utilized to get the constraints on the parameters of the controllers. To reject noise and load disturbances, the constraints given by sensitivity and complementary sensitivity function are also considered. The proposed method has superior features for systems with high order, time delays and monotonic or oscillatory responses. Three simulation examples are included to show the effectiveness, simplicity and applicability of the proposed method.

A new design method for PID controller using user-specified gain margin and phase margin for delayed systems has been proposed. The proposed PID controller is particularly useful in auto-tuning. The controller parameters are calculated using several approximations and elimination processes. The robustness of the proposed controller is verified by different simulation examples.

This paper proposes a fractional order PID analytical design framework for industrial robot based on digital twin. The effectiveness of the digital twin real-time optimization framework is verified by the simulation of PMSM motor speed control. The digital twin framework implemented in this paper consists of three following parts: multi-domain modeling, behavioral matching and control optimization. Firstly, the physical system is modeled to realize the omni-directional monitoring of robot and the kinematic simulation of single-axis motor. A model similar to the real physical system can be obtained in the step of behavioral matching, which is conducive to the next step of controller parameter optimization. The analytical design method of the five-parameter fractional order PID controller is then presented to optimize the parameters based on the accurate model after behavioral matching, so that the control system can meet the given frequency domain specifications and the required tracking performance. The simulation results show that the fractional order PID controller is robust to loop gain changes. In terms of time domain performance specifications like rise time, overshoot, and adjustment time, fractional order PID controller performs better than integer order PID controller.

Motivation: In designing linear feedback systems, tracking quality specifications are typically mapped into admissible domains in the complex plane and then the root locus technique is used to synthesize a controller that places closed loop poles in the desired locations. This methodology motivates the first goal of this chapter: to generalize the notion of admissible domains and the root locus technique to LPNI systems. Accomplishing this goal leads to a quasilinear method for PID controller design.

An analytical approach for tuning fractional PID controllers based on the frequency response of the system is addressed in this paper. Fractional PID controller inherits all advantages of conventional PID controllers and also has additional degrees of freedom. Based on their frequency response a new method of tuning is proposed in this paper, which is inspired from the previous works associated with this topic. Then the same method is validated by applying for attitude control of Reusable launch vehicle. The robustness study of the whole system is also carried out.

In the Ziegler-Nichols method of PID controller tuning the ultimate gain and the ultimate period were determined by closed loop test. In practice it is very difficult to conduct a closed loop test in process industries. Moreover the ultimate gain and period cannot be easily determined by closed loop test if the process has a long time delay, on-off control or if an integrating element present in the process. To overcome this difficulty, the ultimate gain and period were determined by simulation of the process model obtained from open loop test. The PID tuning parameters were then calculated by making use of Ziegler-Nichols relation.

This paper presents a method for PID controller design which can achieve dominant pole assignment using two of the controller parameters. The non-dominant poles are restricted on the left of the line s = σ̂, where σ̂ is the minimum feasible value, called as the feasibility border. It is obvious that a dominant pole assignment is not practical if σ̂ is close to the real parts of the required dominant poles. Hence, finding σ̂ for a given system is very important. The method, which parameterizes all such controllers in order to allow further design criteria, can be applied to other kinds of low-order compensators.

This paper proposes a small-sized two-wheeled Unmanned Aerial Vehicle(UAV) in order to get into and visually inspect a narrow part, for example, a bridge bearing. First, we present the two-wheeled multi-copter loading with a digital control device to downsize the wheel of the size of 66cm to size of 25cm. Second, for high accuracy positioning of inspection, a new design method of the optimal digital PID controller for the multicopter is proposed. The optimal controller minimizes a cost functional. The design method is reduced to the standard LQR method and is straightforward. The effectiveness is demonstrated by some flight experiments moving on a wall.